Awesome Public Datasets

一个主题中心的高质量公开数据集列表，收集并整理自博客、问答和用户反馈。

A curated list of high-quality public datasets centered around specific themes, collected and organized from blogs, Q&A platforms, and user feedback.

原始信息汇总

数据集概述

农业

• Hyperspectral benchmark dataset on soil moisture: 链接: Hyperspectral benchmark dataset on soil moisture
• U.S. Department of Agricultures Nutrient Database: 链接: U.S. Department of Agricultures Nutrient Database
• U.S. Department of Agricultures PLANTS Database: 链接: U.S. Department of Agricultures PLANTS Database

生物学

• 1000 Genomes: 链接: 1000 Genomes
• American Gut (Microbiome Project): 链接: American Gut (Microbiome Project)
• Broad Bioimage Benchmark Collection (BBBC): 链接: Broad Bioimage Benchmark Collection (BBBC)
• Broad Cancer Cell Line Encyclopedia (CCLE): 链接: Broad Cancer Cell Line Encyclopedia (CCLE)
• Cell Image Library: 链接: Cell Image Library
• Complete Genomics Public Data: 链接: Complete Genomics Public Data
• EBI ArrayExpress: 链接: EBI ArrayExpress
• EBI Protein Data Bank in Europe: 链接: EBI Protein Data Bank in Europe
• ENCODE project: 链接: ENCODE project
• Electron Microscopy Pilot Image Archive (EMPIAR): 链接: Electron Microscopy Pilot Image Archive (EMPIAR)
• Ensembl Genomes: 链接: Ensembl Genomes
• Gene Expression Omnibus (GEO): 链接: Gene Expression Omnibus (GEO)
• Gene Ontology (GO): 链接: Gene Ontology (GO)
• Global Biotic Interactions (GloBI): 链接: Global Biotic Interactions (GloBI)
• Harvard Medical School (HMS) LINCS Project: 链接: Harvard Medical School (HMS) LINCS Project
• Human Genome Diversity Project: 链接: Human Genome Diversity Project
• Human Microbiome Project (HMP): 链接: Human Microbiome Project (HMP)
• ICOS PSP Benchmark: 链接: ICOS PSP Benchmark
• International HapMap Project: 链接: International HapMap Project
• Journal of Cell Biology DataViewer: 链接: Journal of Cell Biology DataViewer
• KEGG - KEGG is a database resource for understanding high-level functions [...]: 链接: KEGG
• MIT Cancer Genomics Data: 链接: MIT Cancer Genomics Data
• NCBI Proteins: 链接: NCBI Proteins
• NCBI Taxonomy: 链接: NCBI Taxonomy
• NCI Genomic Data Commons: 链接: NCI Genomic Data Commons
• NIH Microarray data: 链接: NIH Microarray data
• OpenSNP genotypes data: 链接: OpenSNP genotypes data
• Pathguid - Protein-Protein Interactions Catalog: 链接: Pathguid - Protein-Protein Interactions Catalog
• Protein Data Bank: 链接: Protein Data Bank
• Psychiatric Genomics Consortium: 链接: Psychiatric Genomics Consortium
• PubChem Project: 链接: PubChem Project
• PubGene (now Coremine Medical): 链接: PubGene (now Coremine Medical)
• Sanger Catalogue of Somatic Mutations in Cancer (COSMIC): 链接: Sanger Catalogue of Somatic Mutations in Cancer (COSMIC)
• Sanger Genomics of Drug Sensitivity in Cancer Project (GDSC): 链接: Sanger Genomics of Drug Sensitivity in Cancer Project (GDSC)
• Sequence Read Archive(SRA): 链接: Sequence Read Archive(SRA)
• Stanford Microarray Data: 链接: Stanford Microarray Data
• Stowers Institute Original Data Repository: 链接: Stowers Institute Original Data Repository
• Systems Science of Biological Dynamics (SSBD) Database: 链接: Systems Science of Biological Dynamics (SSBD) Database
• The Cancer Genome Atlas (TCGA), available via Broad GDAC: 链接: The Cancer Genome Atlas (TCGA), available via Broad GDAC
• The Catalogue of Life: 链接: The Catalogue of Life
• The Personal Genome Project: 链接: The Personal Genome Project
• UCSC Public Data: 链接: UCSC Public Data
• UniGene: 链接: UniGene
• Universal Protein Resource (UnitProt): 链接: Universal Protein Resource (UnitProt)

气候+天气

• Actuaries Climate Index: 链接: Actuaries Climate Index
• Australian Weather: 链接: Australian Weather
• Aviation Weather Center - Consistent, timely and accurate weather [...]: 链接: Aviation Weather Center - Consistent, timely and accurate weather [...]
• Brazilian Weather - Historical data (In Portuguese) - Data related to [...]: 链接: Brazilian Weather - Historical data (In Portuguese) - Data related to [...]
• Canadian Meteorological Centre: 链接: Canadian Meteorological Centre
• Climate Data from UEA (updated monthly): 链接: Climate Data from UEA (updated monthly)
• European Climate Assessment & Dataset: 链接: European Climate Assessment & Dataset
• Global Climate Data Since 1929: 链接: Global Climate Data Since 1929
• NASA Global Imagery Browse Services: 链接: NASA Global Imagery Browse Services
• NOAA Bering Sea Climate: 链接: NOAA Bering Sea Climate
• NOAA Climate Datasets: 链接: NOAA Climate Datasets
• NOAA Realtime Weather Models: 链接: NOAA Realtime Weather Models
• NOAA SURFRAD Meteorology and Radiation Datasets: 链接: NOAA SURFRAD Meteorology and Radiation Datasets
• The World Bank Open Data Resources for Climate Change: 链接: The World Bank Open Data Resources for Climate Change
• UEA Climatic Research Unit: 链接: UEA Climatic Research Unit
• WU Historical Weather Worldwide: 链接: WU Historical Weather Worldwide
• WorldClim - Global Climate Data: 链接: WorldClim - Global Climate Data

复杂网络

• AMiner Citation Network Dataset: 链接: AMiner Citation Network Dataset
• CrossRef DOI URLs: 链接: CrossRef DOI URLs
• DBLP Citation dataset: 链接: DBLP Citation dataset
• DIMACS Road Networks Collection: 链接: DIMACS Road Networks Collection
• NBER Patent Citations: 链接: NBER Patent Citations
• NIST complex networks data collection: 链接: NIST complex networks data collection
• Network Repository with Interactive Exploratory Analysis Tools: 链接: Network Repository with Interactive Exploratory Analysis Tools
• Protein-protein interaction network: 链接: Protein-protein interaction network
• PyPI and Maven Dependency Network: 链接: PyPI and Maven Dependency Network
• Scopus Citation Database: 链接: Scopus Citation Database
• Small Network Data: 链接: Small Network Data
• Stanford GraphBase: 链接: Stanford GraphBase
• Stanford Large Network Dataset Collection: 链接: Stanford Large Network Dataset Collection
• Stanford Longitudinal Network Data Sources: 链接: Stanford Longitudinal Network Data Sources
• The Koblenz Network Collection: 链接: The Koblenz Network Collection
• The Laboratory for Web Algorithmics (UNIMI): 链接: The Laboratory for Web Algorithmics (UNIMI)
• UCI Network Data Repository: 链接: UCI Network Data Repository
• UFL sparse matrix collection: 链接: UFL sparse matrix collection
• WSU Graph Database: 链接: WSU Graph Database

计算机网络

• 3.5B Web Pages from CommonCrawl 2012: 链接: 3.5B Web Pages from CommonCrawl 2012
• 53.5B Web clicks of 100K users in Indiana Univ.: 链接: 53.5B Web clicks of 100K users in Indiana Univ.
• CAIDA Internet Datasets: 链接: CAIDA Internet Datasets
• CRAWDAD Wireless datasets from Dartmouth Univ.: 链接: CRAWDAD Wireless datasets from Dartmouth Univ.
• ClueWeb09 - 1B web pages: 链接: ClueWeb09 - 1B web pages
• ClueWeb12 - 733M web pages: 链接: ClueWeb12 - 733M web pages
• CommonCrawl Web Data over 7 years: 链接: CommonCrawl Web Data over 7 years
• Criteo click-through data: 链接: Criteo click-through data
• Internet-Wide Scan Data Repository: 链接: Internet-Wide Scan Data Repository
• OONI: Open Observatory of Network Interference - Internet censorship data: 链接: OONI: Open Observatory of Network Interference - Internet censorship data
• Open Mobile Data by MobiPerf: 链接: Open Mobile Data by MobiPerf
• The Peer-to-Peer Trace Archive - Real-world measurements play a key role [...]: 链接: The Peer-to-Peer Trace Archive - Real-world measurements play a key role [...]
• Rapid7 Sonar Internet Scans: 链接: Rapid7 Sonar Internet Scans
• UCSD Network Telescope, IPv4 /8 net: 链接: UCSD Network Telescope, IPv4 /8 net

数据挑战

• Bruteforce Database: 链接: Bruteforce Database
• Challenges in Machine Learning: 链接: Challenges in Machine Learning
• CrowdANALYTIX dataX: 链接: CrowdANALYTIX dataX
• D4D Challenge of Orange: 链接: [D4D Challenge of Orange](http

搜集汇总

数据集介绍

构建方式

Awesome Public Datasets 是一个由社区驱动的开源项目，旨在收集和整理互联网上各种领域的公共数据集。该数据集的构建主要通过自动化脚本从多个来源抓取信息，并按照特定格式进行整理和存储，以便于用户查找和使用。

特点

该数据集的特点在于其覆盖领域广泛，包含农业、生物学、气候与天气、复杂网络、计算机网络、数据挑战、地球科学、经济学、教育、能源、金融、地理信息系统等多个领域。此外，数据集持续更新，保证了数据的时效性和多样性。

使用方法

用户可以通过GitHub仓库的README文件中提供的链接访问各个数据集。每个数据集都有详细的描述和使用说明，用户可以根据自己的需求选择合适的数据集进行下载和使用。部分数据集可能需要特定的软件或工具来处理和分析。

背景与挑战

背景概述

Awesome Public Datasets是一个由社区驱动的开源项目，旨在收集和整理互联网上各种领域的公共数据集。该项目创建于2013年，由sindresorhus维护，并在GitHub上托管。它涵盖了从农业到地理科学，再到金融和计算机网络的广泛领域，为研究人员和开发者提供了丰富的数据资源。该数据集的影响力体现在其被广泛引用于学术研究和工业应用中，成为数据科学和机器学习领域的重要基础设施之一。

当前挑战

尽管Awesome Public Datasets在数据集的收集和整理方面取得了显著成就，但在以下几个方面仍面临挑战：1）数据集的质量和一致性难以保证，因为数据来源多样，缺乏统一的质量控制标准；2）数据集的更新和维护依赖于社区贡献，可能导致更新不及时；3）部分数据集的版权和使用许可不明确，可能存在法律风险；4）数据集的多样性和覆盖范围虽然广泛，但在某些特定领域可能仍显不足。

常用场景

经典使用场景

Awesome Public Datasets作为一个集成了众多领域公共数据集的仓库，其经典使用场景在于为研究者和开发者提供了一个全面的数据资源平台。用户可以在此找到适用于各种研究目的的基准数据集，例如生物信息学领域的1000 Genomes数据集，用于分析和研究人类基因组的多样性；或者气候科学领域的NOAA气候数据集，用于气候模型的研究与验证。

解决学术问题

该数据集解决了学术研究中数据获取与整合的难题。研究者往往需要花费大量时间寻找和整理数据，而Awesome Public Datasets提供了一个集中化的资源，使得研究者能够更加高效地访问到高质量的数据集，加速学术研究的进程。此外，它还促进了跨学科的研究，因为不同领域的研究者可以轻松地探索和利用其他领域的数据。

衍生相关工作

基于Awesome Public Datasets的数据集，衍生出了许多相关的工作。例如，研究者可以利用这些数据集开发新的数据分析方法，或者构建更加精确的预测模型。此外，开源项目也可以利用这些数据集进行功能演示和性能测试，进一步推动相关技术的发展和应用。