awesome-public-datasets

一个包含高质量公开数据集的列表，这些数据集来自公共领域，持续更新中。

A list of high-quality public datasets sourced from the public domain, continuously updated.

原始信息汇总

数据集概述

本数据集名为“Awesome Public Datasets”，是一个收集并整理自博客、问答和用户反馈的公共数据源列表。以下是该数据集的主要分类及其相关数据源：

农业

• U.S. Department of Agricultures PLANTS Database

生物学

• 1000 Genomes
• American Gut (Microbiome Project)
• Broad Cancer Cell Line Encyclopedia (CCLE)
• Cell Image Library
• Collaborative Research in Computational Neuroscience (CRCNS)
• Complete Genomics Public Data
• EBI ArrayExpress
• EBI Protein Data Bank in Europe
• ENCODE project
• Ensembl Genomes
• Gene Expression Omnibus (GEO)
• Gene Ontology (GO)
• Global Biotic Interactions (GloBI)
• Harvard Medical School (HMS) LINCS Project
• Human Genome Diversity Project
• Human Microbiome Project (HMP)
• ICOS PSP Benchmark
• International HapMap Project
• Journal of Cell Biology DataViewer
• MIT Cancer Genomics Data
• NCBI Proteins
• NCBI Taxonomy
• NeuroData
• NIH Microarray data
• OpenSNP genotypes data
• Pathguid - Protein-Protein Interactions Catalog
• Protein Data Bank
• PubChem Project
• PubGene (now Coremine Medical)
• Sanger Catalogue of Somatic Mutations in Cancer (COSMIC)
• Sanger Genomics of Drug Sensitivity in Cancer Project (GDSC)
• Sequence Read Archive(SRA)
• Stanford Microarray Data
• Stowers Institute Original Data Repository
• Systems Science of Biological Dynamics (SSBD) Database
• Temple University Hospital EEG Database
• The Cancer Genome Atlas (TCGA), available via Broad GDAC
• The Catalogue of Life
• The Personal Genome Project
• UCSC Public Data
• Universal Protein Resource (UnitProt)
• UniGene

气候/天气

• Australian Weather
• Brazilian Weather - Historical data (In Portuguese)
• Canadian Meteorological Centre
• Climate Data from UEA (updated monthly)
• European Climate Assessment & Dataset
• Global Climate Data Since 1929
• NASA Global Imagery Browse Services
• NOAA Bering Sea Climate
• NOAA Climate Datasets
• NOAA Realtime Weather Models
• The World Bank Open Data Resources for Climate Change
• UEA Climatic Research Unit
• WorldClim - Global Climate Data
• WU Historical Weather Worldwide

复杂网络

• CrossRef DOI URLs
• DBLP Citation dataset
• NBER Patent Citations
• NIST complex networks data collection
• Protein-protein interaction network
• PyPI and Maven Dependency Network
• Scopus Citation Database
• Small Network Data
• Stanford GraphBase (Steven Skiena)
• Stanford Large Network Dataset Collection
• Stanford Longitudinal Network Data Sources
• The Koblenz Network Collection
• The Laboratory for Web Algorithmics (UNIMI)
• The Nexus Network Repository
• UCI Network Data Repository
• UFL sparse matrix collection
• WSU Graph Database

计算机网络

• 3.5B Web Pages from CommonCraw 2012
• 53.5B Web clicks of 100K users in Indiana Univ.
• CAIDA Internet Datasets
• ClueWeb09 - 1B web pages
• ClueWeb12 - 733M web pages
• CommonCrawl Web Data over 7 years
• CRAWDAD Wireless datasets from Dartmouth Univ.
• Criteo click-through data
• Open Mobile Data by MobiPerf
• UCSD Network Telescope, IPv4 /8 net

上下文数据

• Context-aware data sets from five domains

数据挑战

• Challenges in Machine Learning
• CrowdANALYTIX dataX
• D4D Challenge of Orange
• DrivenData Competitions for Social Good
• ICWSM Data Challenge (since 2009)
• Kaggle Competition Data
• KDD Cup by Tencent 2012
• Localytics Data Visualization Challenge
• Netflix Prize
• Space Apps Challenge
• Telecom Italia Big Data Challenge
• Yelp Dataset Challenge

经济学

• American Economic Ass (AEA)
• EconData from UMD
• Economic Freedom of the World Data
• Historical MacroEconomic Statistics
• International Trade Statistics
• Internet Product Code Database
• Joint External Debt Data Hub
• Jon Haveman International Trade Data Links
• OpenCorporates Database of Companies in the World
• Our World in Data
• SciencesPo World Trade Gravity Datasets
• The Atlas of Economic Complexity
• The Center for International Data
• The Observatory of Economic Complexity
• UN Commodity Trade Statistics
• UN Human Development Reports

教育

• Student Data from Free Code Camp

能源

• AMPds
• BLUEd
• COMBED
• Dataport
• ECO
• EIA
• HFED
• iAWE
• Plaid
• REDD
• UK-Dale

金融

• CBOE Futures Exchange
• Google Finance
• Google Trends
• NASDAQ
• OANDA
• OSU Financial data
• Quandl
• St Louis Federal
• Yahoo Finance

地质学

• Earth Models
• Smithsonian Institution Global Volcano and Eruption Database
• USGS Earthquake Archives

地理空间/GIS

• BODC - marine data of ~22K vars
• Cambridge, MA, US, GIS data on GitHub
• EOSDIS - NASAs earth observing system data
• Factual Global Location Data
• Geo Spatial Data from ASU
• Geo Wiki Project - Citizen-driven Environmental Monitoring
• GeoFabrik - OSM data extracted to a variety of formats and areas
• GeoNames Worldwide
• Global Administrative Areas Database (GADM)
• International Institute for Systems Analysis - GIS Datasets
• Landsat 8 on AWS
• List of all countries in all languages
• National Weather Service GIS Data Portal
• Natural Earth - vectors and rasters of the world
• OpenAddresses
• OpenStreetMap (OSM)
• Pleiades - Gazetteer and graph of ancient places
• Reverse Geocoder using OSM data
• TIGER/Line - U.S. boundaries and roads
• TwoFishes - Foursquares coarse geocoder
• TZ Timezones shapfiles
• UN Environmental Data
• World boundaries from the U.S. Department of State
• World countries in multiple formats

政府

• Alberta, Province of Canada
• Antwerp, Belgium
• Argentina (non official)
• Argentina
• Austin, TX, US
• Australia (abs.gov.au)
• Australia (data.gov.au)
• Austria (data.gv.at)
• Baton Rouge, LA, US
• Belgium
• Brazil
• Buenos Aires, Argentina
• Calgary, AB, Canada
• Cambridge, MA, US
• Canada
• Chicago
• Dallas Open Data
• DataBC - data from the Province of British Columbia
• Denver Open Data
• Durham, NC Open Data
• Edmonton, AB, Canada
• England LGInform
• EuroStat
• FedStats
• Finland
• France
• Fredericton, NB, Canada
• Gatineau, QC, Canada
• Germany
• Ghent, Belgium
• Glasgow, Scotland, UK
• Greece
• Guardian world governments
• Halifax, NS, Canada
• Helsinki Region, Finland
• Hong Kong, China
• Houston Open Data
• Indian Government Data
• Indonesian Data Portal
• Irelands Open Data Portal
• Japan
• Laval, QC, Canada
• Lexington, KY
• London Datastore, UK
• London, ON, Canada
• Los Angeles Open Data
• MassGIS, Massachusetts, U.S.
• Mexico
• Missisauga, ON, Canada
• Moncton, NB, Canada
• Montreal, QC, Canada
• Netherlands
• New Zealand
• NYC betanyc
• NYC Open Data
• OECD
• Oklahoma
• Open Government Data (OGD) Platform India
• Oregon
• Ottawa, ON, Canada
• Portland, Oregon
• Portugal - Pordata organization
• Puerto Rico Government
• Quebec City, QC, Canada
• Quebec Province of Canada
• Regina SK, Canada
• Rio de Janeiro, Brazil
• Romania
• Russia
• San Francisco Data sets
• Saskatchewan, Province of Canada
• Seattle
• Singapore Government Data
• South Africa
• South Africa Trade Statistics
• State of Utah, US
• Switzerland
• Texas Open Data
• The World Bank
• Toronto, ON, Canada
• U.K. Government Data
• U.S. American Community Survey
• U.S. CDC Public Health datasets
• U.S. Census Bureau
• U.S. Department of Housing and Urban Development (HUD)
• U.S. Federal Government Agencies
• U.S. Federal Government Data Catalog
• U.S. Food and Drug Administration (FDA)
• U.S. National Center for Education Statistics (NCES)
• U.S. Open Government
• UK 2011 Census Open Atlas Project
• United Nations
• Uruguay
• Vancouver, BC Open Data Catalog
• Victoria, BC, Canada
• Vienna, Austria

医疗保健

• EHDP Large Health Data Sets
• Gapminder World demographic databases
• Medicare Coverage Database (MCD), U.S.

搜集汇总

数据集介绍

构建方式

该数据集是通过收集和整理来自博客、回答和用户响应的公共数据源而构建的。它包含了大量免费的数据库，但也包含一些非免费的数据库。

特点

数据集的特点在于其内容的广泛性和多样性，涵盖了多个领域的公共数据，如农业、生物学、气候、网络数据等，为研究人员和开发者提供了丰富的资源。

使用方法

用户可以通过数据集的GitHub页面了解每个数据集的具体信息，包括数据来源、格式和如何使用。对于每个数据集，用户通常需要遵循相应的使用条款和条件。

背景与挑战

背景概述

awesome-public-datasets数据集是一个收集和整理自博客、回答和用户响应的公共数据源列表。该数据集主要由sindresorhus和caesar0301维护，旨在为研究者提供便捷的公共数据集资源。数据集涵盖了多个领域，包括农业、生物学、气候/天气、复杂网络、计算机网络、上下文数据、数据挑战、经济学、教育、能源、金融、地质学、地理空间/GIS、政府、健康护理等。其创建时间为2012年，由sindresorhus和caesar0301等研究人员或机构共同创建，对相关领域的研究产生了重要影响。

当前挑战

在构建awesome-public-datasets数据集的过程中，研究人员面临了多个挑战。首先，收集和整理大量的公共数据集需要耗费大量的时间和精力。其次，数据集的多样性和质量保证也是一个挑战，需要确保收录的数据集对研究者具有实际价值。此外，随着数据集的不断扩大，维护和更新数据集也变得越来越困难。在领域问题上，数据集解决了研究者寻找和获取高质量公共数据集的难题，但同时也带来了数据集选择、整合和使用的挑战。

常用场景

经典使用场景

该数据集汇总了来自多个领域的公共数据集，常被用于学术研究、数据分析以及作为机器学习项目的数据源。经典的使用场景包括为研究提供数据支持，例如在生物信息学领域使用基因序列数据进行分析，或者在社会科学领域利用经济数据进行趋势预测。

解决学术问题

数据集解决了学术研究中数据获取的难题，特别是在那些需要大量数据支撑的领域，如基因组学、环境科学、社会科学等。它为研究者提供了丰富的数据资源，帮助他们验证假设、发现模式并进行预测。

衍生相关工作

基于该数据集，已经衍生出许多相关的工作，包括数据可视化项目、数据分析工具以及基于数据集的学术研究和论文。这些工作进一步推动了数据集的应用和学术研究的进展。