Awesome Public Datasets

一个包含高质量开放数据集的精选列表，涵盖多个领域，如农业、生物学、气候/天气等。

A curated list of high-quality open datasets spanning various domains, including agriculture, biology, climate/weather, and more.

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、问答和用户响应的公共数据源列表。以下是该数据集中包含的主要类别及其相关数据集的概述：

农业

• U.S. Department of Agricultures PLANTS Database

生物学

• 1000 Genomes
• American Gut (Microbiome Project)
• Collaborative Research in Computational Neuroscience (CRCNS)
• EBI ArrayExrepss
• ENCODE project
• Ensembl Genomes
• Gene Expression Omnibus (GEO)
• Gene Ontology (GO)
• Global Biotic Interations (GloBI)
• Human Microbiome Project (HMP)
• ICOS PSP Benchmark
• MIT Cancer Genomics Data
• NIH Microarray data
• OpenSNP genotypes data
• Pathguid - Protein-Protein Interactions Catalog
• Protein Data Bank
• PubChem Project
• PubGene (now Coremine Medical)
• Sequence Read Archive(SRA)
• Stanford Microarray Data
• The Catalogue of Life
• The Personal Genome Project
• UCSC Public Data
• 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
• 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
• Stanford Longitudinal Network Data Sources

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

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
• 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
• Natural Earth - vectors and rasters of the world
• OpenAddresses
• OpenStreetMap (OSM)
• Reverse Geocoder using OSM data
• TIGER/Line - U.S. boundaries and roads
• TwoFishes - Foursquares coarse geocoder
• TZ Timezones shapfiles
• UN Environmental Data
• 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
• Guardian world governments
• Halifax, NS, Canada
• Helsinki Region, Finland
• Houston Open Data
• Indian Government Data
• Indonesian Data Portal
• Laval, QC, Canada
• 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
• 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

医疗保健

• EHDP Large Health Data Sets
• Gapminder World demographic databases
• Medicare Coverage Database (MCD), U.S.
• Medicare Data Engine of medicare.gov Data
• Medicare Data File
• MeSH, the vocabulary thesaurus used for indexing articles for PubMed
• Number of Ebola Cases and Deaths in Affected Countries (2014)
• Open-ODS (structure of the UK NHS)
• The Cancer Genome Atlas project (TCGA)
• World Health Organization Global Health Observatory

图像处理

• 10k US Adult Faces Database
• 2GB of Photos of Cats
• Affective Image Classification
• Animals with attributes
• Face Recognition Benchmark
• ImageNet (in WordNet hierarchy)
• Indoor Scene Recognition
• International Affective Picture System, UFL
• Massive Visual Memory Stimuli, MIT
• Several Shape-from-Silhouette Datasets
• Stanford Dogs Dataset
• SUN database, MIT
• The Oxford-IIIT Pet Dataset
• YouTube Faces Database

机器学习

• Delve Datasets for classification and regression (Univ. of Toronto)
• Discogs Monthly Data
• eBay Online Auctions (2012)
• IM

以上数据集涵盖了多个领域，包括农业、生物学、气候、复杂网络、计算机网络、上下文数据、数据挑战、经济学、能源、金融、地质学、地理空间/GIS、政府、医疗保健、图像处理和机器学习等。每个类别下都列出了相关的数据集，为研究人员和数据分析师提供了丰富的资源。

搜集汇总

数据集介绍

构建方式

Awesome Public Datasets 是一个收集和整理自博客、回答和用户响应的公共数据集列表。该数据集的构建主要依赖于对现有资源的整合和分类，旨在为研究者提供便捷的数据访问途径。

特点

该数据集的特点在于其覆盖领域广泛，包括农业、生物学、气候、网络、医疗等多个领域，且大部分数据集是免费的。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

用户可以通过数据集提供的链接直接访问和下载所需数据。对于每个数据集，用户应当遵循相应的使用条款和许可协议。部分数据集可能需要特定的软件或工具来处理和分析数据。

背景与挑战

背景概述

Awesome Public Datasets是一个收集和整理自博客、回答和用户响应的公共数据集列表。该数据集主要由sindresorhus和caesar0301维护，旨在为研究人员提供方便的数据集资源。数据集列表涵盖了多个领域，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、能源、金融、地质学、地理空间/GIS、政府、医疗保健、图像处理、机器学习等。这些数据集大部分是免费的，但也有一些不是。该数据集的创建时间是持续性的，主要研究人员为sindresorhus和caesar0301，核心研究问题是提供方便、全面的公共数据集资源，对相关领域的影响力在于促进了数据共享和开放访问的趋势。

当前挑战

该数据集面临的挑战主要包括：1)数据的多样性和质量保证，由于数据集涵盖多个领域，确保每个数据集的质量和适用性是一个挑战；2)数据集的维护和更新，随着新的数据集不断出现，保持数据集列表的时效性和准确性需要持续的努力；3)数据集的描述和元数据管理，为了方便用户使用，需要为每个数据集提供详细的描述和元数据信息。

常用场景

经典使用场景

Awesome Public Datasets是一个汇总了众多公开数据集的资源列表，其经典使用场景在于为研究人员和开发者提供一站式的数据资源查找服务，便于他们能够快速定位并获取到所需的数据集，进而进行数据分析和机器学习等研究工作。

解决学术问题

该数据集解决了学术研究中数据获取困难的问题，尤其是在数据集的查找、对比和选择上，大大降低了研究门槛，提高了研究效率。同时，它也促进了数据共享，避免了重复劳动，推动了学术界的合作与进步。

衍生相关工作

基于该数据集，已经衍生出了一系列相关工作，包括数据集的整理、标注、分析工具的开发以及基于这些数据集的学术论文发表等，这些都进一步推动了相关领域的研究发展。