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GitHub Repo Deep-Learning-Based-Image-Compression

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Introduction

The paper list about deep learning based image compression

Paper List

Generative compression

Title	Pub. & Date
Rate-Distortion-Cognition Controllable Versatile Neural Image Compression	ECCV 2025
Lossy Image Compression with Foundation Diffusion Models	ECCV 2025
EGIC: Enhanced Low-Bit-Rate Generative Image Compression Guided by Semantic Segmentation	ECCV 2025
DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer	ICCV 2025
StableCodec: Taming One-Step Diffusion for Extreme Image Compression	ICCV 2025
DLF: Extreme Image Compression with Dual-generative Latent Fusion	ICCV 2025
Cross-Granularity Online Optimization with Masked Compensated Information for Learned Image Compression	ICCV 2025
Decouple Distortion from Perception: Region Adaptive Diffusion for Extreme-low Bitrate Perception Image Compression	CVPR 2025
Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion	ICML 2025
Zero-Shot Image Compression with Diffusion-Based Posterior Sampling	arXiv 2025
Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaptation	ICLR 2025
Conditional Latent Coding with Learnable Synthesized Reference for Deep Image Compression	AAAI 2025
GLIC: General Format Learned Image Compression	AAAI 2025
Efficient Progressive Image Compression with Variance-aware Masking	arXiv 2024
UniMIC: Towards Universal Multi-modality Perceptual Image Compression	arXiv 2024
Progressive Compression with Universally Quantized Diffusion Models	arXiv 2024
Controllable Distortion-Perception Tradeoff Through Latent Diffusion for Neural Image Compression	AAAI 2025
ComNeck: Bridging Compressed Image Latents and Multimodal LLMs via Universal Transform-Neck	arXiv 2024
Stable Diffusion is a Natural Cross-Modal Decoder for Layered AI-generated Image Compression	arXiv 2024
Linearly transformed color guide for low-bitrate diffusion based image compression	TIP 2024
JPEG-LM: LLMs as Image Generators with Canonical Codec Representations	arXiv 2024
Image Encryption and Compression Based on Reversed Diffusion Model	PCS 2024
Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaption	arXiv 2024
Machine Perception-Driven Facial Image Compression: A Layered Generative Approach	TCSVT 2024
Understanding is Compression	arXiv 2024
High Efficiency Image Compression for Large Visual-Language Models	arXiv 2024
Consistency Guided Diffusion Model with Neural Syntax for Perceptual Image Compression	ACM MM 2024
Zero-Shot Image Compression with Diffusion-Based Posterior Sampling	arXiv 2024
High Frequency Matters: Uncertainty Guided Image Compression with Wavelet Diffusion	arXiv 2024
Exploiting Inter-Image Similarity Prior for Low-Bitrate Remote Sensing Image Compression	arXiv 2024
LDM-RSIC: Exploring Distortion Prior with Latent Diffusion Models for Remote Sensing Image Compression	arXiv 2024
Generative Latent Coding for Ultra-Low Bitrate Image Compression	CVPR 2024
Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaption	arXiv 2024
CMC-Bench: Towards a New Paradigm of Visual Signal Compression	arXiv 2024

Lossless Compression

Title	Pub. & Date
Fitted Neural Lossless Image Compression	CVPR 2025
Large Language Models for Lossless Image Compression: Next-Pixel Prediction in Language Space is All You Need	NeurIPS 2026
SEEC: Segmentation-Assisted Multi-Entropy Models for Learned Lossless Image Compression	arXiv 2025
CALLIC: Content Adaptive Learning for Lossless Image Compression	AAAI 2025
Learning Lossless Compression for High Bit-Depth Volumetric Medical Image	arXiv 2024
Rate-Complexity Optimization in Lossless Neural-Based Image Compression	ICIP 2024
Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding	arXiv 2024
Hybrid-context-based multi-prior entropy modeling for learned lossless image compression	Pattern Recognition 2024
Learned Lossless Image Compression based on Bit Plane Slicing	Pattern Recognition 2024

Variable Rate / Scalable Compression

Title	Pub. & Date
Towards Scalable Compression with Universally Quantized Diffusion Models	NeurIPSW 2024
Flexible image decoding in learned image compression	NeurIPSW 2024
Variable-size Symmetry-based Graph Fourier Transforms for image compression	arXiv 2024
Latent Variables Coding for Perceptual Image Compression	ACM MM 2024
STanH: Parametric Quantization for Variable Rate Learned Image Compression	arXiv 2024
RAQ-VAE: Rate-Adaptive Vector-Quantized Variational Autoencoder	Arxiv 2024

Quantization

Title	Pub. & Date
Bridging the Gap between Gaussian Diffusion Models and Universal Quantization for Image Compression	CVPR 2025
Bridging the Gap between Diffusion Models and Universal Quantization for Image Compression	NeurIPSW 2024
Learning Optimal Lattice Vector Quantizers for End-to-end Neural Image Compression	arXiv 2024
Convolution Filter Compression via Sparse Linear Combinations of Quantized Basis	TNNLS 2024
Lossy Image Compression with Stochastic Quantization	arXiv 2024
Quantization-free Lossy Image Compression Using Integer Matrix Factorization	arXiv 2024
DeepHQ: Learned Hierarchical Quantizer for Progressive Deep Image Coding	arXiv 2024
A Quantization Loss Compensation Network for Remote Sensing Image Compression	PCS 2024
Image and Video Tokenization with Binary Spherical Quantization	arXiv 2024
NLIC: Non-uniform Quantization based Learned Image Compression	TCSVT 2024

Entropy Model

Title	Pub. & Date
Learned Image Compression with Hierarchical Progressive Context Modeling	ICCV 2025
Test-time Adaptation for Image Compression with Distribution Regularization	ICLR 2025
Exploring Autoregressive Vision Foundation Models for Image Compression	arXiv 2025
Learned Image Compression Framework with Quad-Prior Entropy Model	arXiv 2025
FlashGMM: Fast Gaussian Mixture Entropy Model for Learned Image Compression	arXiv 2025
Generalized Gaussian Model for Learned Image Compression	arXiv 2024
The Gap Between Principle and Practice of Lossy Image Coding	arXiv 2025
Group Image Compression for Dual Use of Machine and Human Vision	TCSVT 2024
Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec	arXiv 2024
Delta-ICM: Entropy Modeling with Delta Function for Learned Image Compression	arXiv 2024
Causal Context Adjustment Loss for Learned Image Compression	NeurIPS 2024
Spatial-Temporal Context Model for Remote Sensing Imagery Compression	ACM MM 2024
WeConvene: Learned Image Compression with Wavelet-Domain Convolution and Entropy Model	arXiv 2024
Rethinking Learned Image Compression: Context is All You Need	arXiv 2024
Bidirectional Stereo Image Compression with Cross-Dimensional Entropy Model	arXiv 2024

Achitecture

Title	Pub. & Date
WeConvene: Learned Image Compression with Wavelet-Domain Convolution and Entropy Model	ECCV 2025
Region-Adaptive Transform with Segmentation Prior for Image Compression	ECCV 2025
BaSIC: BayesNet Structure Learning for Computational Scalable Neural Image Compression	ECCV 2025
Efficient Learned Image Compression Through Knowledge Distillation	ICCV 2025
Cassic: Towards Content-Adaptive State-Space Models for Learned Image Compression	ICCV 2025
PICD: Versatile Perceptual Image Compression with Diffusion Rendering	CVPR 2025
MambaIC: State Space Models for High-Performance Learned Image Compression	CVPR 2025
Unraveling Neural Cellular Automata for Lightweight Image Compression	arXiv 2025
Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding	ICLR 2025
Learning Optimal Linear Block Transform by Rate Distortion Minimization	arXiv 2024
Sparse Point Clouds Assisted Learned Image Compression	TCSVT 2024
On Disentangled Training for Nonlinear Transform in Learned Image Compression	arXiv 2025
Test-time adaptation for image compression with distribution regularization	arXiv 2024
Effectiveness of learning-based image codecs on fingerprint storage	arXiv 2024
Gabic: Graph-Based Attention Block for Image Compression	ICIP 2024
Streaming Neural Images	ICIP 2024
Bi-Level Spatial and Channel-aware Transformer for Learned Image Compression	arXiv 2024
Extreme Low Bitrate Image Compression System for Mobile Deployment	MMSP 2024
Window-based Channel Attention for Wavelet-enhanced Learned Image Compression	arXiv 2024
Feature Enhanced Learning Image Compression With Recurrent Criss-Cross Attention	ICIP 2024
Approximately Invertible Neural Network for Learned Image Compression	arXiv 2024
Rate-Distortion-Perception Controllable Joint Source-Channel Coding for High-Fidelity Generative Communications	Arxiv 2024
Structured Pruning and Quantization for Learned Image Compression	ICIP 2024
Practical Learned Image Compression with Online Encoder Optimization	PCS 2024
On Efficient Neural Network Architectures for Image Compression	arXiv 2024
A Study on the Effect of Color Spaces in Learned Image Compression	arXiv 2024
Learning-Based Conditional Image Compression	ISCAS 2024
Asymmetric Neural Image Compression with High-Preserving Information	ISCAS 2024
Wavelet-like Transform with Subbands Fusion in Decoupled Structure for Deep Image Compression	PCS 2024
FDNet: Frequency Decomposition Network for Learned Image Compression	TCSVT 2024
Image Compression for Machine and Human Vision with Spatial-Frequency Adaptation	arXiv 2024
Rate-Distortion-Cognition Controllable Versatile Neural Image Compression	arXiv 2024
MambaVC: Learned Visual Compression with Selective State Spaces	arXiv 2024

Screen Content Image

Title	Pub. & Date
Learned HDR Image Compression for Perceptually Optimal Storage and Display	ECCV 2025
Efficient Screen Content Image Compression via Superpixel-based Content Aggregation and Dynamic Feature Fusion	IJCAI 2024
DSCIC: Deep Screen Content Image Compression	TCSVT 2024

HDR Image

Title	Pub. & Date
Breaking Boundaries: Unifying Imaging and Compression for HDR Image Compression	TIP 2025
Learned HDR Image Compression for Perceptually Optimal Storage and Display	arXiv 2024

Image coding for machine vision

Title	Pub. & Date
Image Compression for Machine and Human Vision With Spatial-Frequency Adaptation	ECCV 2025
A Unified Image Compression Method for Human Perception and Multiple Vision Tasks	ECCV 2025
Neural Image Compression with Regional Decoding	ToMM 2024
Saliency Segmentation Oriented Deep Image Compression With Novel Bit Allocation	TIP 2024
LL-ICM: Image Compression for Low-level Machine Vision via Large Vision-Language Model	arXiv 2024
Task-Adapted Learnable Embedded Quantization for Scalable Human-Machine Image Compression	TCSVT 2025
An Efficient Adaptive Compression Method for Human Perception and Machine Vision Tasks	arXiv 2025
Unified Coding for Both Human Perception and Generalized Machine Analytics with CLIP Supervision	arXiv 2025
All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path Aggregation	arXiv 2024
Tell Codec What Worth Compressing: Semantically Disentangled Image Coding for Machine with LMMs	arXiv 2024
Feature-Preserving Rate-Distortion Optimization in Image Coding for Machines	arXiv 2024
Group Image Compression for Dual Use of Machine and Human Vision	TCSVT 2024
Feature-Preserving Rate-Distortion Optimization in Image Coding for Machines	MMSP 2024
Compression of Self-Supervised Representations for Machine Vision	arXiv 2024
Learned Image Compression for Both Humans and Machines via Dynamic Adaptation	ICIP 2024
Image Coding For Machine Via Analytics-Driven Appearance Redundancy Reduction	ICIP 2024
Saliency Map-Guided End-to-End Image Coding for Machines	SPL 2024
Redundancy Removal Module for Reducing the Bitrates of Image Coding for Machines	ISCAS 2024

Medical Image

Title	Pub. & Date
Versatile Volumetric Medical Image Coding for Human-Machine Vision	arXiv 2024
UniCompress: Enhancing Multi-Data Medical Image Compression with Knowledge Distillation	Arxiv 2024

Implicit Neural Representation

Title	Pub. & Date
LotteryCodec: Searching the Implicit Representation in a Random Network for Low-Complexity Image Compression	ICML 2025
HyperCool: Reducing Encoding Cost in Overfitted Codecs with Hypernetworks	Arxiv 2025
Redefining Visual Quality: The Impact of Loss Functions on INR-Based Image Compression	ICIP 2024
Implicit Neural Image Field for Biological Microscopy Image Compression	ICIP 2024

Panoramic/stereo Image

Title	Pub. & Date
Bidirectional Stereo Image Compression with Cross-Dimensional Entropy Model	ECCV 2025
Learning Content-Weighted Pseudocylindrical Representation for 360° Image Compression	ICIP 2024

Benchmark & Dataset & Survey

Title	Pub. & Date
JPEG AI: The First International Standard for Image Coding Based on an End-to-End Learning-Based Approach	IEEE MultiMedia 2024
OpenDIC: An Open-Source Library and Performance Evaluation for Deep-learning-based Image Compression	ACMMM 2024

Others

Title	Pub. & Date
Dataset Distillation as Data Compression: A Rate-Utility Perspective	ICCV 2025
Balanced Rate-Distortion Optimization in Learned Image Compression	CVPR 2025
Privacy-Shielded Image Compression: Defending Against Exploitation from Vision-Language Pretrained Models	ICML 2025
Synonymous Variational Inference for Perceptual Image Compression	ICML 2025
CAMSIC: Content-aware Masked Image Modeling Transformer for Stereo Image Compression	AAAI 2025
Robust and Transferable Backdoor Attacks Against Deep Image Compression With Selective Frequency Prior	arXiv 2024
JPEG AI Image Compression Visual Artifacts: Detection Methods and Dataset	arXiv 2024
An Information-Theoretic Regularizer for Lossy Neural Image Compression	ICCV 2025
Deep Learning-Based Image Compression for Wireless Communications: Impacts on Reliability, Throughput, and Latency	arXiv 2024
HNR-ISC: Hybrid Neural Representation for Image Set Compression	TMM 2024
Is JPEG AI going to change image forensics?	arXiv 2024
2D Gaussian Splatting for Image Compression	ATSIP 2024
Cross-Platform Neural Video Coding: A Case Study	arXiv 2024
Gone With the Bits: Benchmarking Bias in Facial Phenotype Degradation Under Low-Rate Neural Compression	ICMLW 2024
Few-Shot Domain Adaptation for Learned Image Compression	AAAI 2025

✔2024

(SPL 2024) OMR-NET: A Two-Stage Octave Multi-Scale Residual Network for Screen Content Image Compression Jiang S, Ren T, Fu C, et al. paper
(TPAMI 2024) I2C: Invertible Continuous Codec for High-Fidelity Variable-Rate Image Compression Cai, Shilv and Chen, Liqun and Zhang, Zhijun and Zhao, Xiangyun and Zhou, Jiahuan and Peng, Yuxin and Yan, Luxin and Zhong, Sheng and Zou, Xu paper
(ICASSP 2024) Leveraging Redundancy in Feature for Efficient Learned Image CompressionN Qin, Peng and Bao, Youneng and Meng, Fanyang and Tan, Wen and Li, Chao and Wang, Genhong and Liang, Yongsheng paper
(ICASSP 2024) RATE-QUALITY BASED RATE CONTROL MODEL FOR NEURAL VIDEO COMPRESSION Liao, Shuhong and Jia, Chuanmin and Fan, Hongfei and Yan, Jingwen and Ma, Siwei paper
(ICASSP 2024) Enhancing Adversarial Training with Prior Knowledge Distillation for Robust Image Compression Zhi, Cao and Youneng, Bao and Fanyang, Meng and Chao, Li and Wen, Tan and Genhong, Wang and Yongsheng, Liangpaper
(AAAI 2024) Make Lossy Compression Meaningful for Low-Light Images Cai, Shilv and Chen, Liqun and Zhong, Sheng and Yan, Luxin and Zhou, Jiahuan and Zou, Xu paper
(AAAI 2024) End-to-End RGB-D Image Compression via Exploiting Channel-Modality Redundancy Zheng, Huiming and Gao, Wei paper
(CVPR 2024) Towards Backward-Compatible Continual Learning of Image Compression Duan, Zhihao and Lu, Ming and Yang, Justin and He, Jiangpeng and Ma, Zhan and Zhu, Fengqing paper
(NeurIPS 2024) Compression with bayesian implicit neural representations Guo, Zongyu and Flamich, Gergely and He, Jiajun and Chen, Zhibo and Hern{'a}ndez-Lobato, Jos{'e} Miguel paper
(TIP 2024) Bilateral Context Modeling for Residual Coding in Lossless 3D Medical Image Compression Liu, Xiangrui and Wang, Meng and Wang, Shiqi and Kwong, Sam paper
(TMM 2024) Neural Network Coding of Difference Updates for Efficient Distributed Learning Communication Sheng, Xihua and Li, Li and Liu, Dong and Li, Houqiang paper
(TCSVT 2024) FICNet: An End to End Network for Free-view Image Coding Yang, Chunhui and Yang, Jiayu and Zhai, Yongqi and Wang, Ronggangpaper
(TCSVT 2024) GroupedMixer: An Entropy Model with Group-wise Token-Mixers for Learned Image Compression Li, Daxin and Bai, Yuanchao and Wang, Kai and Jiang, Junjun and Liu, Xianming and Gao, Wen paper
(TCSVT 2024) Multirate Progressive Entropy Model for Learned Image Compression Li, Chao and Yin, Shanzhi and Jia, Chuanmin and Meng, Fanyang and Tian, Yonghong and Liang, Yongsheng paper
(TCSVT 2024) EUICN: An Efficient Underwater Image Compression Network Li, Mengyao and Shen, Liquan and Hua, Xia and Tian, Zhaoyi paper
(TCSVT 2024) Rate-Distortion Optimized Cross Modal Compression with Multiple Domains Gao, Junlong and Jia, Chuanmin and Huang, Zhimeng and Wang, Shanshe and Ma, Siwei and Gao, Wen paper
(ToMM 2024) Perceptual Quality-Oriented Rate Allocation via Distillation from End-to-End Image Compression Yang, Runyu and Liu, Dong and Ma, Siwei and Wu, Feng and Gao, Wen paper
(TGRS 2024) Remote Sensing Image Compression Based on High-Frequency and Low-Frequency Components Xiang, Shao and Liang, Qiaokang paper
(WCACV 2024) Neural Image Compression Using Masked Sparse Visual Representation Jiang, Wei and Wang, Wei and Chen, Yue paper
(PCS 2024) CoCliCo: Extremely low bitrate image compression based on CLIP semantic and tiny color map Bachard, Tom and Bordin, Tom and Maugey, Thomas paper
(IEVC 2024) The Effect of Edge Information in Stable Diffusion Applied to Image Coding Watanabe, Hiroshi and Chujoh, Takeshi and Fan, Zheming and Jin, Luoxu and Yasugi, Yukinobu and Ikai, Tomohiro and Hayami, Taiga and Hong, Sujun paper
(SPL 2024) Enhancing High-Resolution Image Compression Through Local-Global Joint Attention MechanismJiang, Zeyu and Liu, Xiaohong and Li, Aini and Wang, Guangyupaper
(SPL 2024) Learning-Based Image Compression With Parameter-Adaptive Rate-Constrained LossGuerin, Nilson D and da Silva, Renam Castro and Macchiavello, Brunopaper
(ICASSP 2024) Fine color guidance in diffusion models and its application to image compression at extremely low bitratesBordin, Tom and Maugey, Thomaspaper
(Arxiv 2024) On the Adversarial Robustness of Learning-based Image Compression Against Rate-Distortion AttacksWu, Chenhao and Wu, Qingbo and Wei, Haoran and Chen, Shuai and Wang, Lei and Ngan, King Ngi and Meng, Fanman and Li, Hongliangpaper
(Arxiv 2024) Scalable Image Coding for Humans and Machines Using Feature Fusion NetworkLi, Junhui and Hou, Xingsongpaper
(Arxiv 2024) Towards Task-Compatible Compressible Representations de Andrade, Anderson and Baji{'c}, Ivanpaper
(Arxiv 2024) Enhancing Perception Quality in Remote Sensing Image Compression via Invertible Neural Network Li, Junhui and Hou, Xingsongpaper
(Arxiv 2024) NLIC: Non-uniform Quantization based Learned Image Compression Ge, Ziqing and Ma, Siwei and Gao, Wen and Pan, Jingshan and Jia, Chuanminpaper
(Arxiv 2024) Domain Adaptation for Learned Image Compression with Supervised AdaptersPresta, Alberto and Spadaro, Gabriele and Tartaglione, Enzo and Fiandrotti, Attilio and Grangetto, Marcopaper
(Arxiv 2024) 2D Gaussian Splatting for Image CompressionPingping Zhang, Xiangrui Liu, Meng Wang, Shiqi Wang, Sam Kwongpaper
(Arxiv 2024) Domain Adaptation for Learned Image Compression with Supervised AdaptersPresta, Alberto and Spadaro, Gabriele and Tartaglione, Enzo and Fiandrotti, Attilio and Grangetto, Marcopaper
(Arxiv 2024) Towards Extreme Image Compression with Latent Feature Guidance and Diffusion PriorLi, Zhiyuan and Zhou, Yanhui and Wei, Hao and Ge, Chenyang and Jiang, Jingwenpaper
(Arxiv 2024) S2LIC: Learned Image Compression with the SwinV2 Block, Adaptive Channel-wise and Global-inter Attention ContextWang, Yongqiang and Liang, Feng and Liang, Jie and Fu, Haishengpaper
(Arxiv 2024) Lossy Image Compression with Foundation Diffusion ModelsWRelic, Lucas and Azevedo, Roberto and Gross, Markus and Schroers, Christopherpaper
(Arxiv 2024) Correcting Diffusion-Based Perceptual Image Compression with Privileged End-to-End DecoderMa, Yiyang and Yang, Wenhan and Liu, Jiayingpaper
(Arxiv 2024) Fine color guidance in diffusion models and its application to image compression at extremely low bitratesBordin, Tom and Maugey, Thomaspaper
(Arxiv 2024) Human-Machine Collaborative Image Compression Method Based on Implicit Neural RepresentationsLi, Huanyang and Zhang, Xinfengpaper
(Arxiv 2024) CGenerative Refinement for Low Bitrate Image Coding Using Vector Quantized ResidualKong, Yuzhuo and Lu, Ming and Ma, Zhanpaper
(Arxiv 2024) Image and Video Compression using Generative Sparse Representation with Fidelity ControlsJiang, Wei and Wang, Weipaper
(Arxiv 2024) Content-aware Masked Image Modeling Transformer for Stereo Image CompressionZhang, Xinjie and Gao, Shenyuan and Liu, Zhening and Ge, Xingtong and He, Dailan and Xu, Tongda and Wang, Yan and Zhang, Junpaper
(Arxiv 2024) Super-High-Fidelity Image Compression via Hierarchical-ROI and Adaptive QuantizationLuo, Jixiang and Wang, Yan and Qin, Hongweipaper
(Arxiv 2024) Theoretical Bound-Guided Hierarchical VAE for Neural Image CodecsZhang, Yichi and Duan, Zhihao and Huang, Yuning and Zhu, Fengqingpaper
(Arxiv 2024) Unifying Generation and Compression: Ultra-low bitrate Image Coding Via Multi-stage TransformerXue, Naifu and Mao, Qi and Wang, Zijian and Zhang, Yuan and Ma, Siweipaper
(Arxiv 2024) Enhancing the Rate-Distortion-Perception Flexibility of Learned Image Codecs with Conditional Diffusion DecodersMari, Daniele and Milani, Simonepaper
(Arxiv 2024) Channel-wise Feature Decorrelation for Enhanced Learned Image CompressionPakdaman, Farhad and Gabbouj, Moncefpaper
(Arxiv 2024) Overfitted image coding at reduced complexityBlard, Th{'e}ophile and Ladune, Th{'e}o and Philippe, Pierrick and Clare, Gordon and Jiang, Xiaoran and D{'e}forges, Olivierpaper
(Arxiv 2024) Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity Lee, Hagyeong and Kim, Minkyu and Kim, Jun-Hyuk and Kim, Seungeon and Oh, Dokwan and Lee, Jaehopaper
(Arxiv 2024) Transformer-based Learned Image Compression for Joint Decoding and Denoising Chen, Yi-Hsin and Ho, Kuan-Wei and Tsai, Shiau-Rung and Lin, Guan-Hsun and Gnutti, Alessandro and Peng, Wen-Hsiao and Leonardi, Riccardopaper
(Arxiv 2024) Channel-wise Feature Decorrelation for Enhanced Learned Image Compression Pakdaman, Farhad and Gabbouj, Moncefpaper
(Arxiv 2024) Super-High-Fidelity Image Compression via Hierarchical-ROI and Adaptive Quantization Luo, Jixiang and Wang, Yan and Qin, Hongweipaper
(Arxiv 2024) S2LIC: Learned Image Compression with the SwinV2 Block, Adaptive Channel-wise and Global-inter Attention Context Wang, Yongqiang and Liang, Feng and Liang, Jie and Fu, Haishengpaper
(Arxiv 2024) Content-aware Masked Image Modeling Transformer for Stereo Image Compression Zhang, Xinjie and Gao, Shenyuan and Liu, Zhening and Ge, Xingtong and He, Dailan and Xu, Tongda and Wang, Yan and Zhang, Junpaper
(Arxiv 2024) Probing Image Compression For Class-Incremental Learning Yang, Justin and Duan, Zhihao and Peng, Andrew and Huang, Yuning and He, Jiangpeng and Zhu, Fengqingpaper
(Arxiv 2024) Variable-Rate Learned Image Compression with Multi-Objective Optimization and Quantization-Reconstruction Offsets Kamisli, Fatih and Racape, Fabien and Choi, Hyomin paper
(Arxiv 2024) Channel-wise Feature Decorrelation for Enhanced Learned Image Compression Pakdaman, Farhad and Gabbouj, Moncef paper
(Arxiv 2024) Exploration of Learned Lifting-Based Transform Structures for Fully Scalable and Accessible Wavelet-Like Image Compression Li, Xinyue and Naman, Aous and Taubman, David paper
(Arxiv 2024) Powerful Lossy Compression for Noisy Images Cai, Shilv and Liang, Xiaoguo and Cao, Shuning and Yan, Luxin and Zhong, Sheng and Chen, Liqun and Zou, Xu paper
(Arxiv 2024) Enhancing Adversarial Training with Prior Knowledge Distillation for Robust Image Compression Zhi, Cao and Youneng, Bao and Fanyang, Meng and Chao, Li and Wen, Tan and Genhong, Wang and Yongsheng, Liang paper
(Arxiv 2024) Image Coding for Machines with Edge Information Learning Using Segment Anything Shindo, Takahiro and Yamada, Kein and Watanabe, Taiju and Watanabe, Hiroshi paper
(Arxiv 2024) Resilience of Entropy Model in Distributed Neural Networks Zhang, Milin and Abdi, Mohammad and Rifat, Shahriar and Restuccia, Francescopaper
(Arxiv 2024) Unifying Generation and Compression: Ultra-low bitrate Image Coding Via Multi-stage Transformer Xue, Naifu and Mao, Qi and Wang, Zijian and Zhang, Yuan and Ma, Siweipaper
(Arxiv 2024) Content-aware Masked Image Modeling Transformer for Stereo Image Compression Zhang, Xinjie and Gao, Shenyuan and Liu, Zhening and Ge, Xingtong and He, Dailan and Xu, Tongda and Wang, Yan and Zhang, Junpaper
(Arxiv 2024) GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splatting Zhang, Xinjie and Ge, Xingtong and Xu, Tongda and He, Dailan and Wang, Yan and Qin, Hongwei and Lu, Guo and Geng, Jing and Zhang, Junpaper
(Arxiv 2024) Wavelet-Like Transform-Based Technology in Response to the Call for Proposals on Neural Network-Based Image Coding Dong, Cunhui and Ma, Haichuan and Zhang, Haotian and Gao, Changsheng and Li, Li and Liu, Dongpaper
(Arxiv 2024) Region-Adaptive Transform with Segmentation Prior for Image Compression Liu, Yuxi and Yang, Wenhan and Bai, Huihui and Wei, Yunchao and Zhao, Yaopaper
(Arxiv 2024) LEARNED IMAGE COMPRESSION WITH TEXT QUALITY ENHANCEMENT Lai, Chih-Yu and Tran, Dung and Koishida, Kazuhitopaper
(Arxiv 2024) Variable-Rate Learned Image Compression with Multi-Objective Optimization and Quantization-Reconstruction Offsets Kamisli, Fatih and Racape, Fabien and Choi, Hyominpaper
(Arxiv 2024) End-to-End Optimized Image Compression with the Frequency-Oriented Transform Zhang, Yuefeng and Lin, Kai paper
(Arxiv 2024) Learned Image Compression with ROI-Weighted Distortion and Bit Allocation Jiang, Wei and Zhai, Yongqi and Li, Hangyu and Wang, Ronggang paper
(Arxiv 2024) Semantic Ensemble Loss and Latent Refinement for High-Fidelity Neural Image Compression Li, Daxin and Bai, Yuanchao and Wang, Kai and Jiang, Junjun and Liu, Xianming paper
(Arxiv 2024) FLLIC: Functionally Lossless Image Compression Zhang, Xi and Wu, Xiaolin paper
(Arxiv 2024) Fast Implicit Neural Representation Image Codec in Resource-limited Devices Liu, Xiang and Chen, Jiahong and Chen, Bin and Liu, Zimo and An, Baoyi and Xia, Shu-Tao paper
(NeurPIS 2024) Robustly overfitting latents for flexible neural image compression Perugachi-Diaz, Yura and Gansekoele, Arwin and Bhulai, Sandjai paper
(Arxiv 2024) Saliency-aware End-to-end Learned Variable-Bitrate 360-degree Image Compression Gungordu, Oguzhan and Tekalp, A Murat paper
(Arxiv 2024) Joint End-to-End Image Compression and Denoising: Leveraging Contrastive Learning and Multi-Scale Self-ONNs Xie, Yuxin and Yu, Li and Pakdaman, Farhad and Gabbouj, Moncefpaper
(Arxiv 2024) LEARNED COMPRESSION OF ENCODING DISTRIBUTIONS Ulhaq, Mateen and Bajic, Ivan Vpaper
(Arxiv 2024) Transformer-based Learned Image Compression for Joint Decoding and Denoising Chen, Yi-Hsin and Ho, Kuan-Wei and Tsai, Shiau-Rung and Lin, Guan-Hsun and Gnutti, Alessandro and Peng, Wen-Hsiao and Leonardi, Riccardopaper
(VICP 2024) Flexible Coding Order for Learned Image Compression Li, Yuqi and Zhang, Haotian and Liu, Dong paper
(VICP 2024) Variable-rate Learned Image Compression with Adaptive Quantization Step Size Mei, Feihong and Li, Li and Liu, Dong paper
(VICP 2024) Learned Progressive Image Compression With Spatial Autoregression Li, Hangyu and Jiang, Wei and Li, Litian and Zhai, Yongqi and Wang, Ronggang paper
(VICP 2024) Hybrid Implicit Neural Image Compression with Subpixel Context Model and Iterative Pruner Tian, Wenxin and Li, Shaohui and Dai, Wenrui and Lu, Cewu and Hu, Weisheng and Zhang, Lin and Du, Junfeng and Xiong, Hongkai paper
(VICP 2024) Learned Progressive Image Compression With Spatial Autoregression Tian, Wenxin and Li, Shaohui and Dai, Wenrui and Lu, Cewu and Hu, Weisheng and Zhang, Lin and Du, Junfeng and Xiong, Hongkai paper

✔2023

(NeurIPS 2023) Towards efficient image compression without autoregressive models Ali, Muhammad Salman and Kim, Yeongwoong and Qamar, Maryam and Lim, Sung-Chang and Kim, Donghyun and Zhang, Chaoning and Bae, Sung-Ho and Kim, Hui Yong paper
(NeurIPS 2023) LUT-LIC: Look-Up Table-Assisted Learned Image Compression Yu, SeungEun and Lee, Jong-Seokpaper
(ACMMM 2023) Toward Scalable Image Feature Compression: A Content-Adaptive and Diffusion-Based Approach Guo, Sha and Chen, Zhuo and Zhao, Yang and Zhang, Ning and Li, Xiaotong and Duan, Lingyu paper
(ACMMM 2023) Nif: A fast implicit image compression with bottleneck layers and modulated sinusoidal activations Catania, Lorenzo and Allegra, Dario paper
(ACMMM 2023) Lambda-Domain Rate Control for Neural Image Compression Xue, Naifu and Zhang, Yuan paper
(ACMMM 2023) MLIC: Multi-Reference Entropy Model for Learned Image Compression Jiang, Wei and Yang, Jiayu and Zhai, Yongqi and Ning, Peirong and Gao, Feng and Wang, Ronggang paper
(ACMMM 2023) ELFIC: A Learning-based Flexible Image Codec with Rate-Distortion-Complexity Optimization Zhang, Zhichen and Chen, Bolin and Lin, Hongbin and Lin, Jielian and Wang, Xu and Zhao, Tiesong paper
(ACMMM 2023) ICMH-Net: Neural Image Compression Towards both Machine Vision and Human Vision Liu, Lei and Hu, Zhihao and Chen, Zhenghao and Xu, Dong paper
(TIP 2023) Learned Image Compression Using Cross-Component Attention Mechanism Duan, Wenhong and Chang, Zheng and Jia, Chuanmin and Wang, Shanshe and Ma, Siwei and Song, Li and Gao, Wen paper
(TIP 2023) Scalable Face Image Coding via StyleGAN Prior: Towards Compression for Human-Machine Collaborative Vision Mao, Qi and Wang, Chongyu and Wang, Meng and Wang, Shiqi and Chen, Ruijie and Jin, Libiao and Ma, Siwei paper
(CVPR 2023) Dec-Adapter: Exploring Efficient Decoder-Side Adapter for Bridging Screen Content and Natural Image Compression Shen, Sheng and Yue, Huanjing and Yang, Jingyu paper
(CVPR 2023) Context-Based Trit-Plane Coding for Progressive Image Compression Jeon, Seungmin and Choi, Kwang Pyo and Park, Youngo and Kim, Chang-Su paper
(CVPR 2023) Transtic: Transferring transformer-based image compression from human perception to machine perception Chen, Yi-Hsin and Weng, Ying-Chieh and Kao, Chia-Hao and Chien, Cheng and Chiu, Wei-Chen and Peng, Wen-Hsiao paper
(TAI 2023) Manipulation Attacks on Learned Image Compression Liu, Kang and Wu, Di and Wu, Yangyu and Wang, Yiru and Feng, Dan and Tan, Benjamin and Garg, Siddharthpaper
(ICIP 2023) A Decoupled Spatial-Channel Inverted Bottleneck For Image Compression Hu, Yuting and Tan, Wen and Meng, Fanyang and Liang, Yongshengpaper
(ICIP 2023) NUCQ: Non-Uniform Conditional Quantization for Learned Image Compression Ge, Ziqing and Jia, Chuanmin and Ma, Siwei and Gao, Wepaper
(ICIP 2023) End-to-End Learning-based Image Compression with A Decoupled Framework Zhang, Zhaobin and Esenlik, Semih and Wu, Yaojun and Wang, Meng and Zhang, Kai and Zhang, Lipaper
(ICIP 2023) Advancing the Rate-Distortion-Computation Frontier for Neural Image Compression Minnen, David and Johnston, Nickpaper
(ICIP 2023) Efficient Pruning Method for Learned Lossy Image Compression Models Based on Side Information LChen, Weixuan and Yang, Qianqianpaper
(ICIP 2023) Content-Adaptive Parallel Entropy Coding for End-to-End Image Compression Li, Shujia and Wang, Dezhao and Fan, Zejia and Liu, Jiayingpaper
(ICIP 2023) Edge-Guided Remote-Sensing Image Compression Han, Pengfei and Zhao, Bin and Li, Xuelong paper
(ICIP 2023) Learned Image Compression Guided Adaptive Quantization for Perceptual Quality Chen, Cheng and Geng, Ruiqi and Li, Bohan and Ustarroz-Calonge, Maryla and Galligan, Frank and Han, Jingning and Xu, Yaowu paper
(ICIP 2023) Unified Learning-Based Lossy and Lossless Jpeg Recompression J. Zhang et al. paper
(ICIP 2023) ULcompress: A Unified low bit-rate image Compression Framework via Invertible Image Representation F. Gao, X. Deng, C. Gao and M. Xu paper
(ICIP 2023) Learned Image Compression with Multi-Scan Based Channel Fusion Y. Li, W. Zhou, P. Lu and S. -i. Kamata, paper
(ICIP 2023) Integer Quantized Learned Image Compression G. -W. Jeon, S. Yu and J. -S. Lee paper
(ICIP 2023) A Decoupled Spatial-Channel Inverted Bottleneck For Image Compression Hu, Yuting and Tan, Wen and Meng, Fanyang and Liang, Yongsheng paper
(ICIP 2023) Learned Image Compression with Large Capacity and Low Redundancy of Latent Representation Meng, Xiandong and Zhu, Shuyuan and Ma, Siwei and Zeng, Bing paper
(ICIP 2023) An Improved Upper Bound on the Rate-Distortion Function of Images Duan, Zhihao and Ma, Jack and He, Jiangpeng and Zhu, Fengqingpaper
(ICIP 2023) AICT: An Adaptive Image Compression Transformer Ghorbel, Ahmed and Hamidouche, Wassim and Morin, Lucepaper
(WACV 2023) Neural Distributed Image Compression with Cross-Attention Feature Alignment Mital, Nitish and {"O}zyilkan, Ezgi and Garjani, Ali and G{"u}nd{"u}z, Denizpaper
(VCIP 2023) Image Data Hiding in Neural Compressed Latent Representations Huang, Chen-Hsiu and Wu, Ja-Lingpaper
(VICP 2023) EVC: TOWARDS REAL-TIME NEURAL IMAGE COMPRESSION WITH MASK DECA Wang, Guo-Hua and Li, Jiahao and Li, Bin and Lu, Yan paper
(VICP 2023) A Near Lossless Learned Image Coding Network Quantization Approach for Cross-Platform Inference Hang, Xinyu and Jia, Chuanmin and Ma, Siwei and Gao, Wen paper
(ICASSP 2023) A Novel Cross-Component Context Model for End-to-End Wavelet Image Coding Meyer, Anna and Kaup, Andr{'e} paper
(TCSVT 2024) Lightweight Context Model Equipped aiWave in Response to the AVS Call for Evidence on Volumetric Medical Image Coding Xue, Dongmei and Li, Li and Liu, Dong and Li, Houqiang paper
(TCSVT 2023) MASIC: Deep Mask Stereo Image Compression Deng, Xin and Deng, Yufan and Yang, Ren and Yang, Wenzhe and Timofte, Radu and Xu, Mai paper
(TCSVT 2023) Extremely Low Bit-rate Image Compression via Invertible Image Generation Gao, Fangyuan and Deng, Xin and Jing, Junpeng and Zou, Xin and Xu, Mai paper
(TCSVT 2023) Task-Switchable Pre-Processor for Image Compression for Multiple Machine Vision Tasks Yang, Mingyi and Yang, Fei and Murn, Luka and Blanch, Marc Gorriz and Sock, Juil and Wan, Shuai and Yang, Fuzheng and Herranz, Luis paper
(TCSVT 2023) Rethinking semantic image compression: Scalable representation with cross-modality transfer Zhang, Pingping and Wang, Shiqi and Wang, Meng and Li, Jiguo and Wang, Xu and Kwong, Sam paper
(TCSVT 2023) Facial Image Compression via Neural Image Manifold Compression Yang, Wenhan and Huang, Haofeng and Liu, Jiaying and Kot, Alex C. paper
(TCSVT 2023) Sketch Assisted Face Image Coding for Human and Machine Vision: a Joint Training Approach. Fang, Xin and Duan, Yiping and Du, Qiyuan and Tao, Xiaoming and Li, Fan paper
(ICCV 2023) COMPASS: High-Efficiency Deep Image Compression with Arbitrary-scale Spatial Scalability Park, Jongmin and Lee, Jooyoung and Kim, Munchurl paper
(ICCV 2023) AdaNIC: Towards Practical Neural Image Compression via Dynamic Transform Routing Tao, Lvfang and Gao, Wei and Li, Ge and Zhang, Chenhao paper
(WCACV 2023) Controlling Rate, Distortion, and Realism: Towards a Single Comprehensive Neural Image Compression Model Iwai, Shoma and Miyazaki, Tomo and Omachi, Shinichiro paper
(Arxiv 2023) EGIC: Enhanced Low-Bit-Rate Generative Image Compression Guided by Semantic Segmentation K{"o}rber, Nikolai and Kromer, Eduard and Siebert, Andreas and Hauke, Sascha and Mueller-Gritschneder, Daniel paper
(Arxiv 2023) A Training-Free Defense Framework for Robust Learned Image Compression Song, Myungseo and Choi, Jinyoung and Han, Bohyung paper
(Arxiv 2023) FFCA-Net: Stereo Image Compression via Fast Cascade Alignment of Side InformationXia, Yichong and Huang, Yujun and Chen, Bin and Wang, Haoqian and Wang, Yaoweipaper
(Arxiv 2023) Another Way to the Top: Exploit Contextual Clustering in Learned Image CodingZhang, Yichi and Duan, Zhihao and Lu, Ming and Ding, Dandan and Zhu, Fengqing and Ma, Zhanpaper
(Arxiv 2023) Attack and Defense Analysis of Learned Image CompressionZhu, Tianyu and Sun, Heming and Xiong, Xiankui and Zhu, Xuanpeng and Gong, Yong and Fan, Yibo and otherspaper
(Arxiv 2023) Fast and High-Performance Learned Image Compression With Improved Checkerboard Context Model, Deformable Residual Module, and Knowledge Distillation Fu, Haisheng and Liang, Feng and Liang, Jie and Wang, Yongqiang and Zhang, Guohe and Han, Jingning paper
(Arxiv 2023) Multi-Context Dual Hyper-Prior Neural Image Compression Khoshkhahtinat, Atefeh and Zafari, Ali and Mehta, Piyush M and Akyash, Mohammad and Kashiani, Hossein and Nasrabadi, Nasser M paper
(Arxiv 2023) On Uniform Scalar Quantization for Learned Image Compression Zhang, Haotian and Li, Li and Liu, Dongpaper
(Arxiv 2023) Frequency-Aware Transformer for Learned Image Compression Li, Han and Li, Shaohui and Dai, Wenrui and Li, Chenglin and Zou, Junni and Xiong, Hongkaipaper
(Arxiv 2023) Perceptual Image Compression with Cooperative Cross-Modal Side Information Qin, Shiyu and Chen, Bin and Huang, Yujun and An, Baoyi and Dai, Tao and Via, Shu-Taopaper
(Arxiv 2023) Progressive Learning with Visual Prompt Tuning for Variable-Rate Image Compression Qin, Shiyu and Zhou, Yimin and Wang, Jinpeng and Chen, Bin and An, Baoyi and Dai, Tao and Xia, Shu-Taopaper
(Arxiv 2023) Exploring the Rate-Distortion-Complexity Optimization in Neural Image Compression Gao, Yixin and Feng, Runsen and Guo, Zongyu and Chen, Zhibopaper
(JVCIR 2023) Corner-to-Center long-range context model for efficient learned image compression LSui, Yang and Ding, Ding and Pan, Xiang and Xu, Xiaozhong and Liu, Shan and Yuan, Bo and Chen, Zhenzhongpaper
(VICP 2023) A Near Lossless Learned Image Coding Network Quantization Approach for Cross-Platform Inference Hang, Xinyu and Jia, Chuanmin and Ma, Siwei and Gao, Wen paper
(TMI 2023) A Near Lossless Learned Image Coding Network Quantization Approach for Cross-Platform Inference Hang, Xinyu and Jia, Chuanmin and Ma, Siwei and Gao, Wen paper

✔2022

(PCS 2022) Reducing The Amortization Gap of Entropy Bottleneck In End-to-End Image Compression Balcilar, Muhammet and Damodaran, Bharath and Hellier, Pierre paper e
(CVPR workshop 2022) Self-Supervised Variable Rate Image Compression using Visual Attention Sinha, Abhishek Kumar and Moorthi, S Manthira and Dhar, Debajyotipaper
(CVPR workshop 2022) RDONet: Rate-Distortion Optimized Learned Image Compression with Variable Depth Brand, Fabian and Fischer, Kristian and Kopte, Alexander and Windsheimer, Marc and Kaup, Andr{'e} paper
(Arxiv 2022) Transformations in Learned Image Compression from Modulation Perspective Bao, Youneng and Meng, Fangyang and Tan, Wen and Li, Chao and Tian, Yonghong and Liang, Yongsheng paper
(Arxiv 2022) Flexible Neural Image Compression via Code Editing Gao, Chenjian and Xu, Tongda and He, Dailan and Qin, Hongwei and Wang, Yan paper
(Arxiv 2022) Attention-Based Generative Neural Image Compression on Solar Dynamics Observatory Zafari, Ali and Khoshkhahtinat, Atefeh and Mehta, Piyush M and Nasrabadi, Nasser M and Thompson, Barbara J and da Silva, Daniel and Kirk, Michael SFpaper
(Arxiv 2022) Progressive Deep Image Compression for Hybrid Contexts of Image Classification and Reconstruction Lei, Zhongyue and Duan, Peng and Hong, Xuemin and Mota, Jo{~a}o FC and Shi, Jianghong and Wang, Cheng-Xiang paper
(CVPRW 2022) Universal Deep Image Compression via Content-Adaptive Optimization with Adapters Tsubota, Koki and Akutsu, Hiroaki and Aizawa, Kiyoharu paper
(CVPRW 2022) User-Guided Variable Rate Learned Image Compression Gupta, Rushil and BV, Suryateja and Kapoor, Nikhil and Jaiswal, Rajat and Nangi, Sharmila Reddy and Kulkarni, Kuldeeppaper
(CVPRW 2022) Adaptive Bitrate Quantization Scheme Without Codebook for Learned Image Compression L{"o}hdefink, Jonas and Sitzmann, Jonas and B{"a}r, Andreas and Fingscheidt, Tim paper
(TIP 2022) OSLO: On-the-Sphere Learning for Omnidirectional images and its application to 360-degree image compression Bidgoli, Navid Mahmoudian and Roberto, G de A and Maugey, Thomas and Roumy, Aline and Frossard, Pascal paper
(AAAI 2022) Two-Stage Octave Residual Network for End-to-End Image Compression Chen, Fangdong and Xu, Yumeng and Wang, Li paper
(Arxiv 2022) Preprocessing Enhanced Image Compression for Machine Vision Lu, Guo and Ge, Xingtong and Zhong, Tianxiong and Geng, Jing and Hu, Qiang paper
(Arxiv 2022) Learning-Driven Lossy Image Compression; A Comprehensive Survey Jamil, Sonain and Piran, Md and others paper
(Arxiv 2022) Estimating the Resize Parameter in End-to-end Learned Image Compression Chen, Li-Heng and Bampis, Christos G and Li, Zhi and Krasula, Luk{'a}{\v{s}} and Bovik, Alan C paper
(Arxiv 2022) Image Compression with Product Quantized Masked Image Modeling El-Nouby, Alaaeldin and Muckley, Matthew J and Ullrich, Karen and Laptev, Ivan and Verbeek, Jakob and J{'e}gou, Herv{'e} paper
(ITJ 2022) Human–Machine Interaction-Oriented Image Coding for Res8ource-Constrained Visual Monitoring in IoT Wang, Zixi and Li, Fan and Xu, Jing and Cosman, Pamela C paper
(TGRS 2022) Towards simultaneous image compression and indexing for scalable content-based retrieval in remote sensing Sumbul, Gencer and Xiang, Jun and Demir, Beg{"u}m paper
(SPI 2022) Rate-constrained learning-based image compression paper
(TIP 2022) Exploiting Intra-Slice and Inter-Slice Redundancy for Learning-Based Lossless Volumetric Image Compression Chen, Zhenghao and Gu, Shuhang and Lu, Guo and Xu, Dong paper lossless
(Arxiv 2022) Entroformer: A transformer-based entropy model for learned image compression Qian, Yichen and Lin, Ming and Sun, Xiuyu and Tan, Zhiyu and Jin, Rong paper
(Arxiv 2022) Multi-Sample Training for Neural Image Compression Xu, Tongda and Wang, Yan and He, Dailan and Gao, Chenjian and Gao, Han and Liu, Kunzan and Qin, Hongwei paper
(CVPR 2022) ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding He, Dailan and Yang, Ziming and Peng, Weikun and Ma, Rui and Qin, Hongwei and Wang, Yan paper
(ECCV 2022) Contextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compression Koyuncu, A Burakhan and Gao, Han and Boev, Atanas and Gaikov, Georgii and Alshina, Elena and Steinbach, Eckehard paper
(ECCV 2022) Contextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compression Koyuncu, A Burakhan and Gao, Han and Boev, Atanas and Gaikov, Georgii and Alshina, Elena and Steinbach, Eckehard paper
(ECCV 2022) Content-Oriented Learned Image Compression Li, Meng and Gao, Shangyin and Feng, Yihui and Shi, Yibo and Wang, Jing paper
(ECCV 2022) Implicit Neural Representations for Image Compression Str{"u}mpler, Yannick and Postels, Janis and Yang, Ren and Gool, Luc Van and Tombari, Federico paper
(ECCV 2022) Content Adaptive Latents and Decoder for Neural Image Compression Pan, Guanbo and Lu, Guo and Hu, Zhihao and Xu, Dong paper
(ECCV 2022) Optimizing Image Compression via Joint Learning with Denoising Cheng, Ka Leong and Xie, Yueqi and Chen, Qifeng paper denoising
(2022) 2C-Net: Integrate Image Compression and Classification via Deep Neural Network Liu, Linfeng and Chen, Tong and Liu, Haojie and Pu, Shiliang and Wang, Li and Shen, Qiu paper
(ACMMM 2022) High-Fidelity Variable-Rate Image Compression via Invertible Activation Transformation Cai, Shilv and Zhang, Zhijun and Chen, Liqun and Yan, Luxin and Zhong, Sheng and Zou, Xu [paper]
(arxiv 2022) Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compression Bai, Yuanchao and Liu, Xianming and Wang, Kai and Ji, Xiangyang and Wu, Xiaolin and Gao, Wen [paper]
(TCSVT 2022) End-to-End Optimized Image Compression With Deep Gaussian Process Regression Cao, Maida and Dai, Wenrui and Li, Shaohui and Li, Chenglin and Zou, Junni and Chen, Ying and Xiong, Hongkai [paper]
(TIP 2022) End-to-end optimized 360° image compression Li, Mu and Li, Jinxing and Gu, Shuhang and Wu, Feng and Zhang, David [paper]
(arxiv 2022) Lossy Compression with Gaussian Diffusion Theis, Lucas and Salimans, Tim and Hoffman, Matthew D and Mentzer, Fabian [paper]
(arxiv 2022) Joint Image Compression and Denoising via Latent-Space Scalability Alvar, Saeed Ranjbar and Ulhaq, Mateen and Choi, Hyomin and Baji{'c}, Ivan V [paper]
(arxiv 2022) Post-Training Quantization for Cross-Platform Learned Image Compression He, Dailan and Yang, Ziming and Chen, Yuan and Zhang, Qi and Qin, Hongwei and Wang, Yan [paper]
(ICASSP 2022) Satellite Image Compression and Denoising With Neural Networks Yin, Shanzhi and Li, Chao and Bao, Youneng and Liang, Yongsheng and Meng, Fanyang and Liu, Wei [paper]
(ICASSP 2022) AdderIC: Towards Low Computation Cost Image Compression Li, Bowen and Xin, Yao and Li, Chao and Bao, Youneng and Meng, Fanyang and Liang, Yongsheng [paper]
(IEEE Geoscience and Remote Sensing Letters 2022) Universal Efficient Variable-Rate Neural Image Compression de Oliveira, Vinicius Alves and Chabert, Marie and Oberlin, Thomas and Poulliat, Charly and Bruno, Mickael and Latry, Christophe and Carlavan, Mikael and Henrot, Simon and Falzon, Frederic and Camarero, Roberto [paper]
(CVPR 2022) The Devil Is in the Details: Window-Based Attention for Image Compression Zou, Renjie and Song, Chunfeng and Zhang, Zhaoxiang paper
(CVPR 2022) Joint Global and Local Hierarchical Priors for Learned Image Compression, Kim, Jun-Hyuk and Heo, Byeongho and Lee, Jong-Seok [paper] (E)
(CVPR 2022) RIDDLE: Lidar Data Compression with Range Image Deep Delta Encoding Zhou, Xuanyu and Qi, Charles R and Zhou, Yin and Anguelov, Dragomir [paper]
(CVPR 2022) Neural Data-Dependent Transform for Learned Image Compression Wang, Dezhao and Yang, Wenhan and Hu, Yueyu and Liu, Jiaying [paper]
(CVPRW 2022) Self-Supervised Variable Rate Image Compression using Visual Attention Sinha, Abhishek Kumar and Moorthi, S Manthira and Dhar, Debajyoti [paper]
(CVPRW 2022) User-Guided Variable Rate Learned Image Compression Gupta, Rushil and BV, Suryateja and Kapoor, Nikhil and Jaiswal, Rajat and Nangi, Sharmila Reddy and Kulkarni, Kuldeep [paper]
(CVPR 2022) RDONet: Rate-Distortion Optimized Learned Image Compression With Variable Depth Brand, Fabian and Fischer, Kristian and Kopte, Alexander and Windsheimer, Marc and Kaup, Andr{'e}. [paper]
(CVPR 2022) LC-FDNet: Learned Lossless Image Compression with Frequency Decomposition Network Rhee, Hochang and Jang, Yeong Il and Kim, Seyun and Cho, Nam Ik. [paper]
(CVPR 2022) PO-ELIC: Perception-Oriented Efficient Learned Image Coding He, Dailan and Yang, Ziming and Yu, Hongjiu and Xu, Tongda and Luo, Jixiang and Chen, Yuan and Gao, Chenjian and Shi, Xinjie and Qin, Hongwei and Wang, Yan. [paper]
(CVPR 2022) Online Meta Adaptation for Variable-Rate Learned Image Compression Jiang, Wei and Wang, Wei and Li, Songnan and Liu, Shan. [paper]
(CVPR 2022) Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression Zhu, Xiaosu and Song, Jingkuan and Gao, Lianli and Zheng, Feng and Shen, Heng Tao. [paper]
(CVPR 2022) Split Hierarchical Variational Compression Ryder, Tom and Zhang, Chen and Kang, Ning and Zhang, Shifeng. [paper]
(CVPR 2022) SASIC: Stereo Image Compression With Latent Shifts and Stereo Attention W{"o}dlinger, Matthias and Kotera, Jan and Xu, Jan and Sablatnig, Robert. [paper]
(CVPR 2022) Deep Stereo Image Compression via Bi-directional Coding, Lei, Jianjun and Liu, Xiangrui and Peng, Bo and Jin, Dengchao and Li, Wanqing and Gu, Jingxiao [paper]
(AAAI 2022) OoDHDR-Codec: Out-of-Distribution Generalization for HDR Image Compression, Cao, Linfeng and Jiang, Aofan and Li, Wei and Wu, Huaying and Ye, Nanyang [paper] (HDR)
(arXiv preprint 2022) Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression, Zhu, Xiaosu and Song, Jingkuan and Gao, Lianli and Zheng, Feng and Shen, Heng Tao [paper][code] (E)
(arXiv preprint 2022) Estimating the Resize Parameter in End-to-end Learned Image Compression, Chen, Li-Heng and Bampis, Christos G and Li, Zhi and Krasula, Luk{'a}{\v{s}} and Bovik, Alan C [paper][code] (Sa)
(arXiv preprint 2022) DeepFGS: Fine-Grained Scalable Coding for Learned Image Compression, Ma, Yi and Zhai, Yongqi and Wang, Ronggang [paper](Sa)
(arXiv preprint 2022) End-to-End Learned Block-Based Image Compression with Block-Level Masked Convolutions and Asymptotic Closed Loop Training, Kamisli, Fatih [paper] (T+E)
(arXiv preprint 2022) Transformations in Learned Image Compression from Modulation Perspective, Bao, Youneng and Meng, Fangyang and Tan, Wen and Li, Chao and Tian, Yonghong and Liang, Yongsheng [paper]
(arXiv preprint 2022) Identity Preserving Loss for Learned Image Compression, Xiao, Jiuhong and Aggarwal, Lavisha and Banerjee, Prithviraj and Aggarwal, Manoj and Medioni, Gerard [paper]
(arXiv preprint 2022) High-Efficiency Lossy Image Coding Through Adaptive Neighborhood Information Aggregation, Lu, Ming and Ma, Zhan [paper] (E)
(arXiv preprint 2022) Learning Weighting Map for Bit-Depth Expansion within a Rational Range, Liu, Yuqing and Jia, Qi and Zhang, Jian and Fan, Xin and Wang, Shanshe and Ma, Siwei and Gao, Wen [paper] [code]
(arXiv preprint 2022) Joint Image Compression and Denoising via Latent-Space Scalability, Ranjbar Alvar, Saeed and Ulhaq, Mateen and Choi, Hyomin and Baji{'c}, Ivan V [paper]

✔2021

(TPAMI 2021) Learning end-to-end lossy image compression: A benchmark, Hu, Yueyu and Yang, Wenhan and Ma, Zhan and Liu, Jiaying [paper] [code](Benchmark)
(IJCV 2021) Semantics-to-signal scalable image compression with learned revertible representations, Liu, Kang and Liu, Dong and Li, Li and Yan, Ning and Li, Houqiang [paper][code] (Scalable)
(TIP 2021) Semantic Perceptual Image Compression With a Laplacian Pyramid of Convolutional Networks, Wang, Juan and Duan, Yiping and Tao, Xiaoming and Xu, Mai and Lu, Jianhua [paper]
(ICLR 2021) Hierarchical Image Compression Framework, Ge, Yunying and Wang, Jing and Shi, Yibo and Gao, Shangyin [paper]
(ICCV 2021) Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform, Song, Myungseo and Choi, Jinyoung and Han, Bohyung [paper] (E)
(CVPR 2021) Asymmetric Gained Deep Image Compression With Continuous Rate Adaptation, Cui, Ze and Wang, Jing and Gao, Shangyin and Guo, Tiansheng and Feng, Yihui and Bai, Bo [paper] [code](VR)
(CVPR 2021) Checkerboard context model for efficient learned image compression, He, Dailan and Zheng, Yaoyan and Sun, Baocheng and Wang, Yan and Qin, Hongwei [paper] [code1] [code] (E)
(CVPR 2021) Learning scalable ly=-constrained near-lossless image compression via joint lossy image and residual compression, Bai, Yuanchao and Liu, Xianming and Zuo, Wangmeng and Wang, Yaowei and Ji, Xiangyang [paper] [code](lossless)
(CVPRW 2021) End-to-end optimized image compression with competition of prior distributions, Brummer, Benoit and De Vleeschouwer, Christophe [paper] [code](E)
(CVPRW 2021) Subjective Quality Optimized Efficient Image Compression, Wang, Xining and Chen, Tong and Ma, Zhan [paper] [code](perceptual)
(CVPRW 2021) Variable Rate ROI Image Compression Optimized for Visual Quality, Ma, Yi and Zhai, Yongqi and Yang, Chunhui and Yang, Jiayu and Wang, Ruofan and Zhou, Jing and Li, Kai and Chen, Ying and Wang, Ronggang [paper](VR)
(CVPRW 2021) Image Compression with Recurrent Neural Network and Generalized Divisive Normalization, Islam, Khawar and Dang, L Minh and Lee, Sujin and Moon, Hyeonjoon [paper][code]
(CVPRW 2021) End-to-End Learned Image Compression with Augmented Normalizing Flows, Ho, Yung-Han and Chan, Chih-Chun and Peng, Wen-Hsiao and Hang, Hsueh-Ming [paper][code]
(CVPRW 2021) Learned Image Compression with Super-Resolution Residual Modules and DISTS Optimization, Suzuki, Akifumi and Akutsu, Hiroaki and Naruko, Takahiro and Tsubota, Koki and Aizawa, Kiyoharu [paper] (Perceptual)
(CVPRW 2021) Perceptual Friendly Variable Rate Image Compression, Gao, Yixin and Wu, Yaojun and Guo, Zongyu and Zhang, Zhizheng and Chen, Zhibo [paper] (VR+Perceptual)
(WACV 2021) Saliency Driven Perceptual Image Compression, Patel, Yash and Appalaraju, Srikar and Manmatha, R [paper] (perceputal)
(TCSVT 2021) Causal contextual prediction for learned image compression, Guo, Zongyu and Zhang, Zhizheng and Feng, Runsen and Chen, Zhibo [paper] (E)
(TCSVT 2021) Learned Block-based Hybrid Image Compression, Wu, Yaojun and Li, Xin and Zhang, Zhizheng and Jin, Xin and Chen, Zhibo [paper] (T+E)
(ACMMM 2021) Enhanced Invertible Encoding for Learned Image Compression, Yueqi Xie, Ka Leong Cheng, Qifeng Chen [paper] [code] (Invertible)
(ACMMM 2021) Semantic Scalable Image Compression with Cross-Layer Priors, Tu, Hanyue and Li, Li and Zhou, Wengang and Li, Houqiang [paper] (Scalable)
(ACMMM 2021) Interpolation Variable Rate Image Compression, Sun, Zhenhong and Tan, Zhiyu and Sun, Xiuyu and Zhang, Fangyi and Qian, Yichen and Li, Dongyang and Li, Hao [paper] (VR)
(TMM 2021) Learned Multi-Resolution Variable-Rate Image Compression With Octave-Based Residual Blocks, Akbari, Mohammad and Liang, Jie and Han, Jingning and Tu, Chengjie [paper] (VR)
(DCC 2021) Accelerate Neural Image Compression with Channel-adaptive Arithmetic Coding, uo, Zongyu and Fu, Jun and Feng, Runsen and Chen, Zhibo [paper]
(ICIP 2021) Graph-Convolution Network for Image Compression, Yang, Chunhui and Ma, Yi and Yang, Jiayu and Liu, Shiyi and Wang, Ronggang [paper]
(PMLR 2021) Soft then hard: Rethinking the quantization in neural image compression, Z Guo，Z Zhang，R Feng，Z Chen [paper]
(arXiv preprint 2021) Learned Image Compression for Machine Perception, Codevilla, Felipe and Simard, Jean Gabriel and Goroshin, Ross and Pal, Chris [paper] (Perceptual)
(arXiv preprint 2021) Substitutional Neural Image Compression, Wang, Xiao and Jiang, Wei and Wang, Wei and Liu, Shan and Kulis, Brian and Chin, Peter [paper] (VR)
(arXiv preprint 2021) DPICT: Deep Progressive Image Compression Using Trit-Planes, Lee, Jae-Han and Jeon, Seungmin and Choi, Kwang Pyo and Park, Youngo and Kim, Chang-Su [paper] (VR)
(arXiv preprint 2021) Implicit Neural Representations for Image Compression, Str{"u}mpler, Yannick and Postels, Janis and Yang, Ren and Van Gool, Luc and Tombari, Federico [paper]
(arXiv preprint 2021) A Novel Framework for Image-to-image Translation and Image Compression, Yang, Fei and Wang, Yaxing and Herranz, Luis and Cheng, Yongmei and Mozerov, Mikhail [paper] (I2I)
(arXiv preprint 2021) Semantic-assisted image compression, Sun, Qizheng and Guo, Caili and Yang, Yang and Chen, Jiujiu and Xue, Xijun [paper]
(arXiv preprint 2021) End-to-End Learned Image Compression with Quantized Weights and Activations, Sun, Heming and Yu, Lu and Katto, Jiro [paper]
(arXiv preprint 2021) End-to-End Image Compression with Probabilistic Decoding, Ma, Haichuan and Liu, Dong and Dong, Cunhui and Li, Li and Wu, Feng [paper]
(arXiv preprint 2021) Towards End-to-End Image Compression and Analysis with Transformers, Bai, Yuanchao and Yang, Xu and Liu, Xianming and Jiang, Junjun and Wang, Yaowei and Ji, Xiangyang and Gao, Wen [paper]
(arXiv preprint 2021) A Cross Channel Context Model for Latents in Deep Image Compression, Ma, Changyue and Wang, Zhao and Liao, Ruling and Ye, Yan [paper]
(arXiv preprint 2021) Online Meta Adaptation for Variable-Rate Learned Image Compression, Wei Jiang, Wei Wang, Songnan Li, Shan Liu [paper] (VR)
(arXiv preprint 2021) Transformer-based Image Compression, Ming Lu, Peiyao Guo, Huiqing Shi, Chuntong Cao, Zhan Ma [paper]

✔2020

[arXiv preprint 2020] Lossless Image Compression through Super-Resolution, Sheng Cao, Chao-Yuan Wu, Philipp Krähenbühl [paper]

✔2019

(PCS 19) A novel deep progressive image compression framework, Cai, Chunlei and Chen, Li and Zhang, Xiaoyun and Lu, Guo and Gao, Zhiyong. [paper]
(CVPR 19) Learning image and video compression through spatial-temporal energy compaction, Cheng, Zhengxue and Sun, Heming and Takeuchi, Masaru and Katto, Jiro. [paper]

✔2018

Awesome LLM Apps

Tue, 10 Feb 2026 18:34:25 -0800

🌟 Awesome LLM Apps

Introduction

A curated collection of Awesome LLM apps built with RAG, AI Agents, Multi-agent Teams, MCP, Voice Agents, and more. This repository features LLM apps that use models from OpenAI , Anthropic, Google, xAI and open-source models like Qwen or Llama that you can run locally on your computer.

GitHub-Awesome LLM Apps

Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models.

🤔 Why Awesome LLM Apps?

💡 Discover practical and creative ways LLMs can be applied across different domains, from code repositories to email inboxes and more.
🔥 Explore apps that combine LLMs from OpenAI, Anthropic, Gemini, and open-source alternatives with AI Agents, Agent Teams, MCP & RAG.
🎓 Learn from well-documented projects and contribute to the growing open-source ecosystem of LLM-powered applications.

📂 Featured AI Projects

AI Agents

🌱 Starter AI Agents

🚀 Advanced AI Agents

🎮 Autonomous Game Playing Agents

🤝 Multi-agent Teams

🗣️ Voice AI Agents

MCP AI Agents

📀 RAG (Retrieval Augmented Generation)

💾 LLM Apps with Memory Tutorials

💬 Chat with X Tutorials

🎯 LLM Optimization Tools

🎯 Toonify Token Optimization - Reduce LLM API costs by 30-60% using TOON format
🧠 Headroom Context Optimization - Reduce LLM API costs by 50-90% through intelligent context compression for AI agents (includes persistent memory & MCP support)

🔧 LLM Fine-tuning Tutorials

🧑‍🏫 AI Agent Framework Crash Course

Google ADK Crash Course

Starter agent; model‑agnostic (OpenAI, Claude)
Structured outputs (Pydantic)
Tools: built‑in, function, third‑party, MCP tools
Memory; callbacks; Plugins
Simple multi‑agent; Multi‑agent patterns

OpenAI Agents SDK Crash Course

Starter agent; function calling; structured outputs
Tools: built‑in, function, third‑party integrations
Memory; callbacks; evaluation
Multi‑agent patterns; agent handoffs
Swarm orchestration; routing logic

🚀 Getting Started

Clone the repository

1

git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git

Navigate to the desired project directory

1

cd awesome-llm-apps/starter_ai_agents/ai_travel_agent

Install the required dependencies
1

pip install -r requirements.txt
Follow the project-specific instructions in each project’s README.md file to set up and run the app.

NeuroTechEDU's Awesome List of BCI-related Resources

Mon, 02 Feb 2026 12:34:25 -0800

Introduction

Curated Collection of BCI resources

This is a list of tools, resources, and learning materials related to Brain-Computer Interfaces (BCI). The list is maintained by the NeuroTechX community.

Software

BCI Experiment Design and Analysis

These applications help you design BCI experiments, run them, collect data, and analyze the results.

EEG-ExPy: Free & Open-Source (FOSS) Python library for EEG & experiment design, recording, and analysis. Maintained by the EEG-ExPy team within NeuroTechX. CNS2024 Poster
OpenViBE: A software platform dedicated to designing, testing, and using Brain-Computer Interfaces, maintained by the OpenViBE Consortium.
BCI2000: Software suite with GUI based on C++ for data acquisition, stimulus presentation, and brain monitoring applications.
Brainstorm: Collaborative, open-source application dedicated to the analysis of brain recordings: MEG, EEG, fNIRS, ECoG, depth electrodes and multiunit electrophysiology.
BrainBay: Bio- and neurofeedback application working with various hardware frameworks including OpenBCI/OpenEEG.
EventIDE: EventIDE is a software platform for designing and running multimodal experiments, with an IDE.
NeuroPype: platform for real-time brain-computer interfacing (BCI), neuroimaging, and neural signal processing, which supports a range of biosignal modalities including EEG, fNIRS, ExG, etc.
MNE: MNE-Python is an open-source Python module for processing, analysis, and visualization of functional neuroimaging data (EEG, MEG, sEEG, ECoG, and fNIRS). The tools suite includes interoperable packages in Python, MATLAB, C++, etc., which operate in GUI, CLI, or API.
PsychoPy Builder: PsychoPy is an open-source application for creating experiments in neuroscience, psychology, and psychophysics.
PsychToolBox: Psychophysics Toolbox Version 3 (PTB-3) is a free set of Matlab and GNU Octave functions for vision and neuroscience research.

Matlab Toolboxes

Python Toolboxes

Mobile Apps

MindMonitor: iOS App Store, Google Play Store
NeuroSky Android SDK: Google Play Store
EEG-101 (Now-deprecated): Google Play Store

Brain Visualizations

RaspberryPi Framework

Communication Protocols

These are some of the commonly used Communication protocols.

Hardware

This section is separated into different sections based on the types of technology.

EEG

Electroencephalography is the most commonly used form of Neurotechnology. There are many options out there meaning that you can easily find a device that matches your needs and price.

Consumer and DIY Devices

Some of these devices are still supported and actively developed by manufacturers, community members, or researchers. Others are no longer supported but may still have a community of users who can help you get access.

Research Devices Manufactures

EEG Parts & Supplies

Conscious Labs - EEG Supra Headphones
Emotiv Flex Gel & Emotiv Flex Saline
Florida Research Instruments
DIY Electrode Design
TI ADS1299EEG-FE: Analog Front End for EEG solutions. e.g., in OpenBCI Cyton.
Intan Technologies: Microchips and miniature recording & stimulation headstages.
IDUN Dryode: Adhesive dry electrodes for EEG.
Bio-Medical: For supplies and consumables
Comparison of different types of electrodes

NIRS

Near-Infrared Spectroscopy (NIRS) is a technology that measures the concentration of hemoglobin in each brain region, which can be used to infer energy expenditure and hence higher activity in that region.

Multimodal Neurotech

These devices combine different type of sensors to measure or influence brain activity.

Brain Stimulation

DIY TMS: Transcranial Magnetic Stimulation (TMS)
Boston Scientific: DBS, SCS
Medtronic: DBS, tES, SCS
Magstim: TMS
Soterix Medical: TDCS, tACS, tRNS
Clarity: Light & Stimulation therapy for Alzheimer’s Disease
Vielight: Transcranial Photobiomodulation
Neuroelectrics: tDCS, tACS, tRNS
NeuroPace: RNS
NerveX: VNS in canine epilepsy.
NeuroSigma: eTNS
Brainsway: Deep TMS

Upcoming NeuroImaging Tech

Functional Ultrasound (FUS)
Event Related Optical Signal
Event-Related Optical Signal
Quasi-Ballistic Photons. (The Tech being used by Facebook’s BCI)
Open Electrical Impedance Tomography
Optically Pumped Magnetometers (OPM), e.g., QuSpin and Cerca:
- “Optically” stabilizing highly sensitive magnetometers to measure the change in magnetic fields due to neural activity.
- Does not need Helium cooling like conventional (SQUID) MEG, and hence is much smaller and lighter, and somewhat cheaper.
Diffused Optical Imaging: Used for instance by Mary Lou Jepken et al @ Openwater, aiming to build a portable MRI. More info on the tech:
- Diffuse optical imaging pt. 1 (wiki)
- Diffuse Optical Imaging pt. 2

Brain Databases

SCCN list of eeg/erp data for free public download
EEG studies with the raw data - (from BigEEG Consortium)
BNCI Horizon Data Sets
The Child Mind Institute MIPDB Dataset
RAM (DARPA) Invasive Recording Dataset from U. Penn
MindBigData MNIST of Brain Digits
MindBigData ImageNet of The Brain
meagmohit’s List of EEG Datasets
OpenNeuro
PhysioNet
National Sleep Research Resource: A large collection of sleep data. Supported by the Sleep Research Society (SRS).
Temple University EEG Corpora: various datasets including health, epilepsy, artifactual, etc.

Tutorials and Project Ideas

EEGEdu: Web-based live Tutorial on EEG and BCI, from basic to advanced. Maintained by the Mathewsons (Ky Kor Key)
How to Hack Toy EEGs
BCI Workshop
Introduction to Modern BCI
Brain-Controlled Shark Attack
Controlling a sphero with a muse
Building a 20 Euro EEG for your smartphone
Muse File Reader for OpenVibe
EEG 101: Interactive tutorial for Android and Muse
Brainwave analyzer
BCI Course offered by Columbia University
BCI Course at Berkeley by Pierre of NeuroTechX
EEG and MRI Course offered by OHBM
Prometheus Multimodal BCI (Olympic Torch)

Communities and Blogs

Forums

Blogs

NeuroTechX Content Lab: Articles, tutorials, and interviews on neurotechnology
The EEG Newsletter: News, events, and resources in EEG. By Raquel E. London
Natalie Schaworonkow
Autodidact
Strfry
Fabien Lotte
Chip Audette EEG Hacker
Alexandre Barachant
Pierre Karashchuk
Jeremy Frey
Irene Vigué Guix

Competitions

Data Competitions

Brain Controlled Competitions

Conferences and Events

Reading Material

Papers

Introductory Books

Technical Books

Signal Processing

Schools & Summer Courses

NeuroTech MicroCredentials Course: An accredited series of theoretical and hands-on courses on Neurotechnology, offered by NeuroTechX and Queens University.
Neuromatch Academy (NMA) Summer Schools: An online, community-driven set of summer schools in computational sciences
Sinxpress summer schools by Mike X. Cohen
Brainhack: A community-driven, online, and in-person school for neurotech enthusiasts, happening in many cities around you!
Recurring summer schools or community-maintained lists of Neurotech-related summer schools
- List maintained by N. Schwar
- List maintained by N. Biswas

Other Resources

Neuroscience Duke Course (Coursera)
Novel Neurotechnologies Intervening in the Brain
Augment Human Cognition by optimizing cortical oscillations
Open Neuroscience - a user-driven database of Open Source/Science projects related to Neurosciences
Awesome-BCI-Reviews - Curated list of Brain-Computer Interface peer-reviewd published reviews and surveys ordered by year of publication.

GitHub Awesome NeuroScience

Thu, 29 Jan 2026 15:35:25 -0800

Awesome Neuroscience

Introduction

Curated list of awesome neuroscience libraries, software and any content related to the domain.

Neuroscience is the study of how the nervous system develops, its structure, and what it does. Neuroscientists focus on the brain and its impact on behavior and cognitive functions. Traditionally, neuroscience has been seen as a branch of biology, but it has grown to encompass a wide range of interdisciplinary fields that work together toward elucidating brain function at multiple levels of investigation.

Programming

Software, libraries and frameworks for development purposes.

Python

Nengo - Library for creating and simulating large-scale brain models.
Nitime - Timeseries analysis for neuroscience data.
Nilearn - Module for performing statistical learning/machine learning on NeuroImaging data.
DIPY - Toolbox for analysis of MR diffusion imaging.
MNE-Python - Community-driven software for processing time-resolved neural signals including electroencephalography (EEG) and magnetoencephalography (MEG).
NiBabel - Provides read and write access to some common medical and neuroimaging file formats.
PsychoPy - Package for running psychology and neuroscience experiments. It allows for creating psychology stimuli in Python.
NuPic - Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.
Brian2 - Free, open source simulator for spiking neural networks.
expyriment - Platform-independent lightweight Python library for designing and conducting timing-critical behavioural and neuroimaging experiments.
BindsNET - Package for simulating spiking neural networks for reinforcement & machine learning.
SpikeInterface - Framework designed to unify spike-sorting technologies
NiMARE - NiMARE is a Python package for neuroimaging meta-analyses

Matlab

Brain Dynamics Toolbox - Open software for simulating dynamical systems in neuroscience.
BrainStorm - Open-source application dedicated to the analysis of brain recordings (MEG, EEG, fNIRS, ECoG, depth electrodes and multiunit electrophysiology).
EEGLAB - Interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data.
FieldTrip - Toolbox for MEG and EEG analysis.
Psychtoolbox-3 - Free set of Matlab and GNU Octave functions for vision and neuroscience research.
SPM - Free and open source software for the analysis of brain imaging data sequences (fMRI, PET, SPECT, EEG, MEG).

C++

Brayns - Minimalistic visualiser that can perform ray-traced rendering of neurons. Ray-tracing can help to highlight areas of neural circuits where cells touch each other and where synapses are being created leading to a better understanding of how individual cells and subsequently the brain functions.

JavaScript

Brainbrowser - Library exposing set of web-based 3D visualization tools primarily targetting neuroimaging.
jsPsych - Library for creating and running behavioural experiments in a web browser.

R

nat: NeuroAnatomy Toolbox - Package for the (3D) visualisation and analysis of biological image data, especially tracings of single neurons.
brainGraph - Package for performing graph theory analyses of brain MRI data.

Resources

Interesting resources related to neuroscience.

Ebooks

Neuroscience Online - Open-access electronic textbook and interactive courseware covering neuroscience in depth. Provided by the Department of Neurobiology and Anantomy at the University of Texas Medical School at Houston.
Computational Cognitive Neuroscience - Text which provides an in-depth introduction to the main ideas in the computational cognitive neuroscience, a field which aims to understand the brain by using biologically based computational models.
Neuronal Dynamics - Open-access electronic textbook that covers computational and theoretical neuroscience. Provided by École Polytechnique Fédérale de Lausanne (EPFL).
Andy’s Brain Book - Book companion to Andy’s Brain Blog. Provides an introduction to working in a Unix environment, fMRI analysis, and commonplace neuroimaging tools and topics.
NiPraxis - Textbook for the NiPraxis course, covers fundamental concepts in neuroimaging analysis and how they relate to the wider world of statistics, engineering and computer science. Learn how to work with data and code to get a deeper understanding of how fMRI methods work, how they can fail, how to fix them, and how to develop new methods.

Blogs

Neuroskeptic - Discover magazine’s neuroscience blog which offers a look at the latest developments in neuroscience, psychiatry and psychology through a critical lens.
The Neurocritic - Often critical takes on the most sensationalistic recent findings in Human Brain Imaging, Cognitive Neuroscience, and Psychopharmacology.
The scicurious brain - Maintained by Scientific American, this blog typically covers one research paper in a single entry.
Action Potential - Forum operated by neuroscience editors at the journal, Nature.
Andy’s Brain Blog - A large collection of articles, tutorials, and videos, covering many of the popular neuroimaging tools and methods.

MOOCs

Massive Open Online Courses (MOOCs) are free Web-based distance learning programs that are designed for the participation of large numbers of geographically dispersed students. MOOCs may be patterned on a college or university course or may be less structured.

The Fundamentals of Neuroscience | Harvard & edX - Serves an introductory survery of topics in neuroscience and has no specific prerequisites, though some prior exposure to biology and/or chemistry can be helpful.
Introduction to Neuroscience | MIT OCW - Introduction to the mammalian nervous system, with emphasis on the structure and function of the human brain.
Computational Neuroscience | Coursera - Provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function.
Medical Neuroscience - Explores the functional organization and neurophysiology of the human central nervous system, while providing a neurobiological framework for understanding human behavior.
Neuromatch Academy - Jupyter notebooks for the three-week intensive summer school in computational neuroscience.

Communities

Quora - Neuroscience topic on Quora contains answers, often by experts, to questions ranging from basic to advanced.
Reddit - List of neuroscience, psychology and cognitive science subreddits.
StackExchange - Psychology and neuroscience StackExchange site.
neuroimaging@python.org - A list for discussion of neuroimaging analysis in Python. Among other things, this list is home to discussions concerning NiPy projects (including NiBabel, Nilearn, dipy, MNE-Python, and more).

Newsletters

On The Brain - Harvard Mahoney Neuroscience Institute’s quarterly e-newsletter.
Comp-neuro - A mailing list that is is intended to address the broad range of research approaches and issues involved in the general field of computational neuroscience.
BrainPost - A mailing list that delivers weekly easy-to-read summaries of the latest neuroscience publications.

Miscellaneous

Awesome Public Datasets - Neuroscience - High-quality open neuroscience datasets.
McCulloch & Pitts Neural Net Simulator - Simulator for a historical computational model based on neurons.
ModelDB - Searchable database for computational neuroscience models.
NeuronDB - Searchable database for of three types of neuronal properties: voltage gated conductances, neurotransmitter receptors, and neurotransmitter substances.
NeuroElectro - Searchable database of neurons and their electrophysiological properties (extracted from literature)
Neuroscience Mindmap - Interactive mindmap containing curated resources for anyone interested in learning neuroscience.
neuroSummerSchools - List of summer (and seasonal) summer schools in neuroscience and related fields.
Brain Matters - Neuroscience podcast where real neuroscientists sit down and talk about the brain.
NeuroHackademy - Summer school in neuroimaging and data science, held at the University of Washington eScience Institute. Lectures are available through the institute’s YouTube channel.
SORTED - SORTED: a list of interesting science ideas and links (cognitive/neuro & data science)

GitHub Awesome Neuroimaging

Thu, 29 Jan 2026 14:34:25 -0800

Awesome Neuroimaging

Introduction

Exploring, organizing, and analysing brain images and recordings. MR focused.

Viewers

AFNI - Volumetric viewer from the AFNI suit. GUI’s aesthetic defined by the ’90s era Motif toolkit.
freeview - Surface and volumetric image viewer in Freesurfer suit. Uses the QT toolkit.
fsleyes - Volumetric viewer from FSL.
mricron - Volumetric viewer that works on windows.
dsistudio - DSI viewer from the dsi-studio suit of tools.
osirix - DICOM database organizer and viewer.
Mango - Multi-image Analysis GUI is a viewer for medical research images for dcm, nii, surface, etc; version 4.1 released in 2019.
wb_view - Connectome workbench surface file viewer.

Acquisition

MR

Organization

reproIn - Naming exam card sequences.
BIDS - Brain Imaging Data Structure - directory hierarchy and file naming specification.

Management

PACS - Picture Archiving and Communication System standard used to store and transfer DICOM images from medical equipment and likely implemented by scanner manufacture. See Siemens Healthineers Syngo Carbon, Phillips Vue PACS, GE HealthCare True PACS.
XNAT - An extensible open-source imaging informatics software platform dedicated to imaging-based research.
- DAX - Distributed Automation for XNAT: use containerization w/YAML defined input/output.
LORIS - LORIS (Longitudinal Online Research and Imaging System) is web-based data and project management software for neuroimaging research studies.
brainlife.io - Open-source, free and secure reproducible neuroscience analysis platform.
cbrain - CBRAIN is web-based software that allows neuroimaging researchers to perform computationally intensive analyses on data by connecting them to High-Performance Computing (HPC).
💲Flywheel - A cloud-based imaging research data platform for data capture, curating, automation, and machine learning.
💲QMENTA - The all in one imaging platform for your clinical trial.

Motion

FIRMM - Real-time motion monitoring for fMRI, diffusion, and navigated T1/T2 image acquisition.
Dimon - Monitor real-time acquisition of DICOM image files with AFNI.

Quality Assurance and Checking

QA and QC of scanner images.

MRIQC - Extracts no-reference IQMs (image quality metrics) from structural (T1w and T2w) and functional MRI (magnetic resonance imaging) data.
mrQA - Tools for quality assurance in medical imaging datasets, including protocol compliance.
bids-validator - Validator for the Brain Imaging Data Structure.

Pipelines

Preprocessing workflows.

Suites

Software packages for multiple modalities, often offering a graphical user interface.

AFNI - Analysis of Functional NeuroImages is a leading software suite of C, Python, R programs and shell scripts primarily developed for the analysis and display of multiple MRI modalities.
FSL - A comprehensive library of analysis tools for FMRI, MRI and diffusion brain imaging data.
SPM - Statistical Parametric Mapping refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional imaging data.
Qu|Nex - The Quantitative Neuroimaging Environment & Toolbox (QuNex) is an open-source software suite that collectively supports an extensible framework for data organization, preprocessing, quality assurance, and analyses across neuroimaging modalities.

BOLD

fmriprep - Accessible preprocessing pipeline robust to variations in scan acquisition protocols with comprehensive error and output reporting. Input is BIDS dataset.
afni_proc.py - Best practice pipelines with pre-configured blocks using AFNI.
HALFpipe - User-friendly software that facilitates reproducible analysis of fMRI data.
XCP-D - Post-processing and noise regression pipeline picks up right where fMRIprep ends.
clpipe - Uses fmriprep for preprocessing fMRI data and implements a variety of additional processing steps important for functional connectivity analyses such as nuisance regression and filtering.
fmri_processing_scripts - Legacy pipeline for maximal preprocessing.
HCP Pipeline - Pipeline scripts implement the Minimal Preprocessing Pipeline (MPP) described in Glasser et al. 2013.

DSI

dsi-studio - A tractography software tool that maps brain connections and correlates findings with neuropsychological disorders.
qsiprep - Configures pipelines for processing diffusion-weighted MRI (dMRI) data.

Structural

Freesurfer - An open source neuroimaging toolkit for processing, analyzing, and visualizing human brain MR images.
CIVET - An image processing pipeline for fully automated volumetric, corticometric, and morphometric analysis of human brain imaging data.

Raw Data

Dealing with DICOM and k-space images

dcm2niix - DICOM to NIfTI converter.
heudiconv - A flexible DICOM converter for organizing brain imaging data into structured directory layouts.
gdcm - Grassroots DICOM is a C++ library and CLI tool for DICOM medical files.
pydicom - Python package and cli tool for inspecting, modifying, and creating DICOM files.
dicom_hinfo, dicom_hdr - Prints selected information from the DICOM file.
dcmdirtab, dcmtab_bids - CLI focused, regular expression based, and iteration friendly BIDS conversion pipeline from lncdtools.
pymapVBVD - Reads Siemens .dat ’twix’ raw data files. Python port of Philipp Ehses’ Matlab tool mapVBVD.
med2image - Python CLI tool for generating jpg or png images from DICOM or nifti files.

Provenance and Automation

make - follow script recipes defined in Makefile.
datalad - Keep code, data, containers under control with git and git-annex. Esp datalad run --input=... --output=....
3dNotes - A program to add, delete and show notes for AFNI datasets.
niinote - Add AFNI nifti XML history to header to run and record any command. Part of lncdtools.

Imaging Tools

Software to read, write, and manipulate volumetric and/or surface data.

Skullstripping

optibet - Shell script to combine afni and fsl tools for more robust skull stripping in patient populations.
3dSkullStrip - AFNI’s skull stripping utility with many parameters.
bet - FSL’s brain extraction tool.
antsBrainExtraction.sh - ANTs version.
mri-watershed - Part of the Freesurfer pipeline.
ROBEX - Robust Brain Extraction without parameter tweaking.

Warping

Spatial normalization

ANTs - Advanced Normalization Tools includes probabilistic tissue segmentation and machine learning methods based on expert labeled data to order to maximize reliability and consistency of multiple modality image segmentation.
3dQwarp - OpenMP parallelized AFNI tool to compute a nonlinearly warped version of source dataset to match a base dataset.
flirt, fnirt - Warping software provided by FSL tools.

Templates

templateflow - A modular, version-controlled resource that allows researchers to use templates “off-the-shelf” and share new ones.
MNI152 - Unbiased standard magnetic resonance imaging template brain volume for normal population.

Manipulation

Tools for doing math on matrix values

3dcalc - Voxel-by-voxel arithmetic on 1D to 4D datasets. From AFNI.
fslmaths - Simple but powerful program to allow mathematical manipulation of images. From FSL.
fscalc - Freesurfer wrapper of fslmaths.

Modeling

HRF

3dDeconvolve - AFNI - Program to calculate the deconvolution of a measurement 3D+time dataset with a specified input stimulus time series. This program can also perform multiple linear regression using multiple input stimulus time series.
FEAT - GUI guided analysis of simple experiment based on general linear modeling. Part of FSL.

MRSI

lcmodel - Implements linear-combination modeling of magnetic resonance spectroscopy data.
FSL-MRS - A suite of tools for MR Spectroscopy, including single voxel (SVS), MRS imaging (MRSI), functional MRS (fMRS), diffusion MRS (dwMRS), edited spectroscopy, etc.
Osprey - An all-in-one software suite for state-of-the art processing and quantitative analysis of in-vivo magnetic resonance spectroscopy (MRS) data.

EEG

fooof - Fast, efficient, and physiologically-informed tool to parameterize neural power spectra.

Misc

hurst - Algorithm to assess intrinsic excitation-inhibition imbalance in MR (Trakoshis et al, eLife, 2020).
tat2 - Time-averaged T2* wrapper script using AFNI binaries from lncdtools.

Libraries

Python

nipy - Includes nibabel, nipype, and nilearn.

R

oro.nifti - Functions for the input/output and visualization of medical imaging data that follow either the ANALYZE, NIfTI or AFNI formats.

MATLAB

SPM - Statistical Parametric Mapping refers to the construction and assessment of spatially extended statistical processes used to test hypotheses about functional imaging data.
imtool3D_td - 3D Image Viewer with ROI tools for Matlab (NIFTI viewer, Manual segmentation).

Resources

Blogs, Books, and Docs

Andy’s brain blog - Tutorials and videos about neuroimaging analysis from start to finish in all the major software packages (AFNI, SPM, and FSL).
DataLad handbook - Start-to-end use cases of specific applications in neuroimaging using provenance tracking software datalad.
Hitchhacker’s guide to the brain - Notes from study planning to reporting and data sharing by way of acquisition, processing, analysis, and quality control.
Online Neuroimaging Resources - A laundry list of online resources for MRI, fMRI, EEG, MEG.
U of A: Neuroimaging Core Documentation - Documentation for approaches used and/or developed by the neuroimaging core at the University of Arizona.

Boards And Chats

neurostars - General neuroimaging discuss form. fmriprep suggested Q&A site.
afni discuss - AFNI’s discuss instance.
brainhack - A mattermoust community of neuroimagers.

Datasets Repositories

openneuro - A free and open platform for validating and sharing BIDS-compliant MRI, PET, MEG, EEG, and iEEG data.
NDA - National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains.
NITRC - NeuroImaging Tools & Resources Collaboratory library of neuroinformatics software and data.

Big datasets

ABCD - Long-term Adolescent Brain Cognitive Development study including 1000s of longitudinal MRI scans.
UK Biobank - A large-scale biomedical database and research resource with 500,000 research participants.
NCANDA - National Consortium on Alcohol and Neurodevelopment in Adolescence (4000+ MR visits).
PNC - A population-based sample of over 9500 individuals from the greater Philadelphia area, ages 8-21 years who received medical care at the CHOP network.
ENIGMA - The Enhancing Neuro Imaging Genetics through Meta Analysis Consortium contains 50 working group’s imaging and genomics data.

GitHub Awesome Stock Trading

Thu, 29 Jan 2026 14:34:25 -0800

Awesome Stock Trading

Introduction

The curated list of resources for research and learning about stock trading and investing. It contains links to various resources and tools that can help anyone who wants to start or improve their stock trading skills. The project aims to be a comprehensive and useful list for anyone interested in stock trading.

Stock Research

Alpha Spread - Provides data and tools for quantitative research and stock valuation.
Barchart - Offers market data, analysis, and tools for commodity, stock, and forex traders.
Capitol Trade - Keeping Tabs on Politicians’ Trades (US only).
Chartmill - ChartMill is a stock screening and analysis platform.
Danelfin - Provides AI-Powered Stock Research & Picking Tools.
Finbox - Offers tools for financial analysis, valuation, and screening of stocks.
Market Beat - Provides stock research, ratings, and news for individual investors.
Market Screener - Offers stock market quotes, news, analysis, and screening tools.
Morningstar - Provides investment research, ratings, and tools for stocks, mutual funds, and ETFs.
Seeking Alpha - Offers market news and analysis, portfolio management tools, and investment ideas from contributors.
Simply Wall St - Simply Wall St. has a unique pictorial approach to quickly and effectively cut through the massive amounts of data to narrow to a select few candidates.
Strike.Market - Offers a platform for trading options and derivatives on cryptocurrency markets.
Tip Ranks - Provides ratings and analysis of stocks and financial experts based on their historical performance.
Wall Street Zen - Offers tools for financial analysis, screening, and backtesting of investment strategies.
Wallmine - Provides stock analysis, screening, and news for individual investors.
Zacks - Provides research, analysis, and ratings for stocks and funds based on quantitative models and fundamental data.

Market Analysis

Companies Market Cap - Provides a list of companies and their market capitalizations, allowing users to easily track the valuations of various publicly traded companies. It also includes useful data such as industry classifications and stock exchange listings.
Fear & Greed Index - Provides a market sentiment indicator for investors. It analyzes seven different indicators, including market volatility, investor sentiment, and safe-haven demand, to generate a score ranging from 0-100 that reflects whether the market is in a state of fear or greed.
Trading Terminal - Overview of the most important metrics for the US Market.
Tradytics - AI predictions, intraday market price action, biggest movers, sectors performance, and more.

Stock Screener

Cnbc Stock Screener - Stock screener for US stock market.
Finviz - Free stock screener with financial visualizations.
Market Beat Stock Screener - US stock market screener that allows filtering stocks by market cap, sector, industry, and more.
Simply Wall St Stock Screener - Global stock screener that allows filtering stocks by market cap, sector, industry, and more.
Tip Ranks Stock Screener - International stock market screener that allows filtering stocks by market cap, sector, industry, and more.
Trading Terminal Scanner - US market stock screener that allows filtering stocks by market cap, sector, industry, and more.
Wallmine Free Stock Screener - Free stock screener that allows filtering stocks by market cap, sector, industry, and more.
Wallstreet Zen Stock Screener - Free US stock market screener that allows filtering stocks by market cap, sector, industry, and more.
Zacks Stock Screener - US stock market screener that allows filtering stocks by market cap, sector, industry, and more.

Charting

TradingView - Platform that offers charting tools, trading ideas, and real-time market data for stocks, forex, cryptocurrencies, and other financial instruments.
StockCharts - Technical analysis and charting website that provides advanced charting tools, custom indicators, and market analysis for stocks, funds, and indices.

News

Barron’s - Financial magazine that provides news, analysis, and insights on the stock market, investing, and personal finance.
Benzinga - Financial news and data provider that delivers real-time market updates, stock analysis, and investment ideas.
Bloomberg - Financial news and information company that covers business, markets, politics, and technology.
Investing - Online platform that offers financial news, real-time quotes, and analysis on stocks, currencies, commodities, and other investments.
MarketWatch - Financial news website that provides business news, analysis, and stock market data.
The Motley Fool - Investment website that provides stock market analysis, investing ideas, and personal finance advice.
The Wall Street Journal - A business-focused newspaper that covers global news, markets, and economics.
The Street - Financial news and investing website that offers stock market analysis, investment strategies, and personal finance advice.
Yahoo Finance - Financial news and data website that provides real-time stock quotes, financial news, and investment analysis.

Commentaries

J.P. Morgan - Market Updates - Weekly commentaries to get market insights from J.P. Morgan.
MSCI - Market Insights - Market commentaries and research reports with a focus on macroeconomic topics.

Portfolio Tracker

Portfolio Visualizer - Portfolio management and analysis tool that provides portfolio optimization, backtesting, and risk analysis.
Wealthica - Wealth management platform that provides portfolio management, financial planning, and investment research.

Strategy Backtesting

Screening Tale - Backtesting platform that allows users to test their trading strategies on historical data.
QuantConnect - Algorithmic trading platform that provides backtesting, live trading, and research tools for stocks, forex, and cryptocurrencies.

Stock Picks

Alpha Picks - Alpha Picks gives you two top stock picks each month, sifted from Seeking Alpha analysis of thousands of stocks.
Benzinga Pro - Benzinga offers daily trade picks from professional day traders with on-demand support, as well as exclusive market-moving stories.
Best Stocks to Buy Now - Investopedia list of the best stocks to buy now.
EarningsBeats - EarningsBeats.com provides a research and educational platform for investors. Services are designed to help their members beat the S&P 500.
Investing Groups by Seeking Alpha - Investing groups on Seeking Alpha that provide stock picks, analysis, and market insights.
The Motley Fool Stock Advisor - Stock Advisor is a premium service that provides stock picks, analysis, and market insights.

Stock Collections

Growth 250 - MarketSmith’s Growth 250 is a curated list of high-potential stocks.
StockTwits Top 10 - StockTwits’ list of the top 10 trending stocks.

Stock APIs

Alpha Vantage - Alpha Vantage offers free APIs for realtime and historical stock data, forex, and cryptocurrency data.
Eodhistoricaldata - Eodhistoricaldata offers APIs for realtime and historical stock data, forex, and cryptocurrency data.
Financial Modeling Prep - Financial Modeling Prep API provides real time stock price, company financial statements, major index prices, stock historical data, forex real time rate and cryptocurrencies.
MarketStack - MarketStack offers APIs for realtime and historical stock data, forex, and cryptocurrency data.
Morningstar - Provides data, research, and reports.
Nasdaq Data Link - Nasdaq Data Link offers a premier source for financial, economic and alternative datasets.
Massive - Massive offers APIs for realtime and historical stock data, forex, and cryptocurrency data.
Refinitiv Eikon Data - The Eikon Data API allows applications to access data directly from Eikon or Refinitv Workspace.

Knowledge

Investopedia - Investopedia.com is a website that provides educational content, news, analysis, and tools related to investing, finance, and business.
StockScreening101 - StockScreening101 is a website that provides educational content, news, analysis, and tools related to investing, finance, and business.
Wallstreetmojo - Learn Investment Banking, Finance Modeling and Excel with more than 4800+ Articles, Self Study Guides, Resources and courses.

Books

Value Investing and Fundamental Analysis

Berkshire Hathaway Letters to Shareholders - Warren Buffett, 2016
For nearly six decades, Warren Buffett has written an annual letter to his shareholders. The letters, written between 1965 and 2014, reveal the investor’s thoughts on investment strategy, share buybacks, corporate culture and much more.
Common Stocks and Uncommon Profits - Philip A. Fisher, 1957
This book is considered a classic and is used as part of several investment courses, such as Stanford Graduate School of Business. In the book, Fisher explains his basic views and approach to his investment strategies.
Damodaran on Valuation: Security Analysis for Investment and Corporate Finance - Aswath Damodaran, 1994
Damodaran explains aspect of valuation, from the basics of estimating cash flows and discount rates to the principles for using multiples.
Margin of Safety: Risk-Averse Value Investing Strategies for the Thoughtful Investor - Seth Klarman, 1991
Margin of Safety explains the key fundamentals and practices of value investing. He outlines what value investing looks like and where investors might find attractive opportunities.
Security Analysis - Benjamin Graham, 1934
This book laid the intellectual foundation for what would later be called value investing. The first edition was published in 1934, shortly after the Wall Street crash and start of the Great Depression.
The Alchemy of Finance - George Soros, 1987
This book offers insight into the decision-making process of one of the most successful wealth managers, George Soros.
The Dhandho Investor: The Low-Risk Value Method to High Returns - Mohnish Pabrai, 2007
Written by Mohnish Pabrai, an investor of Indian origin, the book explains his value investing approach using the Dhandho capital allocation framework.
The Intelligent Investor - Benjamin Graham, 1949
In this book, Grahame explains his investment principles and views regarding an investor’s mindset. He shows how investors analyze the actual performance of companies and advises to disregard the changing moods of the market.
The Little Book of Value Investing - Christopher H. Browne, 2006
Brown explains the basic approaches of the value investing philosophy, but without making any big promises about market success. He provides guidance on the use of simple metrics such as the price-earnings ratio.
The Most Important Thing - Howard Marks, 2011
In this book, Howard Marks summarizes investment insights from his client memos and explains his investment philosophy.
The Thoughtful Investor - Basant Maheshwari, 2011
Maheshwari, a renowned Indian investor, explains in his book topics of financial analysis, the analysis of individual sectors and the behavioral aspect of investing.
The Warren Buffett Way - Robert G. Hagstrom, 2007
The book describes the business and investment principles of value investing according to Warren Buffett.
Value Investing: From Graham to Buffett and Beyond - Bruce C. N. Greenwald, 2004
Greenwald explains the basic techniques of value investing and, in this context, illustrates their application using profiles of successful investors.

Quantitative Investing and Portfolio Management

Active Portfolio Management - Richard C. Grinold, Ronald Kahn, 1994
In this book, Grinold and Kahn show how economics, econometrics, and operations research can be used to solve practical investment problems and identify profit opportunities.
Portfolio Selection: Efficient Diversification of Investments - Harry M. Markowitz, 1968
A comprehensive explanation of analysis and calculation methods to help investors find the best combinations of securities to match their requirements.
Quantitative Equity Portfolio Management - Ludwig B. Chincarini, Daehwan Kim, 2006
The authors address the construction and management of a portfolio using quantitative methods. Among other things, they offer explanations of factor models and the prediction of premiums and exposures.

General Stock Trading

Beating the Street - Peter Lynch, 1992
In the book, Lynch, a successful fund manager from 1977 to 1990, gives readers insight into his investment methods and tactics.
Charlie Munger: The Complete Investor - Tren Griffin, 2015
Tren Griffin uses interviews, writings, and letters to explain the investment philosophy and thought processes of Charlie Munger, vice chairman of Berkshire Hathaway and longtime business partner of Warren Buffett.
Market Wizards: Interviews with Top Traders - Jack D. Schwager, 1989
By interviewing successful investors such as Bruce Kovner, Richard Dennis, Paul Tudor Jones, Michel Steinhardt, Ed Seykota, Marty Schwartz, Tom Baldwin, and others, Schwager explores what separates the world’s best traders from the vast majority of unsuccessful investors.
One Up On Wall Street - Peter Lynch, 1989
Peter Lynch, who managed Fidelity Investment’s successful Magellan Fund from 1977 to 1990, gives investors an insight into his investment methods. Using simple examples and some practices, he explains his process of stock selection.
Stocks for the Long Run - Jeremy Siegel, 1994
The book by Siegel, a finance professor, addresses how to build a balanced portfolio and explains how investors can avoid typical mistakes.
The Battle for Investment Survival - Gerald M. Loeb, 1911
Now more than 100 years old, Gerald M. Loeb’s work is considered a classic of financial literature. In his explanations, Loeb straightforwardly explains how investors should behave in rising and falling markets.
The Complete Turtle Trader - Michael W. Covel, 2007
The author tells the story of Richard Dennis, an extraordinarily successful stock market trader of the 1980s, and how he turned a group of beginners, under his guidance, into extraordinarily successful traders.
The Craft of Investing - John Train, 1994
In the book, Train outlines his key strategies and principles that have brought him success, addressing everything from the psychology of the market to practical portfolio management tips.
The Little Book of Trading - Michael W. Covel, 2011
Michael W. Covel’s book offers insights into the rules and philosophies used by successful traders. Drawing on the author’s own trading experience and the wisdom of other traders, the book offers advice in a direct and easy-to-understand manner.
The Little Book that Still Beats the Market - Joel Greenblatt, 2007
Joel Greenblatt explains how investors can outperform the popular market averages by systematically applying a formula. The book is kept simple and is aimed at beginners.
The New Market Wizards - Jack D. Schwager, 1992
Jack Schwager interviews some of the most successful stock traders in the United States. Through these interviews, Schwager offers insight into the strategies, perspectives, and psychological insights of successful traders.
Think & Trade Like a Champion - Mark Minervini, 2017
In this book, Mark Minervini explains readers how to apply his methods step by step to enhance their trading performance and create the confidence they need to outperform.

Trend Following

Investing with Volume Analysis - Buff Dormeier, 2011
Dormeier offers insights into using volume metrics to enhance stock trading strategies, providing a framework for interpreting price-volume relationships to predict market trends.
Learn to Trade Momentum Stocks - Matthew R. Kratter, 2015
This beginner-friendly book presents a trading strategy by Matthew R. Kratter. It is designed to give readers the knowledge and skills to make profitable trades in momentum stocks.
Stocks on the Move - Andreas Clenow, 2015
In this book, Clenow, a hedge fund manager, explores why most mutual funds consistently underperform and shows how anyone can outperform them. He emphasizes the power of momentum investing as one of the few consistent ways to beat the markets.
Trading the Trends - L. A. Little, 2011
The book covers various aspects, including identifying trends, using technical indicators, and managing risk. The content is written in an easy-to-understand style, providing readers with valuable insights into understanding and profiting from the stock market.
Trend Following - Michael W. Covel, 2004
Michael W. Covel’s book explains trend following without explicitly addressing specific strategies and provides insights on how to use trend following in market situations, whether bull or bear markets.
Trend Qualification and Trading - L. A. Little, 2011
Through a proven technical approach, the book explains how to gauge the likelihood of trend continuation and its potential for better trading results. Readers will gain understanding on timing entries, taking profits, and effectively exiting trades based on these trends.
Trend Trading Set-Ups - L. A. Little, 2012
Building on the neoclassical concept, Little presents traders and investors with a robust methodology to discover promising trade setups and achieve precise timing for trade entry.

Price Action Trading

Price Action Breakdown - Laurentiu Damir, 2016
This book provides a comprehensive guide to trading pure price action analysis. It covers concepts, ideas and trading methods based on pure price action and can be applied to various financial markets.
Price Action Trading Secrets - Rayner Teo, 2020
Rayner Teo’s book is intended as a guide to the use of price action trading. The book covers trading strategies, instruments and techniques and is written in a simple, step-by-step manner.
Pring on Price Patterns - Martin J. Pring, 2009
Martin J. Pring’s book provides a comprehensive examination of the most commonly used price patterns and offers insights into their effectiveness and logic. The book covers a range of patterns, including one- and two-bar patterns, outside bars, reversals, pennants, and more.
Stock Trading & Investing Using Volume Price Analysis - Anna Coulling, 2015
Anna Coulling provides an in-depth examination of volume price analysis in stock trading. In doing so, she examines the approaches of other successful price analysis practitioners and explains them with examples.
Trading Price Action Trends - Al Brooks, 2011
Al Brooks’ book is intended as a practical guide to profiting from institutional trading trends. The book breaks down Brooks’ trading system into its essential components such as institutional piggybacking or trend trading.

Behavioral Finance and Psychological Aspect of Investing

Irrational Exuberance - Robert J. Shiller, 2000
Robert J. Shiller’s book addresses the psychological and behavioral factors that influence financial markets. It explores the concept of speculative bubbles and irrational exuberance, in which exuberant investor behavior leads to overvaluation of assets.
The Little Book of Behavioral Investing: How not to be your own worst enemy - James Montier, 2010
Author James Montier looks at the psychological aspects of investing and examines common behavioral biases that can hinder investors’ success in the marketplace.
The Wisdom of Crowds - James Surowiecki, 2004
James Surowiecki’s book addresses the concept that large groups of people collectively have higher intelligence than individual experts. Surowiecki supports his argument with various case studies and anecdotes from different fields.

Risk and Uncertainty

Against the Gods - Peter L. Bernstein, 1996
Bernstein takes the reader on a journey through time, showing how societies throughout history have dealt with uncertainty and developed methods for measuring and managing risk. The author shows the profound impact of risk and probability on human decision making and the development of modern finance.
Fooled by Randomness - Nassim Nicholas Taleb, 2001
Part of Taleb’s multi-volume philosophical essay on uncertainty, this book examines various misconceptions of chance, including survival bias and skewed distributions, and illuminates how people tend to seek explanations even when there are none.
The 5 Mistakes Every Investor Makes and How to Avoid Them - Peter Mallouk, 2014
Mallouk’s work discusses the most common mistakes investors make and how to avoid them. Among the most important lessons are the pitfalls of market timing and active trading, which are suboptimal compared to passive strategies.
The Black Swan - Nassim Nicholas Taleb, 2007
Taleb explores the concept of so-called black swans. These are rare and unpredictable events that have massive consequences and are often rationalized retroactively.

Contemporary History

Dot.con: How America Lost Its Mind and Money in the Internet Era - John Cassidy, 2002
Cassidy chronicles the rise and fall of the dot-com bubble with insight and flair. He introduces the key players and events that shaped the Internet era, from visionary entrepreneurs to ruthless investors.

Most Important Stock Exchanges

🇦🇺 Australian Securities Exchange (ASX) - The largest stock exchange in Australia, known for its strong mining and resource sector.
🇧🇷 B3 (Bovespa) - The largest stock exchange in Latin America and one of the fastest-growing markets globally.
🇮🇳 Bombay Stock Exchange (BSE) - The oldest stock exchange in Asia, founded in 1875, and one of the largest in India.
🇩🇪 Frankfurt Stock Exchange (XETRA) - The largest stock exchange in Germany owned and operated by Deutsche Börse.
🇭🇰 Hong Kong Stock Exchange (HKEX) - One of the largest stock exchanges in Asia, known for attracting international investors due to its strategic location and listing rules.
🇰🇷 Korea Exchange (KRX) - The sole securities exchange operator in South Korea, hosting the KOSPI index.
🇬🇧 London Stock Exchange (LSE) - One of the oldest and most important stock exchanges in the world, with over 3,000 listed companies.
🇺🇸 NASDAQ - Second largest stock exchange in the world by market capitalization, known for listing technology companies and having a high trading volume.
🇮🇳 National Stock Exchange of India (NSE) - The largest stock exchange in India by market capitalization and trading volume.
🇺🇸 New York Stock Exchange (NYSE) - Largest stock exchange in the world by market capitalization, with over 2,800 listed companies.
🇨🇳 Shanghai Stock Exchange (SSE) - Fourth largest stock exchange in the world by market capitalization, and the largest in mainland China.
🇨🇳 Shenzhen Stock Exchange (SZSE) - One of the largest stock exchanges in China, known for its focus on technology and growth companies.
🇸🇬 Singapore Exchange (SGX) - One of the leading Asian exchanges, known for its regulatory excellence and derivatives market.
🇨🇭 Swiss Stock Exchange (SIX) - The principal stock exchange in Switzerland, known for its life sciences and financial services companies.
🇯🇵 Tokyo Stock Exchange (TSE) - Third largest stock exchange in the world by market capitalization, and the largest in Asia.
🇨🇦 Toronto Stock Exchange (TSX) - The largest stock exchange in Canada and a major global mining and energy hub.
🇪🇺 Euronext - A pan-European stock exchange operating in several countries, including France, the Netherlands, Belgium, Portugal, and Ireland.

GitHub Awesome Roadmaps

Thu, 29 Jan 2026 13:34:25 -0800

Awesome Roadmaps

Introduction

A curated list of roadmaps, mostly about software development, which give you a clear route to improve your knowledge or skills.

Programming Language

C++ Developer Roadmap - Roadmap focuses on general competencies and skills about C++ in 2024 .
Go Developer Roadmap - Roadmap to becoming a Go developer in 2021 .
Java Developer Roadmap - Roadmap to becoming a Java developer in 2025 .
Nodejs Developer Roadmap - Roadmap to becoming a Node.js developer in 2021 .
PHP Developer roadmap - Following this path will guarantee to Become a PHP Developer in 2021 .
Rust Web Developer Roadmap - Roadmap to becoming a Rust Web developer in 2022 .

Web Development

Angular Developer Roadmap - Roadmap to becoming an Angular developer .
Angular Developer Roadmap 2 - Roadmap to becoming an Angular developer in 2024 .
ASP.Net Core Developer Roadmap - Roadmap to becoming an ASP .NET Core developer in 2025 .
Developer Roadmap - Community driven roadmaps, articles and resources for developers .
Frontend development roadmap - Frontend development interview checklist & roadmap .
Laravel Developer Roadmap - Roadmap to becoming an Laravel developer in 2024 .
React Developer Roadmap - Roadmap to becoming a React developer in 2019 .
Vue Developer Roadmap - Roadmap to becoming a Vue.js developer in 2019 .

Mobile Development

Android Developer Roadmap - Roadmap to becoming an Android developer in 2020 .
Flutter Developer Roadmap - Roadmap for creating hybrid apps using Google’s Flutter SDK .
iOS Developer Roadmap - Roadmap to becoming an iOS developer in 2020 .

Game Development

Game Developer Roadmap - Roadmap to becoming a game developer in 2022 .
Game Programming Roadmap - Roadmap to becoming a game programmer .

AI / Machine Learning / Data Science

AI Expert Roadmap - Roadmap to becoming an Artificial Intelligence Expert in 2022 .
Deep Learning Reading Roadmap - Roadmap through seminal deep learning papers .
Deep Learning Roadmap - Roadmap to getting started with deep learning .
Data Engineer Roadmap - Roadmap to becoming a data engineer in 2021 .
Data Science Roadmap - Roadmap to becoming a data scientist .
Data Scientist Roadmap - Roadmap of tutorials for those interested in data science .
NLP Roadmap - Roadmap for Natural Language Processing learning in 2019 .

Miscellaneous

Awesome Quality Assurance Roadmap - Roadmap for QA and software testing learning curve which you might need to start the journey .
Hacker Roadmap - Roadmap for amateur pen testers and a collection of hacking tools, resources and references ❗.
Software Architect Roadmap - Roadmap for becoming a software architect .
Software Design and Architecture Roadmap - A software design and architecture roadmap for any developer .
System Design Roadmap - Roadmap to learn system design and architecture .
UI/UX Designer Roadmap - Roadmap on becoming a UI/UX designer in 2017 .
University Degree Roadmap - Roadmap for taking online university courses in various degree subjects .

Articles

A Roadmap To Become A Better Android Developer - A collection of articles to provide a proper roadmap to become a better Android Developer .
Java Full Stack Developer Roadmap - Discover all the tech career roadmaps and latest market trends in the tech job market !
Data Analytics Roadmap - Unlock success with this comprehensive roadmap: your guide to mastering analytics skills and career growth!

GitHub Repo Awesome Public Datasets

Wed, 31 Dec 2025 13:34:25 -0800

Awesome Public Datasets

This is a list of topic-centric public data sources in high quality. They are collected and tidied from blogs, answers, and user responses. Most of the data sets listed below are free, however, some are not. This project was incubated at OMNILab, Shanghai Jiao Tong University during Xiaming Chen's Ph.D. studies. OMNILab is now part of the BaiYuLan Open AI community.

Other amazingly awesome lists can be found in sindresorhus's awesome list.

Agriculture

The global dataset of historical yields for major crops 1981–2016 - The Global Dataset of \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Agriculture/Global-dataset-of-historical-yields-for-major-crops.yml)\]
Hyperspectral benchmark dataset on soil moisture - This dataset was measured in a five-day \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Agriculture/Hyperspectral-Benchmark-Dataset-On-Soil-Moisture.yml)\]
Lemons quality control dataset - Lemon dataset has been prepared to investigate the \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Agriculture/Lemon-Dataset.yml)\]
Optimized Soil Adjusted Vegetation Index - The IDB is a tool for working with remote sensing \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Agriculture/Optimized%20Soil%20Adjusted%20Vegetation%20Index)\]
U.S. Department of Agriculture's Nutrient Database - USDA National Nutrient Database for \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Agriculture/U.S.-Department-of-Agricultures-Nutrient-Database.yml)\]
U.S. Department of Agriculture's PLANTS Database - The Complete PLANTS Checklist is nearly 7 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Agriculture/U.S.-Department-of-Agricultures-PLANTS-Database.yml)\]

Architecture

Swiss Apartment Models - This dataset contains detailed data on 42,207 apartments (242,257 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Architecture/appartment-models.yml)\]

Biology

1000 Genomes - The 1000 Genomes Project ran between 2008 and 2015, creating the largest \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/1000-Genomes.yml)\]
ANHIR - Automatic Non-rigid Histological Image Registration (ANHIR) consists of 2D \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/ANHIR.yml)\]
American Gut (Microbiome Project) - The American Gut project is the largest crowdsourced \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/American-Gut-Microbiome-Project.yml)\]
BCNB - There are WSIs of 1058 patients, part of tumor regions are annotated in WSIs. Except \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/BCNB.yml)\]
Broad Bioimage Benchmark Collection (BBBC) - The Broad Bioimage Benchmark Collection (BBBC) \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Broad-Bioimage-Benchmark-Collection-BBBC.yml)\]
Broad Cancer Cell Line Encyclopedia (CCLE) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Broad-Cancer-Cell-Line-Encyclopedia-CCLE.yml)\]
CIMA - CIMA dataset includes images of 2D histological microscopy tissue slices. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/CIMA.yml)\]
Cell Image Library - This library is a public and easily accessible resource database of \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Cell-Image-Library.yml)\]
Complete Genomics Public Data - A diverse data set of whole human genomes are freely \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Complete-Genomics-Public-Data.yml)\]
CytoImageNet - A large-scale dataset of microscopy images. Contains 890,737 total grayscale \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/CytoImageNet.yml)\]
EBI ArrayExpress - ArrayExpress Archive of Functional Genomics Data stores data from high- \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/EBI-ArrayExpress.yml)\]
EBI Protein Data Bank in Europe - The Electron Microscopy Data Bank (EMDB) is a public \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/EBI-Protein-Data-Bank-in-Europe.yml)\]
ENCODE project - The Encyclopedia of DNA Elements (ENCODE) Consortium is an ongoing \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/ENCODE-project.yml)\]
Electron Microscopy Pilot Image Archive (EMPIAR) - EMPIAR, the Electron Microscopy Public \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Electron-Microscopy-Pilot-Image-Archive-EMPIAR.yml)\]
Ensembl Genomes \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Ensembl-Genomes.yml)\]
Gene Expression Omnibus (GEO) - GEO is a public functional genomics data repository \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Gene-Expression-Omnibus-GEO.yml)\]
Gene Ontology (GO) - GO annotation files \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Gene-Ontology-GO.yml)\]
Global Biotic Interactions (GloBI) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Global-Biotic-Interactions-GloBI.yml)\]
Harvard Medical School (HMS) LINCS Project - The Harvard Medical School (HMS) LINCS Center is \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Harvard-Medical-School-LINCS-Project.yml)\]
Human Genome Diversity Project - A group of scientists at Stanford University have \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Human-Genome-Diversity-Project.yml)\]
Human Microbiome Project (HMP) - The HMP sequenced over 2000 reference genomes isolated from \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Human-Microbiome-Project-HMP.yml)\]
ICOS PSP Benchmark - The ICOS PSP benchmarks repository contains an adjustable real-world \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/ICOS-PSP-Benchmark.yml)\]
International HapMap Project \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/International-HapMap-Project.yml)\]
Journal of Cell Biology DataViewer - All JCB data was moved to Biostudies \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Journal-of-Cell-Biology-DataViewer.yml)\]
KEGG - KEGG is a database resource for understanding high-level functions and utilities of \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/KEGG.yml)\]
NCBI Proteins \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/NCBI-Proteins.yml)\]
NCBI Taxonomy - The NCBI Taxonomy database is a curated set of names and classifications for \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/NCBI-Taxonomy.yml)\]
NCI Genomic Data Commons - The GDC Data Portal is a robust data-driven platform that allows \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/NCI-Genomic-Data-Commons.yml)\]
NIH Microarray data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/NIH-Microarray-data.yml)\]
OpenSNP genotypes data - openSNP allows customers of direct-to-customer genetic tests to \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/OpenSNP-genotypes-data.yml)\]
Palmer Penguins - The goal of palmerpenguins is to provide a great dataset for data \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Palmer-Penguins.yml)\]
Pathguid - Protein-Protein Interactions Catalog \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Pathguid.yml)\]
Protein Data Bank - This resource is powered by the Protein Data Bank archive-information \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Protein-Data-Bank.yml)\]
Psychiatric Genomics Consortium - The purpose of the Psychiatric Genomics Consortium (PGC) is \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Psychiatric-Genomics-Consortium.yml)\]
PubChem Project - PubChem is the world's largest collection of freely accessible chemical \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/PubChem-Project.yml)\]
PubGene (now Coremine Medical) - COREMINE™ is a family of tools developed by the Norwegian \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/PubGene-now-Coremine-Medical.yml)\]
Sanger Catalogue of Somatic Mutations in Cancer (COSMIC) - COSMIC, the Catalogue Of Somatic \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Sanger-Catalogue-of-Somatic-Mutations-in-Cancer-COSMIC.yml)\]
Sanger Genomics of Drug Sensitivity in Cancer Project (GDSC) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Sanger-Genomics-of-Drug-Sensitivity-in-Cancer-Project-GDSC.yml)\]
Sequence Read Archive(SRA) - The Sequence Read Archive (SRA) stores raw sequence data from \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Sequence-Read-ArchiveSRA.yml)\]
Serratus - Analysis of 7.1 million RNA/DNA sequencing datasets to discover the total \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Serratus-Open-Virome.yml)\]
Stanford Microarray Data (Retired NOW) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Stanford-Microarray-Data.yml)\]
Stowers Institute Original Data Repository \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Stowers-Institute-Original-Data-Repository.yml)\]
Systems Science of Biological Dynamics (SSBD) Database - Systems Science of Biological \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Systems-Science-of-Biological-Dynamics-SSBD-Database.yml)\]
The Cancer Genome Atlas (TCGA), available via Broad GDAC \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/The-Cancer-Genome-Atlas-TCGA-available-via-Broad-GDAC.yml)\]
The Catalogue of Life - The Catalogue of Life is a quality-assured checklist of more than 1.8 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/The-Catalogue-of-Life.yml)\]
The Personal Genome Project - The Personal Genome Project, initiated in 2005, is a vision and \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/The-Personal-Genome-Project.yml)\]
UCSC Public Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/UCSC-Public-Data.yml)\]
UniGene \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/UniGene.yml)\]
Universal Protein Resource (UnitProt) - The Universal Protein Resource (UniProt) is a \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/Universal-Protein-Resource.yml)\]
Rfam - The Rfam database is a collection of RNA families, each represented by multiple \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Biology/rfam.yml)\]

Chemistry

Ionic Liquids Database - ILThermo \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Chemistry/ionicliquids.yml)\]

Climate+Weather

Actuaries Climate Index \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/Actuaries-Climate-Index.yml)\]
Australian Weather - Updated webpage for Australian Weather data. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/Australian-Weather.yml)\]
Aviation Weather Center - Consistent, timely and accurate weather information for the world \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/Aviation-Weather-Center.yml)\]
Brazilian Weather - Historical data (In Portuguese) - Data related to climate and weather \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/Brazilian-Weather.yml)\]
Several Climate Datasets - The C3S Climate Data Store (CDS) is a one-stop shop for \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/CDS.yml)\]
Canadian Meteorological Centre \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/Canadian-Meteorological-Centre.yml)\]
Caravan - a dataset for large-sample hydrology - Caravan is an open community dataset of \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/Caravan.yml)\]
Climate Data from UEA (updated monthly) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/Climate-Data-from-UEA-updated-monthly.yml)\]
Dutch Weather - The KNMI Data Center (KDC) portal provides access to KNMI data on weather, \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/Dutch-Weather.yml)\]
European Climate Assessment & Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/European-Climate-Assessment-&-Dataset.yml)\]
German Climate Data Center \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/German-Meteorological-Service-CDC.yml)\]
Global Climate Data Since 1929 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/Global-Climate-Data-Since-1929.yml)\]
Charting The Global Climate Change News Narrative 2009-2020 - These four datasets represent \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/GlobalClimateChangeNewsNarrative2009-2020.yml)\]
NASA Global Imagery Browse Services \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/NASA-Global-Imagery-Browse-Services.yml)\]
NOAA Bering Sea Climate \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/NOAA-Bering-Sea-Climate.yml)\]
NOAA Climate Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/NOAA-Climate-Datasets.yml)\]
NOAA Realtime Weather Models \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/NOAA-Realtime-Weather-Models.yml)\]
NOAA SURFRAD Meteorology and Radiation Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/NOAA-SURFRAD-Meteorology-and-Radiation-Datasets.yml)\]
Open-Meteo - Open-Source Weather API - Open-source weather API with free access for non- \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/Open-Meteo.yml)\]
The World Bank Open Data Resources for Climate Change \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/The-World-Bank-Open-Data-Resources-for-Climate-Change.yml)\]
UEA Climatic Research Unit \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/UEA-Climatic-Research-Unit.yml)\]
WU Historical Weather Worldwide \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/WU-Historical-Weather-Worldwide.yml)\]
Wahington Post Climate Change - To analyze warming temperatures in the United States, The \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/Washington%20Post%20Climate%20Change.yml)\]
WorldClim - Global Climate Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Climate+Weather/WorldClim.yml)\]

ComplexNetworks

AMiner Citation Network Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/AMiner-Citation-Network-Dataset.yml)\]
CrossRef DOI URLs \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/CrossRef-DOI-URLs.yml)\]
DBLP Citation dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/DBLP-Citation-dataset.yml)\]
DIMACS Road Networks Collection \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/DIMACS-Road-Networks-Collection.yml)\]
NBER Patent Citations \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/NBER-Patent-Citations.yml)\]
NIST complex networks data collection \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/NIST-complex-networks-data-collection.yml)\]
Network Repository with Interactive Exploratory Analysis Tools \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/Network-Repository-with-Interactive-Exploratory-Analysis-Tools.yml)\]
Protein-protein interaction network \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/Protein.yml)\]
PyPI and Maven Dependency Network \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/PyPI-and-Maven-Dependency-Network.yml)\]
Scopus Citation Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/Scopus-Citation-Database.yml)\]
Small Network Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/Small-Network-Data.yml)\]
Stanford GraphBase \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/Stanford-GraphBase-Steven-Skiena.yml)\]
Stanford Large Network Dataset Collection \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/Stanford-Large-Network-Dataset-Collection.yml)\]
Stanford Longitudinal Network Data Sources \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/Stanford-Longitudinal-Network-Data-Sources.yml)\]
The Koblenz Network Collection \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/The-Koblenz-Network-Collection.yml)\]
The Laboratory for Web Algorithmics (UNIMI) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/The-Laboratory-for-Web-Algorithmics-UNIMI.yml)\]
UCI Network Data Repository \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/UCI-Network-Data-Repository.yml)\]
UFL sparse matrix collection \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/UFL-sparse-matrix-collection.yml)\]
WSU Graph Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/WSU-Graph-Database.yml)\]
Community Resource for Archiving Wireless Data At Dartmouth - Contains datasets of pcap files \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComplexNetworks/crawdad.yml)\]

ComputerNetworks

3.5B Web Pages from CommonCrawl 2012 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/3.5B-Web-Pages-from-CommonCrawl-2012.yml)\]
53.5B Web clicks of 100K users in Indiana Univ. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/53.5B-Web-clicks-of-100K-users-in-Indiana-Univ..yml)\]
CAIDA Internet Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/CAIDA-Internet-Datasets.yml)\]
CRAWDAD Wireless datasets from Dartmouth Univ. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/CRAWDAD-Wireless-datasets-from-Dartmouth-Univ..yml)\]
ClueWeb09 - 1B web pages \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/ClueWeb09.yml)\]
ClueWeb12 - 733M web pages \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/ClueWeb12.yml)\]
CommonCrawl Web Data over 7 years \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/CommonCrawl-Web-Data-over-7-years.yml)\]
Shopper Intent Prediction from Clickstream E‑Commerce Data with Minimal Browsing Information \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/Coveo-Shopper-Intent-Prediction.yaml)\]
Criteo click-through data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/Criteo-click-through-data.yml)\]
Internet-Wide Scan Data Repository \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/Internet-Wide-Scan-Data-Repository.yml)\]
MIRAGE-2019 - MIRAGE-2019 is a human-generated dataset for mobile traffic analysis with \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/MIRAGE-2019.yml)\]
Merklemap DNS records Dataset - Contains 4B+ DNS records accross 700 million unique \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/Merklemap-DNS-Records-dataset.yml)\]
OONI: Open Observatory of Network Interference - Internet censorship data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/OONI-Open-Observatory-of-Network-Interference.yml)\]
Open Mobile Data by MobiPerf \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/Open-Mobile-Data-by-MobiPerf.yml)\]
The Peer-to-Peer Trace Archive - Real-world measurements play a key role in studying the \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/P2P-Trace-Archive.yml)\]
Rapid7 Sonar Internet Scans \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/Rapid7-Sonar-Internet-Scans.yml)\]
UCSD Network Telescope, IPv4 /8 net \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ComputerNetworks/UCSD-Network-Telescope-IPv4-slash8-net.yml)\]

CyberSecurity

CCCS-CIC-AndMal-2020 - The dataset includes 200K benign and 200K malware samples totalling to \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//CyberSecurity/CCCS-CIC-AndMal-2020.yml)\]
Traffic and Log Data Captured During a Cyber Defense Exercise - This dataset was acquired \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//CyberSecurity/Traffic-and-Log-Data-Captured-During-a-Cyber-Defense-Exercise.yml)\]

DataChallenges

AIcrowd Competitions \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/AIcrowd-Competitions.yml)\]
Bruteforce Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/Bruteforce-Database.yml)\]
Challenges in Machine Learning \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/Challenges-in-Machine-Learning.yml)\]
CrowdANALYTIX dataX \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/CrowdANALYTIX-dataX.yml)\]
D4D Challenge of Orange \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/D4D-Challenge-of-Orange.yml)\]
DrivenData Competitions for Social Good \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/DrivenData-Competitions-for-Social-Good.yml)\]
ICWSM Data Challenge (since 2009) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/ICWSM-Data-Challenge-since-2009.yml)\]
KDD Cup by Tencent 2012 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/KDD-Cup-by-Tencent-2012.yml)\]
Kaggle Competition Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/Kaggle-Competition-Data.yml)\]
Localytics Data Visualization Challenge \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/Localytics-Data-Visualization-Challenge.yml)\]
Netflix Prize \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/Netflix-Prize.yml)\]
Space Apps Challenge \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/Space-Apps-Challenge.yml)\]
Telecom Italia Big Data Challenge \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/Telecom-Italia-Big-Data-Challenge.yml)\]
TravisTorrent Dataset - MSR'2017 Mining Challenge \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/TravisTorrent-Dataset.yml)\]
TunedIT - Data mining & machine learning data sets, algorithms, challenges \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/TunedIT.yml)\]
Yelp Dataset Challenge - The Yelp dataset is a subset of our businesses, reviews, and user \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//DataChallenges/Yelp-Dataset-Challenge.yml)\]

EarthScience

38-Cloud (Cloud Detection) - Contains 38 Landsat 8 scene images and their manually extracted \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/38-Cloud.yml)\]
AQUASTAT - Global water resources and uses \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/AQUASTAT.yml)\]
BODC - marine data of ~22K vars \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/BODC.yml)\]
EOSDIS - NASA's earth observing system data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/EOSDIS.yml)\]
Earth Models \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/Earth-Models.yml)\]
Global Wind Atlas - The Global Wind Atlas is a free, web-based application developed to help \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/Global-Wind-Atlas.yml)\]
Integrated Marine Observing System (IMOS) - roughly 30TB of ocean measurements \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/Integrated-Marine-Observing-System-IMOS.yml)\]
Marinexplore - Open Oceanographic Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/Marinexplore.yml)\]
Alabama Real-Time Coastal Observing System \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/MyMobileBay.yml)\]
National Estuarine Research Reserves System-Wide Monitoring Program - long-term estuarine \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/NERRS-SWMP.yml)\]
Oil and Gas Authority Open Data - The dataset covers 12,500 offshore wellbores, 5,000 seismic \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/Oil-and-Gas-Authority-UK.yml)\]
Radiance GeoJSON — Global Light Pollution - Global nighttime light pollution dataset derived \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/Radiance-GeoJSON-Light-Pollution.yml)\]
Smithsonian Institution Global Volcano and Eruption Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/Smithsonian-Institution-Global-Volcano-and-Eruption-Database.yml)\]
USGS Earthquake Archives \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/USGS-Earthquake-Archives.yml)\]
Wellhead Protection Area (protection zone) prediction using breakthrough curves - This \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//EarthScience/WHPA.yml)\]

Economics

Asian Productivity Organization (APO) - The AEPM provides a graphic dashboard view of \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/APO.yml)\]
ASEAN Stats - The ASEANstatsDataPortal was first launched in June 2018. The Portal is \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/ASEAN%20Stats.yml)\]
American Economic Association (AEA) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/American-Economic-Association-AEA.yml)\]
Asian KLEMS - Asia KLEMS is an Asian regional research consortium to promote building \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Asian%20KLEMS.yml)\]
Harvard Atlas of Economic Complexity - A database for people to explore global trade flows \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Atlas%20Economic%20Complexity.yml)\]
BIS Financial Database - The files contain the same data as in the BIS Statistics Explorer \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/BIS%20Financial%20Database.yml)\]
Barro-Lee Education Attainment - Barro-Lee Educational Attainment Data from 1950 to 2010. \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Barro%20Lee.yml)\]
CEPII Database - A database of the world economy, through its country and region profiles, in \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/CEPII%20Database.yml)\]
EUKLEMS - EU KLEMS is an industry level, growth and productivity research project. EU KLEMS \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/EUKLEMS.yml)\]
Economic Freedom of the World Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Economic-Freedom-of-the-World-Data.yml)\]
Historical National Accounts - The datahub on Comparative Historical National Accounts \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Historical%20National%20Accounts.yml)\]
Historical MacroEconomic Statistics \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Historical-MacroEconomic-Statistics.yml)\]
INFORUM - Interindustry Forecasting at the University of Maryland \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/INFORUM.yml)\]
DBnomics – the world's economic database - Aggregates hundreds of millions of time series \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/International-Economics-Database.yml)\]
International Trade Statistics - The new link contains trade based on filtered search on the \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/International-Trade-Statistics.yml)\]
Internet Product Code Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Internet-Product-Code-Database.yml)\]
Joint External Debt Data Hub \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Joint-External-Debt-Data-Hub.yml)\]
Jon Haveman International Trade Data Links \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Jon-Haveman-International-Trade-Data-Links.yml)\]
Latin America KLEMS - LAKLEMS is a technical cooperation project financed by the Inter- \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/LA%20KLEMS.yml)\]
Long-Term Productivity Database - The Long-Term Productivity database was created as a \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Long-Term-Productivity-Database.yml)\]
Maddison Project Database - The Maddison Project Database provides information on comparative \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Maddison%20Project.yml)\]
National Transfer Accounts - The goal of the National Transfer Accounts (NTA) project is to \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/NTA.yml)\]
OpenCorporates Database of Companies in the World \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/OpenCorporates-Database-of-Companies-in-the-World.yml)\]
Our World in Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Our-World-in-Data.yml)\]
Penn World Table - PWT version 10.0 is a database with information on relative levels of \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/Penn%20World%20Table.yml)\]
SciencesPo World Trade Gravity Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/SciencesPo-World-Trade-Gravity-Datasets.yml)\]
The Atlas of Economic Complexity \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/The-Atlas-of-Economic-Complexity.yml)\]
The Center for International Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/The-Center-for-International-Data.yml)\]
The Observatory of Economic Complexity \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/The-Observatory-of-Economic-Complexity.yml)\]
UN Commodity Trade Statistics \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/UN-Commodity-Trade-Statistics.yml)\]
UN Human Development Reports \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/UN-Human-Development-Reports.yml)\]
World Input-Output Database - World Input-Output Tables and underlying data, covering 43 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/World%20Input-Output%20Database.yml)\]
World KLEMS - Analytical KLEMS-type data sets for a broad set of countries around the world. \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Economics/World%20KLEMS.yml)\]

Education

College Scorecard Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Education/College-Scorecard-Data.yml)\]
New York State Education Department Data - The New York State Education Department (NYSED) is \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Education/New-York-State-Education-Department.yml)\]
Program for International Student Assessement (PISA) - Contains 15-year-old students' \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Education/PISA.yml)\]
Student Data from Free Code Camp \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Education/Student-Data-from-Free-Code-Camp.yml)\]

Energy

AMPds - The Almanac of Minutely Power dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/AMPds.yml)\]
BLUEd - Building-Level fUlly labeled Electricity Disaggregation dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/BLUEd.yml)\]
COMBED \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/COMBED.yml)\]
DBFC - Direct Borohydride Fuel Cell (DBFC) Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/DBFC.yml)\]
DEL - Domestic Electrical Load study datsets for South Africa (1994 - 2014) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/DEL.yml)\]
ECO - The ECO data set is a comprehensive data set for non-intrusive load monitoring and \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/ECO.yml)\]
EIA \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/EIA.yml)\]
Global Power Plant Database - The Global Power Plant Database is a comprehensive, open source \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/Global%20Power%20Plant%20Database.yml)\]
HES - Household Electricity Study, UK \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/HES.yml)\]
HFED \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/HFED.yml)\]
MORED: a Moroccan Buildings’ Electricity Consumption Dataset - Since spring of 2019, a data \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/MORED.yml)\]
Marktstammdatenregister - The German Marktstammdatenregister (MaStR) is a database of all \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/MaStR.yml)\]
PEM1 - Proton Exchange Membrane (PEM) Fuel Cell Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/PEM1.yml)\]
PLAID - The Plug Load Appliance Identification Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/PLAID.yml)\]
The Public Utility Data Liberation Project (PUDL) - PUDL makes US energy data easier to \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/PUDL.yml)\]
REDD \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/REDD.yml)\]
SYND - A synthetic energy dataset for non-intrusive load monitoring - With SynD, we present a \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/SYND.yml)\]
Smart Meter Data Portal - The Smart Meter Data Portal is part of the National Science \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/Smart%20Meter%20Data%20Portal.yml)\]
Tracebase \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/Tracebase.yml)\]
Ukraine Energy Centre Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/UDEC.yml)\]
UK-DALE - UK Domestic Appliance-Level Electricity \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/UK-DALE.yml)\]
WHITED \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/WHITED.yml)\]
iAWE \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Energy/iAWE.yml)\]

Entertainment

Top Streamers on Twitch - This contains data of Top 1000 Streamers from past year. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Entertainment/TwitchStreamersData.yml)\]

Finance

BIS Statistics - BIS statistics, compiled in cooperation with central banks and other \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/BIS%20Statistics.yml)\]
Blockmodo Coin Registry - A registry of JSON formatted information files that is primarily \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/Blockmodo-Coin-Registry)\]
CBOE Futures Exchange \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/CBOE-Futures-Exchange.yml)\]
Complete FAANG Stock data - This data set contains all the stock data of FAANG companies from \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/FAANG-StockData.yml)\]
Google Finance \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/Google-Finance.yml)\]
Google Trends \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/Google-Trends.yml)\]
NASDAQ \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/NASDAQ.yml)\]
NYSE Market Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/NYSE-Market-Data.yml)\]
OANDA \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/OANDA.yml)\]
OSU Financial data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/OSU-Financial-data.yml)\]
Quandl \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/Quandl.yml)\]
SEC EDGAR - EDGAR, the Electronic Data Gathering, Analysis, and Retrieval system, is the \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/SEC-EDGAR.yml)\]
St Louis Federal \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/St-Louis-Federal.yml)\]
Yahoo Finance \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Finance/Yahoo-Finance.yml)\]

GIS

Awesome 3D Semantic City Models - Collection of open 3D semantic city and region models. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/3D-Semantic-City-Models.yml)\]
ArcGIS Open Data portal \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/ArcGIS-Open-Data-portal.yml)\]
Cambridge, MA, US, GIS data on GitHub \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Cambridge-MA-US-GIS-data-on-GitHub.yml)\]
Database of all continents, countries, States/Subdivisions/Provinces and Cities - Database \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Database-of-Continents-Coutries-States-Cities.yml)\]
Factual Global Location Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Factual-Global-Location-Data.yml)\]
IEEE Geoscience and Remote Sensing Society DASE Website \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/GRSS-DASE-Website.yml)\]
Geo Maps - High Quality GeoJSON maps programmatically generated \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Geo-Maps.yml)\]
Geo Spatial Data from ASU \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Geo-Spatial-Data-from-ASU.yml)\]
Geo Wiki Project - Citizen-driven Environmental Monitoring \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Geo-Wiki-Project.yml)\]
GeoFabrik - OSM data extracted to a variety of formats and areas \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/GeoFabrik.yml)\]
GeoNames Worldwide \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/GeoNames-Worldwide.yml)\]
Global Administrative Areas Database (GADM) - Geospatial data organized by country. Includes \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Global-Administrative-Areas-Database-GADM.yml)\]
Homeland Infrastructure Foundation-Level Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Homeland-Infrastructure-Foundation.yml)\]
Landsat 8 on AWS \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Landsat-8-on-AWS.yml)\]
List of all countries in all languages \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/List-of-all-countries-in-all-languages.yml)\]
National Weather Service GIS Data Portal \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/National-Weather-Service-GIS-Data-Portal.yml)\]
Natural Earth - vectors and rasters of the world \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Natural-Earth.yml)\]
OpenAddresses \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/OpenAddresses.yml)\]
OpenStreetMap (OSM) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/OpenStreetMap-OSM.yml)\]
Pleiades - Gazetteer and graph of ancient places \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Pleiades.yml)\]
Reverse Geocoder using OSM data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Reverse-Geocoder-using-OSM-data.yml)\]
Robin Wilson - Free GIS Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Robin-Wilson-Free-GIS-Datasets.yml)\]
Shadow Accrual Maps - The repository contains the accumulated shadow information for New York \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/Shadow-Accrual-Maps.yml)\]
TIGER/Line - U.S. boundaries and roads \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/TIGER-Line.yml)\]
TZ Timezones shapefile \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/TZ-Timezones-shapfiles.yml)\]
TwoFishes - Foursquare's coarse geocoder \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/TwoFishes.yml)\]
UN Environmental Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/UN-Environmental-Data.yml)\]
World boundaries from the U.S. Department of State \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/World-boundaries-from--the-U.S.-Department-of-State.yml)\]
World countries in multiple formats \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/World-countries-in-multiple-formats.yml)\]
MAP-VERSE - MAP usability - Validated Empirical Research by Systematic Evaluation - A curated \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//GIS/map-verse.yml)\]

Government

Alberta, Province of Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Alberta-Province-of-Canada.yml)\]
Antwerp, Belgium \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Antwerp-Belgium.yml)\]
Argentina (non official) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Argentina-non-official.yml)\]
Datos Argentina - Portal de datos abiertos de la República Argentina. Encontrá datos públicos \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Argentina.yml)\]
Austin, TX, US \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Austin-TX-US.yml)\]
Australia (abs.gov.au) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Australia-abs.gov.au.yml)\]
Australia (data.gov.au) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Australia-data.gov.au.yml)\]
Austria (data.gv.at) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Austria-data.gv.at.yml)\]
Baton Rouge, LA, US \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Baton-Rouge-LA-US.yml)\]
Beersheba, Israel - Open Data Portal (Smart7 OpenData) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Beersheba-Israel.yml)\]
Belgium \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Belgium.yml)\]
City of Berkeley Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Berkeley-CA-Open-Data.yml)\]
Brazil \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Brazil.yml)\]
Buenos Aires, Argentina \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Buenos-Aires-Argentina.yml)\]
Calgary, AB, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Calgary-AB-Canada.yml)\]
Cambridge, MA, US \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Cambridge-MA-US.yml)\]
Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Canada.yml)\]
Chicago \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Chicago.yml)\]
Chile \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Chile.yml)\]
China \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/China)\]
Dallas Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Dallas-Open-Data.yml)\]
DataBC - data from the Province of British Columbia \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/DataBC.yml)\]
Debt to the Penny - The Debt to the Penny dataset provides information about the total \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Debt-to-penny.yml)\]
Denver Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Denver-Open-Data.yml)\]
Durham, NC Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Durham-NC-Open-Data.yml)\]
Edmonton, AB, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Edmonton-AB-Canada.yml)\]
England LGInform \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/England-LGInform.yml)\]
EuroStat \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/EuroStat.yml)\]
EveryPolitician - Ongoing project collating and sharing data on every politician. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/EveryPolitician.yml)\]
Federal Committee on Statistical Methodology (FCSM) (formerly FedStats) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/FedStats.yml)\]
Finland \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Finland.yml)\]
France \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/France.yml)\]
Fredericton, NB, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Fredericton-NB-Canada.yml)\]
Gatineau, QC, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Gatineau-QC-Canada.yml)\]
Germany \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Germany.yml)\]
Ghent, Belgium \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Ghent-Belgium.yml)\]
Glasgow, Scotland, UK \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Glasgow-Scotland-UK.yml)\]
Greece \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Greece.yml)\]
Guardian world governments \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Guardian-world-governments.yml)\]
Halifax, NS, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Halifax-NS-Canada.yml)\]
Helsinki Region, Finland \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Helsinki-Region-Finland.yml)\]
Hong Kong, China \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Hong-Kong-China.yml)\]
Houston, TX, US \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Houston-TX-US.yml)\]
Indian Government Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Indian-Government-Data.yml)\]
Indonesian Data Portal \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Indonesian-Data-Portal.yml)\]
Iowa - Welcome to the State of Iowa's data portal. Please explore data about Iowa and your \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Iowa.yml)\]
Ireland's Open Data Portal \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Irelands-Open-Data-Portal.yml)\]
Israel's Open Data Portal \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Israel.yml)\]
Istanbul Municipality Open Data Portal \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Istanbul-Municipality-Open-Data.yml)\]
Italy - Il Portale dati.gov.it è il catalogo nazionale dei metadati relativi ai dati \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Italy.yml)\]
Jail deaths in America - The U.S. government does not release jail by jail mortality data, \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Jail-deaths-in-America.yml)\]
Japan \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Japan.yml)\]
Laval, QC, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Laval-QC-Canada.yml)\]
Lexington, KY \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Lexington-KY.yml)\]
London Datastore, UK \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/London-Datastore-UK.yml)\]
London, ON, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/London-ON-Canada.yml)\]
Los Angeles Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Los-Angeles-Open-Data.yml)\]
Luxembourg - Luxembourgish Open Data Portal \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Luxembourg.yml)\]
Malaysia \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Malaysia.yml)\]
MassGIS, Massachusetts, U.S. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/MassGIS-Massachusetts-U.S..yml)\]
Metropolitan Transportation Commission (MTC), California, US \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Metropolitain-Transportation-Commission-MTC-California-US.yml)\]
Mexico \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Mexico.yml)\]
Mississauga, ON, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Missisauga-ON-Canada.yml)\]
Moldova \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Moldova.yml)\]
Moncton, NB, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Moncton-NB-Canada.yml)\]
Montreal, QC, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Montreal-QC-Canada.yml)\]
Mountain View, California, US (GIS) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Mountain-View-California-US-GIS.yml)\]
NYC Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/NYC-Open-Data.yml)\]
NYC betanyc \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/NYC-betanyc.yml)\]
Netherlands \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Netherlands.yml)\]
New York Department of Sanitation Monthly Tonnage - DSNY Monthly Tonnage Data provides \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/New-York-Department-of-Sanitation.yml)\]
New Zealand \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/New-Zealand.yml)\]
OECD \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/OECD.yml)\]
Oakland, California, US \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Oakland-California-US.yml)\]
Oklahoma \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Oklahoma.yml)\]
Open Data for Africa \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Open-Data-for-Africa.yml)\]
Open Government Data (OGD) Platform India \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Open-Government-Data-OGD-Platform-India.yml)\]
OpenDataSoft's list of 1,600 open data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/OpenDataSofts-list-of-1600-open-data.yml)\]
Oregon \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Oregon.yml)\]
Ottawa, ON, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Ottawa-ON-Canada.yml)\]
Palo Alto, California, US \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Palo-Alto-California-US.yml)\]
OpenDataPhilly - OpenDataPhilly is a catalog of open data in the Philadelphia region. In \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Philadelphia-Open-Data.yml)\]
Portland, Oregon \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Portland-Oregon.yml)\]
Portugal - Pordata organization \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Portugal.yml)\]
Puerto Rico Government \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Puerto-Rico-Government.yml)\]
Quebec City, QC, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Quebec-City-QC-Canada.yml)\]
Quebec Province of Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Quebec-Province-of-Canada.yml)\]
Regina SK, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Regina-SK-Canada.yml)\]
Rio de Janeiro, Brazil \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Rio-de-Janeiro-Brazil.yml)\]
Romania \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Romania.yml)\]
Russia \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Russia.yml)\]
San Diego, CA \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/San%20Diego,%20CA.yml)\]
San Antonio, TX - Community Information Now - CI:Now is a nonprofit serving Bexar (San \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/San-Antonio-TX-US-Community-Information-Now.yml)\]
San Francisco Data sets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/San-Francisco-Data-sets.yml)\]
San Jose, California, US \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/San-Jose-California-US.yml)\]
San Mateo County, California, US \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/San-Mateo-County-California-US.yml)\]
Saskatchewan, Province of Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Saskatchewan-Province-of-Canada.yml)\]
Seattle \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Seattle.yml)\]
Singapore Government Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Singapore-Government-Data.yml)\]
South Africa Trade Statistics \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/South-Africa-Trade-Statistics.yml)\]
South Africa \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/South-Africa.yml)\]
State of Utah, US \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/State-of-Utah-US.yml)\]
Switzerland \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Switzerland.yml)\]
Taiwan gov \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Taiwan-g0v.yml)\]
Taiwan \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Taiwan.yml)\]
Tel-Aviv Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Tel-Aviv.yml)\]
Texas Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Texas-Open-Data.yml)\]
The World Bank \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/The-World-Bank.yml)\]
Toronto, ON, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Toronto-ON-Canada.yml)\]
Tunisia \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Tunisia.yml)\]
U.K. Government Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/U.K.-Government-Data.yml)\]
U.S. American Community Survey \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/U.S.-American-Community-Survey.yml)\]
U.S. CDC Public Health datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/U.S.-CDC-Public-Health-datasets.yml)\]
U.S. Census Bureau \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/U.S.-Census-Bureau.yml)\]
U.S. Department of Housing and Urban Development (HUD) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/U.S.-Department-of-Housing-and-Urban-Development-HUD.yml)\]
U.S. Federal Government Agencies \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/U.S.-Federal-Government-Agencies.yml)\]
U.S. Federal Government Data Catalog \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/U.S.-Federal-Government-Data-Catalog.yml)\]
U.S. Food and Drug Administration (FDA) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/U.S.-Food-and-Drug-Administration-FDA.yml)\]
U.S. National Center for Education Statistics (NCES) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/U.S.-National-Center-for-Education-Statistics-NCES.yml)\]
U.S. Open Government \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/U.S.-Open-Government.yml)\]
UK 2011 Census Open Atlas Project \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/UK-2011-Census-Open-Atlas-Project.yml)\]
UNESCO Data Hub - UNESCO's official data catalog providing authoritative global statistics \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/UNESCO-Data-Hub.yml)\]
US Counties - This is a repository of various data, broken down by US county. While most of \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/US-Counties.yml)\]
U.S. Patent and Trademark Office (USPTO) Bulk Data Products \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/USPTO-Bulk-Data-Products.yml)\]
Uganda Bureau of Statistics \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Uganda-Bureau-of-Statistics.yml)\]
Ukraine \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Ukraine.yml)\]
United Nations \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/United-Nations.yml)\]
Uruguay \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Uruguay.yml)\]
Valley Transportation Authority (VTA), California, US \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Valley-Transportation-Authority-VTA-California-US.yml)\]
Vancouver, BC Open Data Catalog \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Vancouver-BC-Open-Data-Catalog.yml)\]
Victoria, BC, Canada \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Victoria-BC-Canada.yml)\]
Vienna, Austria \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Vienna-Austria.yml)\]
Statistics from the General Statistics Office of Vietnam - Data in different categories are \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/Vietnam.yml)\]
U.S. Congressional Research Service (CRS) Reports \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Government/everycrsreport.yml)\]

Healthcare

AWS COVID-19 Datasets - We're working with organizations who make COVID-19-related data \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Aws-COVID-19.yml)\]
COVID-19 Case Surveillance Public Use Data - The COVID-19 case surveillance system database \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/COVID-19-Case-Surveillance-Public-Use-Data.yml)\]
Covid-19 non-processed data of Ecuador - It's a project which provides non-processed datasets \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/COVID-19-Ecuador-Data.yml)\]
2019 Novel Coronavirus COVID-19 Data Repository by Johns Hopkins CSSE - This is the data \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/COVID-19-Johns-Hopkins.yml)\]
Coronavirus (Covid-19) Data in the United States - The New York Times is releasing a series \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/COVID-19-New-York-Times.yml)\]
COVID-19 Reported Patient Impact and Hospital Capacity by Facility - The following dataset \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/COVID-19-Reported-Patient-Impact-and-Hospital-Capacity-by-Facility.yml)\]
Composition of Foods Raw, Processed, Prepared USDA National Nutrient Database for Standard \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Composition-of-Foods-Raw-Processed-Prepared-USDA-National-Nutrient-Database-for-Standard-Reference.yml)\]
The COVID Tracking Project - The COVID Tracking Project collects and publishes the most \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Covid-Tracking-Project.yml)\]
EHDP Large Health Data Sets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/EHDP-Large-Health-Data-Sets.yml)\]
GDC - GDC supports several cancer genome programs for CCG, TCGA, TARGET etc. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/GDC.yml)\]
Gapminder World demographic databases \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Gapminder-World-demographic-databases.yml)\]
MeSH, the vocabulary thesaurus used for indexing articles for PubMed \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/MeSH-the-vocabulary-thesaurus-used-for-indexing-articles-for-PubMed.yml)\]
MeDAL - A large medical text dataset curated for abbreviation disambiguation - Medical \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Medal-medical-abbreviations.yml)\]
Medicare Coverage Database (MCD), U.S. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Medicare-Coverage-Database-MCD-U.S..yml)\]
Medicare Data Engine of medicare.gov Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Medicare-Data-Engine-of-medicare.gov-Data.yml)\]
Medicare Data File \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Medicare-Data-File.yml)\]
Nightingale Open Science \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Nightingale.yml)\]
Number of Ebola Cases and Deaths in Affected Countries (2014) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Number-of-Ebola-Cases-and-Deaths-in-Affected-Countries-2014.yml)\]
Open-ODS (structure of the UK NHS) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Open-ODS.yml)\]
OpenPaymentsData, Healthcare financial relationship data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/OpenPaymentsData-Healthcare-financial-relationship-data.yml)\]
PhysioBank Databases - A large and growing archive of physiological data. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/PhysioBank-Databases.yml)\]
Spanish Flu Dataset - Historical dataset about the 1918–1920 Spanish Flu pandemic, including \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Spanish-Flu.yml)\]
The Cancer Imaging Archive (TCIA) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/TCIA.yml)\]
The Cancer Genome Atlas project (TCGA) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/The-Cancer-Genome-Atlas-project-TCGA.yml)\]
World Health Organization Global Health Observatory \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/World-Health-Organization-Global-Health-Observatory.yml)\]
Yahoo Knowledge Graph COVID-19 Datasets - The Yahoo Knowledge Graph team at Verizon Media is \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/Yahoo-COVID-19.yml)\]
Informatics for Integrating Biology and the Bedside \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Healthcare/i2b2.yml)\]

ImageProcessing

10k US Adult Faces Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/10k-US-Adult-Faces-Database.yml)\]
2GB of Photos of Cats \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/2GB-of-Photos-of-Cats.yml)\]
Audience Unfiltered faces for gender and age classification \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Adience-Unfiltered-faces-for-gender-and-age-classification.yml)\]
Affective Image Classification \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Affective-Image-Classification.yml)\]
Airborne Object Detection and Tracking - The Airborne Object Tracking (AOT) dataset is a \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Airborne-Object-Detection-and-Tracking.yml)\]
Animals with attributes \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Animals-with-attributes.yml)\]
CADDY Underwater Stereo-Vision Dataset of divers' hand gestures - Contains 10K stereo pair \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/CADDY-Underwater-Stereo-Vision-Dataset-of-hand-gestures.yml)\]
Cytology Dataset – CCAgT: Images of Cervical Cells with AgNOR Stain Technique - Contains 9339 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/CCAgT.yml)\]
Caltech Pedestrian Detection Benchmark \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Caltech-Pedestrian-Detection-Benchmark.yml)\]
Chars74K dataset - Character Recognition in Natural Images (both English and Kannada are available) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Chars74K-dataset.yml)\]
Cube++ - 4890 raw 18-megapixel images, each containing a SpyderCube color target in their \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Cube-Plus-Plus.yml)\]
Densely Annotated Video Driving Data Set - This data set consists of 28 video sequences of \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/DAVID.yml)\]
Danbooru Tagged Anime Illustration Dataset - A large-scale anime image database with 3.33m+ \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Danbooru-Tagged-Anime-Illustration-Dataset.yml)\]
DukeMTMC Data Set - DukeMTMC aims to accelerate advances in multi-target multi-camera \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/DukeMTMC-Data-Set.yml)\]
ETH Entomological Collection (ETHEC) Fine Grained Butterfly (Lepidoptra) Images \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/ETH_Entomological_Collection_Fine_Grained_Butterfly_Images.yml)\]
Face Recognition Benchmark \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Face-Recognition-Benchmark.yml)\]
Flickr: 32 Class Brand Logos \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Flickr-32-Class-Brand-Logos.yml)\]
GDXray - X-ray images for X-ray testing and Computer Vision \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/GDXray.yml)\]
HumanEva Dataset - The HumanEva-I dataset contains 7 calibrated video sequences (4 grayscale \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/HumanEva-Dataset.yml)\]
ImageNet (in WordNet hierarchy) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/ImageNet.yml)\]
Indoor Scene Recognition \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Indoor-Scene-Recognition.yml)\]
International Affective Picture System, UFL \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/International-Affective-Picture-System-UFL.yml)\]
KITTI Vision Benchmark Suite \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/KITTI-Vision-Benchmark-Suite.yml)\]
Labeled Information Library of Alexandria - Biology and Conservation - Contains over 10 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/LILA-BC.yml)\]
Long duration stitched and unstitched 8K/30 fps stereoscopic 360° videos - This 360° video \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Long-duration-stitched-and-unstitched-8K-30-fps-stereoscopic-360deg-videos.yml)\]
MNIST database of handwritten digits, near 1 million examples \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/MNIST-database-of-handwritten-digits-near-1-million-examples.yml)\]
Multi-View Region of Interest Prediction Dataset for Autonomous Driving - Contains 16 driving \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/MV-ROI.yml)\]
Massive Visual Memory Stimuli, MIT \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Massive-Visual-Memory-Stimuli-MIT.yml)\]
Newspaper Navigator - This dataset consists of extracted visual content for 16,358,041 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Newspaper-Navigator.yml)\]
Open Images From Google - Pictures with segmentation masks for 2.8 million object instances \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/OpenImagesByGoogle.yml)\]
RuFa - Contains images of text written in one of two Arabic fonts (Ruqaa and Nastaliq \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/RuFa-Arabic-font-dataset.yml)\]
SUN database, MIT \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/SUN-database-MIT.yml)\]
SVIRO Synthetic Vehicle Interior Rear Seat Occupancy - 25.000 synthetic scenery's across ten \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/SVIRO.yml)\]
Several Shape-from-Silhouette Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Several-Shape-from-Silhouette-Datasets.yml)\]
Stanford Dogs Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Stanford-Dogs-Dataset.yml)\]
The Action Similarity Labeling (ASLAN) Challenge \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/The-Action-Similarity-Labeling-ASLAN-Challenge.yml)\]
The Oxford-IIIT Pet Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/The-Oxford-IIIT-Pet-Dataset.yml)\]
Violent-Flows - Crowd Violence / Non-violence Database and benchmark \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Violent-Flows.yml)\]
Visual genome \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/Visual-genome.yml)\]
YouTube Faces Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ImageProcessing/YouTube-Faces-Database.yml)\]

MachineLearning

All-Age-Faces Dataset - Contains 13'322 Asian face images distributed across all ages (from 2 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/All-Age-Faces-Dataset.yml)\]
Audi Autonomous Driving Dataset - We have published the Audi Autonomous Driving Dataset \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Audi-Autonomous-Driving-Dataset.yml)\]
B3FD - Facial age (and gender) estimation dataset with 375k images - The B3FD dataset is a \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Biometrically-Filtered-Famous-Figure-Dataset-for-Age-Estimation.yml)\]
Context-aware data sets from five domains \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Context-aware-datasets-from-five-domains.yml)\]
Delve Datasets for classification and regression \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Delve-Datasets-for-classification-and-regression.yml)\]
Discogs Monthly Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Discogs-Monthly-Data.yml)\]
Fluorescent Neuronal Cells - By releasing this dataset, we aim at providing a new testbed for \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Fluorescent-Neuronal-Cells.yml)\]
Free Music Archive \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Free-Music-Archive.yml)\]
IMDb Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/IMDb-Database.yml)\]
Iranis - A Large-scale Dataset of Farsi/Arabic License Plate Characters \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Iranis.yml)\]
Keel Repository for classification, regression and time series \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Keel-Repository-for-classification-regression-and-time-series.yml)\]
LLVIP - This dataset contains 30976 images, or 15488 pairs, most of which were taken at very \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/LLVIP.yml)\]
Labeled Faces in the Wild (LFW) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Labeled-Faces-in-the-Wild-LFW.yml)\]
Lending Club Loan Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Lending-Club-Loan-Data.yml)\]
Machine Learning Data Set Repository \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Machine-Learning-Data-Set-Repository.yml)\]
Million Song Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Million-Song-Dataset.yml)\]
More Song Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/More-Song-Datasets.yml)\]
MovieLens Data Sets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/MovieLens-Data-Sets.yml)\]
New Yorker caption contest ratings \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/New-Yorker-caption-contest-ratings.yml)\]
RDataMining - "R and Data Mining" ebook data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/RDataMining.yml)\]
Registered Meteorites on Earth \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Registered-Meteorites-on-Earth.yml)\]
Restaurants Health Score Data in San Francisco \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Restaurants-Health-Score-Data-in-San-Francisco.yml)\]
TikTok Dataset - More than 300 dance videos that capture a single person performing dance \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Tik-Tok-Dataset.yml)\]
UCI Machine Learning Repository \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/UCI-Machine-Learning-Repository.yml)\]
Yambda-5B — A Large-Scale Multi-modal Dataset for Ranking And Retrieval - Industrial-scale \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/YaMBDa-5B-Music-Interaction-Dataset.yml)\]
Yahoo! Ratings and Classification Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Yahoo-Ratings-and-Classification-Data.yml)\]
YouTube-BoundingBoxes \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/YouTube-BoundingBoxes.yml)\]
Youtube 8m \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/Youtube-8m.yml)\]
eBay Online Auctions (2012) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//MachineLearning/eBay-Online-Auctions-2012.yml)\]

Museums

Canada Science and Technology Museums Corporation's Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Museums/Canada-Science-and-Technology-Museums-Corporations-Open-Data.yml)\]
Cooper-Hewitt's Collection Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Museums/Cooper-Hewitt-Collection-Database.yml)\]
Metropolitan Museum of Art Collection API \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Museums/Metropolitan-Museum-of-Art-Collection-API.yml)\]
Minneapolis Institute of Arts metadata \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Museums/Minneapolis-Institute-of-Arts-metadata.yml)\]
Natural History Museum (London) Data Portal \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Museums/Natural-History-Museum-London-Data-Portal.yml)\]
Rijksmuseum Historical Art Collection \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Museums/Rijksmuseum-Historical-Art-Collection.yml)\]
Tate Collection metadata \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Museums/Tate-Collection-metadata.yml)\]
The Getty vocabularies \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Museums/The-Getty-vocabularies.yml)\]

NaturalLanguage

Automatic Keyphrase Extraction \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Automatic-Keyphrase-Extraction.yml)\]
The Big Bad NLP Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/BigBadNLPDatabase.yml)\]
Blizzard Challenge Speech - The speech + text data comes from professional audiobooks \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Blizzard-Speech.yml)\]
Blogger Corpus \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Blogger-Corpus.yml)\]
CLiPS Stylometry Investigation Corpus \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/CLiPS-Stylometry-Investigation-Corpus.yml)\]
ClueWeb09 FACC \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/ClueWeb09-FACC.yml)\]
ClueWeb12 FACC \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/ClueWeb12-FACC.yml)\]
DBpedia - Structured data from Wikipedia \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/DBpedia.yml)\]
Dirty Words - With millions of images in our library and billions of user-submitted keywords, \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Dirty-Words.yml)\]
Flickr Personal Taxonomies \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Flickr-Personal-Taxonomies.yml)\]
Freebase of people, places, and things \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Freebase-of-people-places-and-things.yml)\]
German Political Speeches Corpus - Collection of political speeches from the German \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/German-Political-Speeches-Corpus.yml)\]
Google Books Ngrams (2.2TB) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Google-Books-Ngrams-2.2TB.yml)\]
Google MC-AFP - Generated based on the public available Gigaword dataset using Paragraph Vectors \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Google-MC-AFP.yml)\]
Google Web 5gram (1TB, 2006) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Google-Web-5gram-1TB-2006.yml)\]
Gutenberg eBooks List \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Gutenberg-eBooks-List.yml)\]
Hansards text chunks of Canadian Parliament \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Hansards-text-chunks-of-Canadian-Parliament.yml)\]
LJ Speech - Speech dataset consisting of 13,100 short audio clips of a single speaker reading \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/LJ-Speech.yml)\]
M-AILabs Speech - The M-AILABS Speech Dataset is the first large dataset that we are \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/M-AILABS-Speech.yml)\]
Microsoft MAchine Reading COmprehension Dataset (or MS MARCO) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/MS-MARCO.yml)\]
Machine Comprehension Test (MCTest) of text from Microsoft Research \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Machine-Comprehension-Test-MCTest-of-text-from-Microsoft-Research.yml)\]
Machine Translation of European languages \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Machine-Translation-of-European-languages.yml)\]
Making Sense of Microposts 2013 - Concept Extraction \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Making-Sense-of-Microposts-2013.yml)\]
Making Sense of Microposts 2016 - Named Entity rEcognition and Linking \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Making-Sense-of-Microposts-2016.yml)\]
Multi-Domain Sentiment Dataset (version 2.0) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Multi-Domain-Sentiment-Dataset-version-2.0.yml)\]
No Language Left Behind (NLLB - 200vo) - Dataset based on Meta's metadata for mined bitext. \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/NoLanguageLeftBehindNLLB200vo.yml)\]
Noisy speech database for training speech enhancement algorithms and TTS models - Clean and \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Noisy-Speech.yml)\]
Open Multilingual Wordnet \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Open-Multilingual-Wordnet.yml)\]
POS/NER/Chunk annotated data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/POS-NER-Chunk-annotated-data.yml)\]
Personae Corpus \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Personae-Corpus.yml)\]
SMS Spam Collection in English \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/SMS-Spam-Collection-in-English.yml)\]
SaudiNewsNet Collection of Saudi Newspaper Articles (Arabic, 30K articles) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/SaudiNewsNet-Collection-of-Saudi-Newspaper-Articles-Arabic-30K-articles.yml)\]
Stanford Question Answering Dataset (SQuAD) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Stanford-Question-Answering-Dataset-SQuAD.yml)\]
USENET postings corpus of 2005~2011 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/USENET-postings-corpus-of-2005~2011.yml)\]
Universal Dependencies \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Universal-Dependencies.yml)\]
Webhose - News/Blogs in multiple languages \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Webhose.yml)\]
Wikidata - Wikipedia databases \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Wikidata.yml)\]
Wikipedia Links data - 40 Million Entities in Context \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Wikipedia-Links-data.yml)\]
WordNet databases and tools \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/WordNet-databases-and-tools.yml)\]
Wordbank - Open, de-identified database of vocabulary development from 84,138 children and \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Wordbank.yml)\]
WorldTree Corpus of Explanation Graphs for Elementary Science Questions - a corpus of \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//NaturalLanguage/Worldtree-Explanation-Corpus.yml)\]

Neuroscience

Allen Institute Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/Allen-Institute-Datasets.yml)\]
Brain Catalogue \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/Brain-Catalogue.yml)\]
Brainomics \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/Brainomics.yml)\]
CodeNeuro Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/CodeNeuro-Datasets.yml)\]
Collaborative Research in Computational Neuroscience (CRCNS) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/Collaborative-Research-in-Computational-Neuroscience-CRCNS.yml)\]
FCP-INDI \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/FCP-INDI.yml)\]
Human Connectome Project \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/Human-Connectome-Project.yml)\]
NDAR \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/NDAR.yml)\]
NIMH Data Archive \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/NIMH-Data-Archive.yml)\]
NeuroData \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/NeuroData.yml)\]
NeuroMorpho - NeuroMorpho.Org is a centrally curated inventory of digitally reconstructed \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/NeuroMorpho.yml)\]
Neuroelectro \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/Neuroelectro.yml)\]
OASIS \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/OASIS.yml)\]
OpenNEURO \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/OpenNEURO)\]
OpenfMRI \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/OpenfMRI.yml)\]
Study Forrest \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/Study-Forrest.yml)\]
The Nencki-Symfonia EEG/ERP dataset - A high-density electroencephalography (EEG) dataset \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Neuroscience/The_Nencki-Symfonia_EEG_ERP_dataset.yml)\]

Physics

CERN Open Data Portal \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Physics/CERN-Open-Data-Portal.yml)\]
Crystallography Open Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Physics/Crystallography-Open-Database.yml)\]
IceCube - South Pole Neutrino Observatory \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Physics/IceCube.yml)\]
Ligo Open Science Center (LOSC) - Gravitational wave data from the LIGO Hanford and \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Physics/LIGO-Open-Science-Center.yml)\]
NASA Exoplanet Archive \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Physics/NASA-Exoplanet-Archive.yml)\]
NSSDC (NASA) data of 550 space spacecraft \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Physics/NSSDC-NASA-data-of-550-space-spacecraft.yml)\]
Quantum simulations of an electron in a two dimensional potential well - The data was \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Physics/Quantum.yml)\]
Sloan Digital Sky Survey (SDSS) - Mapping the Universe \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Physics/Sloan-Digital-Sky-Survey-SDSS.yml)\]

ProstateCancer

EOPC-DE-Early-Onset-Prostate-Cancer-Germany - Early Onset Prostate Cancer - Germany. \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/EOPC-DE-Early-Onset-Prostate-Cancer-Germany.yml)\]
GENIE - Data from the Genomics Evidence Neoplasia Information Exchange (GENIE) project of the \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/GENIE.yml)\]
Genomic-Hallmarks-Prostate-Adenocarcinoma-CPC-GENE - Comprehensive genomic profiling of 477 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Genomic-Hallmarks-Prostate-Adenocarcinoma-CPC-GENE.yml)\]
MSK-IMPACT-Clinical-Sequencing-Cohort-MSKCC-Prostate-Cancer - Targeted sequencing of clinical \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/MSK-IMPACT-Clinical-Sequencing-Cohort-MSKCC-Prostate-Cancer.yml)\]
Metastatic-Prostate-Adenocarcinoma-MCTP - Comprehensive profiling of 61 prostate cancer \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Metastatic-Prostate-Adenocarcinoma-MCTP.yml)\]
Metastatic-Prostate-Cancer-SU2CPCF-Dream-Team - Comprehensive analysis of 150 metastatic \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Metastatic-Prostate-Cancer-SU2CPCF-Dream-Team.yml)\]
NPCR-2001-2015 - Database from CDC's National Program of Cancer Registries (NPCR). The \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/NPCR-2001-2015.yml)\]
NPCR-2005-2015 - Database from CDC's National Program of Cancer Registries (NPCR). The \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/NPCR-2005-2015.yml)\]
NaF-Prostate - NaF Prostate is a collection of F-18 NaF positron emission tomography/computed \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/NaF-Prostate.yml)\]
Neuroendocrine-Prostate-Cancer - Whole exome and RNA Seq data of castration resistant \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Neuroendocrine-Prostate-Cancer.yml)\]
PLCO-Prostate-Diagnostic-Procedures - The Prostate Diagnostic Procedures dataset (95,837 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/PLCO-Prostate-Diagnostic-Procedures.yml)\]
PLCO-Prostate-Medical-Complications - The Prostate Medical Complications dataset (3,350 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/PLCO-Prostate-Medical-Complications.yml)\]
PLCO-Prostate-Screening-Abnormalities - The Prostate Screening Abnormalities dataset (10,527 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/PLCO-Prostate-Screening-Abnormalities.yml)\]
PLCO-Prostate-Screening - The Prostate Screening dataset (177,315 records, 35,875 subjects, \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/PLCO-Prostate-Screening.yml)\]
PLCO-Prostate-Treatments - The Prostate Treatments dataset (13,409 records, 7,614 subjects, \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/PLCO-Prostate-Treatments.yml)\]
PLCO-Prostate - The Prostate dataset is a comprehensive dataset that contains nearly all the \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/PLCO-Prostate.yml)\]
PRAD-CA-Prostate-Adenocarcinoma-Canada - Prostate Adenocarcinoma - Canada. Collected by the \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/PRAD-CA-Prostate-Adenocarcinoma-Canada.yml)\]
PRAD-FR-Prostate-Adenocarcinoma-France - Prostate Adenocarcinoma - France. Collected by ten \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/PRAD-FR-Prostate-Adenocarcinoma-France.yml)\]
PRAD-UK-Prostate-Adenocarcinoma-United-Kingdom - Prostate Adenocarcinoma - United Kingdom. \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/PRAD-UK-Prostate-Adenocarcinoma-United-Kingdom.yml)\]
PROSTATEx-Challenge - Retrospective set of prostate MR studies. All studies included \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/PROSTATEx-Challenge.yml)\]
Prostate-3T - The Prostate-3T project provided imaging data to TCIA as part of an ISBI \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-3T.yml)\]
Prostate-Adenocarcinoma-Broad-Cornell-2012 - Comprehensive profiling of 112 prostate cancer \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Adenocarcinoma-Broad-Cornell-2012.yml)\]
Prostate-Adenocarcinoma-Broad-Cornell-2013 - Comprehensive profiling of 57 prostate cancer \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Adenocarcinoma-Broad-Cornell-2013.yml)\]
Prostate-Adenocarcinoma-CNA-study-MSKCC - Copy-number profiling of 103 primary prostate \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Adenocarcinoma-CNA-study-MSKCC.yml)\]
Prostate-Adenocarcinoma-Fred-Hutchinson-CRC - Comprehensive profiling of prostate cancer \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Adenocarcinoma-Fred-Hutchinson-CRC.yml)\]
Prostate Adenocarcinoma (MSKCC/DFCI) - Whole Exome Sequencing of 1013 prostate cancer samples. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Adenocarcinoma-MSKCC-DFCI.yml)\]
Prostate-Adenocarcinoma-MSKCC - MSKCC Prostate Oncogenome Project. 181 primary, 37 metastatic \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Adenocarcinoma-MSKCC.yml)\]
Prostate-Adenocarcinoma-Organoids-MSKCC - Exome profiling of prostate cancer samples and \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Adenocarcinoma-Organoids-MSKCC.yml)\]
Prostate-Adenocarcinoma-Sun-Lab - Whole-genome and Transcriptome Sequencing of 65 Prostate \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Adenocarcinoma-Sun-Lab.yml)\]
Prostate-Adenocarcinoma-TCGA-PanCancer-Atlas - Comprehensive TCGA PanCanAtlas data from 11k \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Adenocarcinoma-TCGA-PanCancer-Atlas.yml)\]
Prostate-Adenocarcinoma-TCGA - Integrated profiling of 333 primary prostate adenocarcinoma samples. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Adenocarcinoma-TCGA.yml)\]
Prostate-Diagnosis - PCa T1- and T2-weighted magnetic resonance images (MRIs) were acquired \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Diagnosis.yml)\]
Prostate-Fused-MRI-Pathology - The Prostate Fused-MRI-Pathology collection is a combination \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-Fused-MRI-Pathology.yml)\]
Prostate-MRI - The Prostate-MRI collection of prostate Magnetic Resonance Images (MRIs) was \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-MRI.yml)\]
Prostate-R - The R package 'ElemStatLearn' contains a prostate cancer dataset from Stamey et \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/Prostate-R.yml)\]
QIN-PROSTATE-Repeatability - The QIN-PROSTATE-Repeatability dataset is a dataset with \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/QIN-PROSTATE-Repeatability.yml)\]
QIN-PROSTATE - The QIN PROSTATE collection of the Quantitative Imaging Network (QIN) contains \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/QIN-PROSTATE.yml)\]
SEER-YR1973_2015.SEER9 - The SEER November 2017 Research Data files from nine SEER registries \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/SEER-YR1973_2015.SEER9.yml)\]
SEER-YR1992_2015.SJ_LA_RG_AK - The SEER November 2017 Research Data files from the San Jose- \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/SEER-YR1992_2015.SJ_LA_RG_AK.yml)\]
SEER-YR2000_2015.CA_KY_LO_NJ_GA - The SEER November 2017 Research Data files from the Greater \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/SEER-YR2000_2015.CA_KY_LO_NJ_GA.yml)\]
SEER-YR2000_2015.CA_KY_LO_NJ_GA - The July - December 2005 diagnoses for Louisiana from their \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/SEER-YR2005.LO_2ND_HALF.yml)\]
TCGA-PRAD-US - TCGA Prostate Adenocarcinoma (499 samples). \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//ProstateCancer/TCGA-PRAD-US.yml)\]

Psychology+Cognition

OSU Cognitive Modeling Repository Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Psychology+Cognition/OSU-Cognitive-Modeling-Repository-Datasets.yml)\]
Open Cognitive Science Data - Publicly available behavioral datasets from across cognitive \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Psychology+Cognition/Open-Cognitive-Science-Data-Repository.yml)\]

PublicDomains

Ably Open Realtime Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Ably.yml)\]
Amazon \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Amazon.yml)\]
Archive.org Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Archive.org-Datasets.yml)\]
Archive-it from Internet Archive \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Archive.yml)\]
CMU JASA data archive \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/CMU-JASA-data-archive.yml)\]
CMU StatLab collections \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/CMU-StatLab-collections.yml)\]
Data.World \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Data.World.yml)\]
Data360 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Data360.yml)\]
Enigma Public \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Enigma-Public.yml)\]
Google \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Google.yml)\]
Grand Comics Database - The Grand Comics Database (GCD) is a nonprofit, internet-based \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/GrandComics.yml)\]
Infochimps \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Infochimps.yml)\]
KDNuggets Data Collections \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/KDNuggets-Data-Collections.yml)\]
Microsoft Azure Data Market Free DataSets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Microsoft-Azure-Data-Market-Free-DataSets.yml)\]
Microsoft Data Science for Research \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Microsoft-Data-Science-for-Research.yml)\]
Microsoft Research Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Microsoft-Research-Open-Data)\]
Open Library Data Dumps \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Open-Library-Data-Dumps.yml)\]
Reddit Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Reddit-Datasets.yml)\]
RevolutionAnalytics Collection \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/RevolutionAnalytics-Collection.yml)\]
Sample R data sets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Sample-R-data-sets.yml)\]
Stack Overflow Annual Developer Survey - Annual developer surverys full data sets from 2011 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Stack-Overflow-Annual-Developer-Survey.yml)\]
StatSci.org \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/StatSci.org.yml)\]
Stats4Stem R data sets (archived) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Stats4Stem-R-data-sets.yml)\]
The Washington Post List \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/The-Washington-Post-List.yml)\]
UCLA SOCR data collection \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/UCLA-SOCR-data-collection.yml)\]
UFO Reports \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/UFO-Reports.yml)\]
Wikileaks 911 pager intercepts \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Wikileaks-911-pager-intercepts.yml)\]
Yahoo Webscope \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//PublicDomains/Yahoo-Webscope.yml)\]

SearchEngines

Academic Torrents of data sharing from UMB \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/Academic-Torrents-of-data-sharing-from-UMB.yml)\]
Base dos Dados - Data Basis: Open Data Repository for Brazil \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/BaseDosDados.yml)\]
Datahub.io \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/Datahub.io.yml)\]
Domains Project - Sorted list of Internet domains \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/DomainsProject.yml)\]
Harvard Dataverse Network of scientific data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/Harvard-Dataverse-Network-of-scientific-data.yml)\]
ICPSR (UMICH) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/ICPSR-UMICH.yml)\]
Institute of Education Sciences \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/Institute-of-Education-Sciences.yml)\]
National Technical Reports Library \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/National-Technical-Reports-Library.yml)\]
Open Data Certificates (beta) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/Open-Data-Certificates-beta.yml)\]
OpenDataNetwork - A search engine of all Socrata powered data portals \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/OpenDataNetwork.yml)\]
Statista.com - statistics and Studies \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/Statista.com.yml)\]
Zenodo - An open dependable home for the long-tail of science \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SearchEngines/Zenodo.yml)\]

SocialNetworks

2021 Portuguese Elections Twitter Dataset - 57M+ tweets, 1M+ users - This dataset contains \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/2021_Portuguese_Elections_Twitter_Dataset_57M_tweets_1M_users.yml)\]
72 hours #gamergate Twitter Scrape \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/72-hours-gamergate-Twitter-Scrape.yml)\]
CMU Enron Email of 150 users \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/CMU-Enron-Email-of-150-users.yml)\]
Cheng-Caverlee-Lee September 2009 - January 2010 Twitter Scrape \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Cheng-Caverlee-Lee-Twitter-Scrape-September-2009~January-2010.yml)\]
China Biographical Database - The China Biographical Database is a freely accessible \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/China-Biographical-Database.yml)\]
Clubhouse Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Clubhouse-Dataset.yml)\]
A Twitter Dataset of 40+ million tweets related to COVID-19 - Due to the relevance of the \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Covid19-40-Million-Tweets.yml)\]
43k+ Donald Trump Twitter Screenshots - This archive contains screenshots of 43,475 Donald \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Donald-Trump-Twitter-Screenshots.yml)\]
EDRM Enron EMail of 151 users, hosted on S3 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/EDRM-Enron-EMail-of-151-users-hosted-on-S3.yml)\]
Facebook Data Scrape (2005) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Facebook-Data-Scrape-2005.yml)\]
Facebook Social Connectedness Index - We use an anonymized snapshot of all active Facebook \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Facebook-Social-Connectedness-Index.yml)\]
Facebook Social Networks from LAW (since 2007) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Facebook-Social-Networks-from-LAW-since-2007.yml)\]
Foursquare from UMN/Sarwat (2013) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Foursquare-from-UMN-Sarwat-2013.yml)\]
GitHub Collaboration Archive \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/GitHub-Collaboration-Archive.yml)\]
Google Scholar citation relations \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Google-Scholar-citation-relations.yml)\]
High-Resolution Contact Networks from Wearable Sensors \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/High-Resolution-Contact-Networks-from-Wearable-Sensors.yml)\]
Indie Map: social graph and crawl of top IndieWeb sites \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Indie-Map.yml)\]
Mobile Social Networks from UMASS \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Mobile-Social-Networks-from-UMASS.yml)\]
Network Twitter Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Network-Twitter-Data.yml)\]
Reddit Comments \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Reddit-Comments.yml)\]
Skytrax' Air Travel Reviews Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Skytrax-Air-Travel-Reviews-Dataset.yml)\]
Social Twitter Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Social-Twitter-Data.yml)\]
SourceForge.net Research Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/SourceForge.net-Research-Data.yml)\]
The Reddit COVID dataset - This dataset attempts to capture the full extent of COVID-19 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/The-Reddit-COVID-Dataset.yml)\]
Twitch Top Streamer's Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/TwitchTopStreamers.yml)\]
Twitter Data for Online Reputation Management \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Twitter-Data-for-Online-Reputation-Management.yml)\]
Twitter Data for Sentiment Analysis \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Twitter-Data-for-Sentiment-Analysis.yml)\]
Twitter Graph of entire Twitter site \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Twitter-Graph-of-entire-Twitter-site.yml)\]
Twitter Scrape Calufa May 2011 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Twitter-Scrape-Calufa-May-2011.yml)\]
UNIMI/LAW Social Network Datasets \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/UNIMILAW-Social-Network-Datasets.yml)\]
United States Congress Twitter Data - Daily datasets with tweets of 1100+ accounts associated \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/United-States-Congressional-Twitter-Data.yml)\]
Yahoo! Graph and Social Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Yahoo-Graph-and-Social-Data.yml)\]
Youtube Video Social Graph in 2007,2008 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialNetworks/Youtube-Video-Social-Graph-in-2007~2008.yml)\]

SocialSciences

ACLED (Armed Conflict Location & Event Data Project) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/ACLED.yml)\]
Authoritarian Ruling Elites Database - The Authoritarian Ruling Elites Database (ARED) is a \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Authoritarian-Ruling-Elites.yml)\]
Canadian Legal Information Institute \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Canadian-Legal-Information-Institute.yml)\]
Center for Systemic Peace Datasets - Conflict Trends, Polities, State Fragility, etc \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Center-for-Systemic-Peace-Datasets.yml)\]
Correlates of War Project \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Correlates-of-War-Project.yml)\]
Cryptome Conspiracy Theory Items \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Cryptome-Conspiracy-Theory-Items.yml)\]
Datacards \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Datacards.yml)\]
European Social Survey \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/European-Social-Survey.yml)\]
FBI Hate Crime 2013 - aggregated data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/FBI-Hate-Crime-2013.yml)\]
Fragile States Index \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Fragile-States-Index.yml)\]
GDELT Global Events Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/GDELT-Global-Events-Database.yml)\]
General Social Survey (GSS) since 1972 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/General-Social-Survey-GSS-since-1972.yml)\]
German Social Survey \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/German-Social-Survey.yml)\]
Global Religious Futures Project \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Global-Religious-Futures-Project.yml)\]
Gun Violence Data - A comprehensive, accessible database that contains records of over 260k \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Gun-Violence-Data.yml)\]
Humanitarian Data Exchange \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Humanitarian-Data-Exchange.yml)\]
INFORM Index for Risk Management \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/INFORM-Index-for-Risk-Management.yml)\]
Institute for Demographic Studies \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Institute-for-Demographic-Studies.yml)\]
Inter-American Development Bank Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Inter-American-Development-Bank-Open-Data.yml)\]
International Networks Archive \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/International-Networks-Archive.yml)\]
International Social Survey Program ISSP \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/International-Social-Survey-Program-ISSP.yml)\]
International Studies Compendium Project \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/International-Studies-Compendium-Project.yml)\]
James McGuire Cross National Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/James-McGuire-Cross-National-Data.yml)\]
MIT Reality Mining Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/MIT-Reality-Mining-Dataset.yml)\]
MacroData Guide by Norsk samfunnsvitenskapelig datatjeneste \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/MacroData-Guide-by-Norsk-samfunnsvitenskapelig-datatjeneste.yml)\]
Mass Mobilization Data Project - The Mass Mobilization (MM) data are an effort to understand \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Mass-Mobilization-Data-Project.yml)\]
Microsoft Academic Knowledge Graph - The Microsoft Academic Knowledge Graph is a large RDF \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Microsoft-Academic-Knowledge-Graph.yml)\]
Minnesota Population Center \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Minnesota-Population-Center.yml)\]
Notre Dame Global Adaptation Index (ND-GAIN) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Notre-Dame-Global-Adaptation-Index-NG-DAIN.yml)\]
Open Crime and Policing Data in England, Wales and Northern Ireland \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Open-Crime-and-Policing-Data-in-England-Wales-and-Northern-Ireland.yml)\]
OpenSanctions - A global database of persons and companies of political, criminal, or \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/OpenSanctions.yml)\]
Paul Hensel General International Data Page \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Paul-Hensel-General-International-Data-Page.yml)\]
PewResearch Internet Survey Project \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/PewResearch-Internet-Survey-Project.yml)\]
PewResearch Society Data Collection \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/PewResearch-Society-Data-Collection.yml)\]
Political Polarity Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Political-Polarity-Data.yml)\]
StackExchange Data Explorer \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/StackExchange-Data-Explorer.yml)\]
Terrorism Research and Analysis Consortium \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Terrorism-Research-and-Analysis-Consortium.yml)\]
Texas Inmates Executed Since 1984 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Texas-Inmates-Executed-Since-1984.yml)\]
Titanic Survival Data Set \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Titanic-Survival-Data-Set.yml)\]
UCB's Archive of Social Science Data (D-Lab) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/UCBs-Archive-of-Social-Science-Data-D-Lab.yml)\]
UCLA Social Sciences Data Archive \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/UCLA-Social-Sciences-Data-Archive.yml)\]
UN Civil Society Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/UN-Civil-Society-Database.yml)\]
UPJOHN for Labor Employment Research \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/UPJOHN-for-Labor-Employment-Research.yml)\]
Universities Worldwide \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Universities-Worldwide.yml)\]
Uppsala Conflict Data Program \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/Uppsala-Conflict-Data-Program.yml)\]
World Bank Open Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/World-Bank-Open-Data.yml)\]
World Inequality Database - The World Inequality Database (WID.world) aims to provide open \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/World-Inequality-Database.yml)\]
WorldPop project - Worldwide human population distributions \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//SocialSciences/WorldPop-project.yml)\]

Software

FLOSSmole data about free, libre, and open source software development \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Software/FLOSSmole-data-about-free-libre-and-open-source-software-development.yml)\]
GHTorrent - Scalable, queryable, offline mirror of data offered through the GitHub REST API. \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Software/GHTorrent.yml)\]
Libraries.io Open Source Repository and Dependency Metadata \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Software/Libraries.io-Open-Source-Repository-and-Dependency-Metadata.yml)\]
Public Git Archive - a Big Code dataset for all – dataset of 182,014 top-bookmarked Git \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Software/source%7Bd%7D-Public-Git-Archive.yml)\]
Code duplicates - 2k Java file and 600 Java function pairs labeled as similar or different by \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Software/source%7Bd%7D-code-duplicates.yml)\]
Commit messages - 1.3 billion GitHub commit messages till March 2019 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Software/source%7Bd%7D-commit-messages.yml)\]
Pull Request review comments - 25.3 million GitHub PR review comments since January 2015 till \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Software/source%7Bd%7D-pull-request-review-comments.yml)\]
Source Code Identifiers - 41.7 million distinct splittable identifiers collected from 182,014 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Software/source%7Bd%7D-source-code-identifiers.yml)\]

Sports

American Ninja Warrior Obstacles - Contains every obstacle in the history of American Ninja \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/American-Ninja-Warrior-Obstacles.yml)\]
Betfair Historical Exchange Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/Betfair-Historical-Exchange-Data.yml)\]
Cricsheet Matches (cricket) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/Cricsheet-Matches-cricket.yml)\]
Equity in Athletics - The Equity in Athletics Data Analysis Cutting Tool is brought to you by \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/Equity-in-Athletics.yml)\]
Ergast Formula 1, from 1950 up to date (API) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/Ergast-Formula-1-from-1950-up-to-date-API.yml)\]
Football/Soccer resources (data and APIs) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/FootballSoccer-resources-data-and-APIs.yml)\]
Lahman's Baseball Database \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/Lahmans-Baseball-Database.yml)\]
NFL play-by-play data - NFL play-by-play data sourced from: \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/NFL-play-by-play.yml)\]
Pinhooker: Thoroughbred Bloodstock Sale Data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/Pinhooker.yml)\]
Pro Kabadi season 1 to 7 - Pro Kabadi League is a professional-level Kabaddi league in India. \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/Pro_Kabadi_season1_7.yml)\]
Retrosheet Baseball Statistics \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/Retrosheet-Baseball-Statistics.yml)\]
Tennis database of rankings, results, and stats for ATP \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/Tennis-database-of-rankings-results-and-stats-for-ATP.yml)\]
Tennis database of rankings, results, and stats for WTA \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/Tennis-database-of-rankings-results-and-stats-for-WTA.yml)\]
Transfermarkt Datasets - Clean, structured and automatically updated football (soccer) data \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/Transfermarkt-Datasets.yml)\]
USA Soccer Teams and Locations - USA soccer teams and locations. MLS, NWSL, and USL \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Sports/USA-Soccer.yml)\]

TimeSeries

3W dataset - To the best of its authors' knowledge, this is the first realistic and public \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//TimeSeries/3W-dataset-rare-undesirable-real-events-in-oil-wells.yml)\]
Databanks International Cross National Time Series Data Archive \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//TimeSeries/Databanks-International-Cross-National-Time-Series-Data-Archive.yml)\]
Hard Drive Failure Rates \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//TimeSeries/Hard-Drive-Failure-Rates.yml)\]
Heart Rate Time Series from MIT \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//TimeSeries/Heart-Rate-Time-Series-from-MIT.yml)\]
Time Series Data Library (TSDL) from MU \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//TimeSeries/Time-Series-Data-Library-TSDL-from-MU.yml)\]
Turing Change Point Dataset - Contains 42 annotated time series collected for the development \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//TimeSeries/Turing-Change-Point-Dataset.yml)\]
UC Riverside Time Series Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//TimeSeries/UC-Riverside-Time-Series-Dataset.yml)\]

Transportation

Airlines OD Data 1987-2008 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Airlines-OD-Data-1987~2008.yml)\]
Ford GoBike Data (formerly Bay Area Bike Share Data) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Bay-Area-Bike-Share-Data.yml)\]
Bike Share Systems (BSS) collection \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Bike-Share-Systems-BSS-collection.yml)\]
Dutch Traffic Information \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Dutch-Traffic-Information.yml)\]
GeoLife GPS Trajectory from Microsoft Research \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/GeoLife-GPS-Trajectory-from-Microsoft-Research.yml)\]
German train system by Deutsche Bahn \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/German-train-system-by-Deutsche-Bahn.yml)\]
Hubway Million Rides in MA \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Hubway-Million-Rides-in-MA.yml)\]
Melbourne Pedestrian Counting - This dataset contains hourly pedestrian counts since 2009 \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Melbourne-pedestrian-counting.yml)\]
Montreal BIXI Bike Share \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Montreal-BIXI-Bike-Share.yml)\]
NYC Taxi Trip Data 2009- \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/NYC-Taxi-Trip-Data-2009.yml)\]
NYC Taxi Trip Data 2013 (FOIA/FOILed) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/NYC-Taxi-Trip-Data-2013-FOIA-FOILed.yml)\]
NYC Uber trip data April 2014 to September 2014 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/NYC-Uber-trip-data-April-2014-to-September-2014.yml)\]
Open Traffic collection \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Open-Traffic-collection.yml)\]
OpenFlights - airport, airline and route data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/OpenFlights.yml)\]
Philadelphia Bike Share Stations (JSON) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Philadelphia-Bike-Share-Stations-JSON.yml)\]
Plane Crash Database, since 1920 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Plane-Crash-Database-since-1920.yml)\]
RITA Airline On-Time Performance data \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/RITA-Airline-On.yml)\]
RITA/BTS transport data collection (TranStat) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/RITA-BTS-transport-data-collection-TranStat.yml)\]
Renfe (Spanish National Railway Network) dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Spanish-train-system-by-Renfe.yml)\]
Toronto Bike Share Stations (JSON and GBFS files) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Toronto-Bike-Share-Stations-XML-file.yml)\]
Transport for London (TFL) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Transport-for-London-TFL.yml)\]
Travel Tracker Survey (TTS) for Chicago \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/Travel-Tracker-Survey-TTS-for-Chicago.yml)\]
U.S. Bureau of Transportation Statistics (BTS) \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/U.S.-Bureau-of-Transportation-Statistics-BTS.yml)\]
U.S. Domestic Flights 1990 to 2009 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/U.S.-Domestic-Flights-1990-to-2009.yml)\]
U.S. Freight Analysis Framework since 2007 \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/U.S.-Freight-Analysis-Framework-since-2007.yml)\]
U.S. National Highway Traffic Safety Administration - Fatalities since 1975 - Contains CSV \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//Transportation/U.S.-National-Highway-Traffic-Safety-Administation-Fatalities-since-1975.yml)\]

eSports

CS:GO Competitive Matchmaking Data - In this data set we have data about the CSGO matchmaking \[\...\] \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//eSports/csgo.yml)\]
FIFA-2021 Complete Player Dataset \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//eSports/fifa2021.yml)\]
OpenDota data dump \[[Meta](https://github.com/awesomedata/apd-core/tree/master/core//eSports/opendota-dump.yml)\]

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Paper List

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NeuroTechEDU's Awesome List of BCI-related Resources

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