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Clear format and fix #291
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Xiaming Chen
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69
README.rst
69
README.rst
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@ -25,8 +25,8 @@ Biology
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* `1000 Genomes <http://www.1000genomes.org/data>`_
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* `American Gut (Microbiome Project) <https://github.com/biocore/American-Gut>`_
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* `Broad Cancer Cell Line Encyclopedia (CCLE) <http://www.broadinstitute.org/ccle/home>`_
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* `Broad Bioimage Benchmark Collection (BBBC) <https://www.broadinstitute.org/bbbc>`_
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* `Broad Cancer Cell Line Encyclopedia (CCLE) <http://www.broadinstitute.org/ccle/home>`_
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* `Cell Image Library <http://www.cellimagelibrary.org>`_
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* `Complete Genomics Public Data <http://www.completegenomics.com/public-data/69-genomes/>`_
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* `EBI ArrayExpress <http://www.ebi.ac.uk/arrayexpress/>`_
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@ -64,12 +64,13 @@ Biology
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* `The Catalogue of Life <http://www.catalogueoflife.org/content/annual-checklist-archive>`_
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* `The Personal Genome Project <http://www.personalgenomes.org/>`_ or `PGP <https://my.pgp-hms.org/public_genetic_data>`_
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* `UCSC Public Data <http://hgdownload.soe.ucsc.edu/downloads.html>`_
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* `Universal Protein Resource (UnitProt) <http://www.uniprot.org/downloads>`_
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* `UniGene <http://www.ncbi.nlm.nih.gov/unigene>`_
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* `Universal Protein Resource (UnitProt) <http://www.uniprot.org/downloads>`_
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Climate/Weather
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---------------
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* `Actuaries Climate Index <http://actuariesclimateindex.org/data/>`_
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* `Australian Weather <http://www.bom.gov.au/climate/dwo/>`_
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* `Aviation Weather Center - Consistent, timely and accurate weather information for the world airspace system <https://aviationweather.gov/adds/dataserver>`_
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@ -95,6 +96,7 @@ Complex Networks
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* `AMiner Citation Network Dataset <http://aminer.org/citation>`_
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* `CrossRef DOI URLs <https://archive.org/details/doi-urls>`_
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* `DBLP Citation dataset <https://kdl.cs.umass.edu/display/public/DBLP>`_
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* `DIMACS Road Networks Collection <http://www.dis.uniroma1.it/challenge9/download.shtml>`_
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* `NBER Patent Citations <http://nber.org/patents/>`_
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* `Network Repository with Interactive Exploratory Analysis Tools <http://networkrepository.com/>`_
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* `NIST complex networks data collection <http://math.nist.gov/~RPozo/complex_datasets.html>`_
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@ -111,7 +113,7 @@ Complex Networks
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* `UCI Network Data Repository <https://networkdata.ics.uci.edu/resources.php>`_
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* `UFL sparse matrix collection <http://www.cise.ufl.edu/research/sparse/matrices/>`_
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* `WSU Graph Database <http://www.eecs.wsu.edu/mgd/gdb.html>`_
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* `DIMACS Road Networks Collection <http://www.dis.uniroma1.it/challenge9/download.shtml>`_
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Computer Networks
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-----------------
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@ -130,15 +132,10 @@ Computer Networks
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* `UCSD Network Telescope, IPv4 /8 net <http://www.caida.org/projects/network_telescope/>`_
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Contextual Data
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---------------
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* `Context-aware data sets from five domains <https://github.com/irecsys/CARSKit/tree/master/context-aware_data_sets>`_
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Data Challenges
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---------------
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* `Bruteforce Database <https://github.com/duyetdev/bruteforce-database>`_
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* `Challenges in Machine Learning <http://www.chalearn.org/>`_
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* `CrowdANALYTIX dataX <http://data.crowdanalytix.com>`_
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* `D4D Challenge of Orange <http://www.d4d.orange.com/en/home>`_
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@ -150,9 +147,9 @@ Data Challenges
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* `Netflix Prize <http://netflixprize.com/leaderboard.html>`_
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* `Space Apps Challenge <https://2015.spaceappschallenge.org>`_
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* `Telecom Italia Big Data Challenge <https://dandelion.eu/datamine/open-big-data/>`_
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* `Yelp Dataset Challenge <http://www.yelp.com/dataset_challenge>`_
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* `Bruteforce Database <https://github.com/duyetdev/bruteforce-database>`_
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* `TravisTorrent Dataset - MSR'2017 Mining Challenge <https://travistorrent.testroots.org/>`_
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* `Yelp Dataset Challenge <http://www.yelp.com/dataset_challenge>`_
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Earth Science
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-------------
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@ -216,7 +213,6 @@ Energy
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* `WHITED <http://nilmworkshop.org/2016/proceedings/Poster_ID18.pdf>`_
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Finance
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-------
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@ -224,12 +220,12 @@ Finance
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* `Google Finance <https://www.google.com/finance>`_
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* `Google Trends <http://www.google.com/trends?q=google&ctab=0&geo=all&date=all&sort=0>`_
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* `NASDAQ <https://data.nasdaq.com/>`_
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* `NYSE Market Data <ftp://ftp.nyxdata.com>`_ (see FTP link on `RAW <https://raw.githubusercontent.com/caesar0301/awesome-public-datasets/master/README.rst>`_)
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* `OANDA <http://www.oanda.com/>`_
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* `OSU Financial data <http://fisher.osu.edu/fin/fdf/osudata.htm>`_
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* `Quandl <https://www.quandl.com/>`_
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* `St Louis Federal <https://research.stlouisfed.org/fred2/>`_
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* `Yahoo Finance <http://finance.yahoo.com/>`_
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* `NYSE Market Data <ftp://ftp.nyxdata.com>`_ (see FTP link on `RAW <https://raw.githubusercontent.com/caesar0301/awesome-public-datasets/master/README.rst>`_)
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GIS
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@ -263,9 +259,9 @@ GIS
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Government
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----------
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* `OpenDataSoft's list of 1,600 open data <https://www.opendatasoft.com/a-comprehensive-list-of-all-open-data-portals-around-the-world/>`_
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* `Open Data for Africa <http://opendataforafrica.org/>`_
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* `A list of cities and countries contributed by community <https://github.com/caesar0301/awesome-public-datasets/blob/master/Government.rst>`_
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* `Open Data for Africa <http://opendataforafrica.org/>`_
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* `OpenDataSoft's list of 1,600 open data <https://www.opendatasoft.com/a-comprehensive-list-of-all-open-data-portals-around-the-world/>`_
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Healthcare
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@ -289,10 +285,13 @@ Image Processing
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* `10k US Adult Faces Database <http://wilmabainbridge.com/facememorability2.html>`_
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* `2GB of Photos of Cats <http://137.189.35.203/WebUI/CatDatabase/catData.html>`_ or `Archive version <https://web.archive.org/web/20150520175645/http://137.189.35.203/WebUI/CatDatabase/catData.html>`_
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* `Adience Unfiltered faces for gender and age classification <http://www.openu.ac.il/home/hassner/Adience/data.html>`_
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* `Affective Image Classification <http://www.imageemotion.org/>`_
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* `Animals with attributes <http://attributes.kyb.tuebingen.mpg.de/>`_
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* `Caltech Pedestrian Detection Benchmark <https://www.vision.caltech.edu/Image_Datasets/CaltechPedestrians/>`_
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* `Chars74K dataset, Character Recognition in Natural Images (both English and Kannada are available) <http://www.ee.surrey.ac.uk/CVSSP/demos/chars74k/>`_
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* `Face Recognition Benchmark <http://www.face-rec.org/databases/>`_
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* `GDXray: X-ray images for X-ray testing and Computer Vision <http://dmery.ing.puc.cl/index.php/material/gdxray/>`_
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* `ImageNet (in WordNet hierarchy) <http://www.image-net.org/>`_
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* `Indoor Scene Recognition <http://web.mit.edu/torralba/www/indoor.html>`_
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* `International Affective Picture System, UFL <http://csea.phhp.ufl.edu/media/iapsmessage.html>`_
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@ -301,17 +300,17 @@ Image Processing
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* `Several Shape-from-Silhouette Datasets <http://kaiwolf.no-ip.org/3d-model-repository.html>`_
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* `Stanford Dogs Dataset <http://vision.stanford.edu/aditya86/ImageNetDogs/>`_
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* `SUN database, MIT <http://groups.csail.mit.edu/vision/SUN/hierarchy.html>`_
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* `The Oxford-IIIT Pet Dataset <http://www.robots.ox.ac.uk/~vgg/data/pets/>`_
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* `YouTube Faces Database <http://www.cs.tau.ac.il/~wolf/ytfaces/>`_
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* `Adience Unfiltered faces for gender and age classification <http://www.openu.ac.il/home/hassner/Adience/data.html>`_
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* `The Action Similarity Labeling (ASLAN) Challenge <http://www.openu.ac.il/home/hassner/data/ASLAN/ASLAN.html>`_
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* `The Oxford-IIIT Pet Dataset <http://www.robots.ox.ac.uk/~vgg/data/pets/>`_
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* `Violent-Flows - Crowd Violence \ Non-violence Database and benchmark <http://www.openu.ac.il/home/hassner/data/violentflows/>`_
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* `Visual genome <http://visualgenome.org/api/v0/api_home.html>`_
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* `Caltech Pedestrian Detection Benchmark <https://www.vision.caltech.edu/Image_Datasets/CaltechPedestrians/>`_
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* `YouTube Faces Database <http://www.cs.tau.ac.il/~wolf/ytfaces/>`_
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Machine Learning
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----------------
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* `Context-aware data sets from five domains <https://github.com/irecsys/CARSKit/tree/master/context-aware_data_sets>`_
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* `Delve Datasets for classification and regression (Univ. of Toronto) <http://www.cs.toronto.edu/~delve/data/datasets.html>`_
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* `Discogs Monthly Data <http://data.discogs.com/>`_
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* `eBay Online Auctions (2012) <http://www.modelingonlineauctions.com/datasets>`_
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@ -322,8 +321,8 @@ Machine Learning
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* `Machine Learning Data Set Repository <http://mldata.org/>`_
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* `Million Song Dataset <http://labrosa.ee.columbia.edu/millionsong/>`_
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* `More Song Datasets <http://labrosa.ee.columbia.edu/millionsong/pages/additional-datasets>`_
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* `New Yorker caption contest ratings <https://github.com/nextml/caption-contest-data>`_
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* `MovieLens Data Sets <http://grouplens.org/datasets/movielens/>`_
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* `New Yorker caption contest ratings <https://github.com/nextml/caption-contest-data>`_
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* `RDataMining - "R and Data Mining" ebook data <http://www.rdatamining.com/data>`_
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* `Registered Meteorites on Earth <http://healthintelligence.drupalgardens.com/content/registered-meteorites-has-impacted-earth-visualized>`_
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* `Restaurants Health Score Data in San Francisco <http://missionlocal.org/san-francisco-restaurant-health-inspections/>`_
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@ -347,6 +346,7 @@ Museums
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Natural Language
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----------------
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* `Automatic Keyphrase Extracttion <https://github.com/snkim/AutomaticKeyphraseExtraction/>`_
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* `Blogger Corpus <http://u.cs.biu.ac.il/~koppel/BlogCorpus.htm>`_
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* `CLiPS Stylometry Investigation Corpus <http://www.clips.uantwerpen.be/datasets/csi-corpus>`_
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* `ClueWeb09 FACC <http://lemurproject.org/clueweb09/FACC1/>`_
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@ -361,37 +361,36 @@ Natural Language
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* `Hansards text chunks of Canadian Parliament <http://www.isi.edu/natural-language/download/hansard/>`_
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* `Machine Comprehension Test (MCTest) of text from Microsoft Research <http://research.microsoft.com/en-us/um/redmond/projects/mctest/index.html>`_
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* `Machine Translation of European languages <http://statmt.org/wmt11/translation-task.html#download>`_
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* `Multi-Domain Sentiment Dataset (version 2.0) <http://www.cs.jhu.edu/~mdredze/datasets/sentiment/>`_
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* `Microsoft MAchine Reading COmprehension Dataset (or MS MARCO) <http://www.msmarco.org/dataset.aspx>`_
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* `Multi-Domain Sentiment Dataset (version 2.0) <http://www.cs.jhu.edu/~mdredze/datasets/sentiment/>`_
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* `Open Multilingual Wordnet <http://compling.hss.ntu.edu.sg/omw/>`_
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* `Personae Corpus <http://www.clips.uantwerpen.be/datasets/personae-corpus>`_
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* `SaudiNewsNet Collection of Saudi Newspaper Articles (Arabic, 30K articles) <https://github.com/ParallelMazen/SaudiNewsNet>`_
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* `SMS Spam Collection in English <http://www.dt.fee.unicamp.br/~tiago/smsspamcollection/>`_
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* `Universal Dependencies <http://universaldependencies.org>`_
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* `USENET postings corpus of 2005~2011 <http://www.psych.ualberta.ca/~westburylab/downloads/usenetcorpus.download.html>`_
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* `Webhose - News/Blogs in multiple languages <https://webhose.io/datasets>`_
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* `Wikidata - Wikipedia databases <https://www.wikidata.org/wiki/Wikidata:Database_download>`_
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* `Wikipedia Links data - 40 Million Entities in Context <https://code.google.com/p/wiki-links/downloads/list>`_
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* `Universal Dependencies <http://universaldependencies.org>`_
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* `WordNet databases and tools <http://wordnet.princeton.edu/wordnet/download/>`_
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* `Open Multilingual Wordnet <http://compling.hss.ntu.edu.sg/omw/>`_
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* `Automatic Keyphrase Extracttion <https://github.com/snkim/AutomaticKeyphraseExtraction/>`_
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* `News/Blogs in multiple languages <https://webhose.io/datasets/>`_
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Neuroscience
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-------------
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* `Allen Institute Datasets <http://www.brain-map.org/>`_
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* `Brain Catalogue <http://braincatalogue.org/>`_
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* `Brainomics <http://brainomics.cea.fr/localizer>`_
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* `CodeNeuro Datasets <http://datasets.codeneuro.org/>`_
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* `Brainomics <http://brainomics.cea.fr/localizer>`_
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* `CodeNeuro Datasets <http://datasets.codeneuro.org/>`_
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* `Collaborative Research in Computational Neuroscience (CRCNS) <http://crcns.org/data-sets>`_
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* `FCP-INDI <http://fcon_1000.projects.nitrc.org/index.html>`_
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* `Human Connectome Project <http://www.humanconnectome.org/data/>`_
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* `Human Connectome Project <http://www.humanconnectome.org/data/>`_
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* `NDAR <https://ndar.nih.gov/>`_
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* `NIMH Data Archive <http://data-archive.nimh.nih.gov/>`_
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* `NeuroData <http://neurodata.io>`_
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* `Neuroelectro <http://neuroelectro.org/>`_
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* `NIMH Data Archive <http://data-archive.nimh.nih.gov/>`_
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* `OASIS <http://www.oasis-brains.org/>`_
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* `OpenfMRI <https://openfmri.org/>`_
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* `Neuroelectro <http://neuroelectro.org/>`_
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* `Study Forrest <http://studyforrest.org>`_
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@ -419,9 +418,9 @@ Public Domains
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* `Archive.org Datasets <https://archive.org/details/datasets>`_
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* `CMU JASA data archive <http://lib.stat.cmu.edu/jasadata/>`_
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* `CMU StatLab collections <http://lib.stat.cmu.edu/datasets/>`_
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* `Data.World <https://data.world>`_
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* `Data360 <http://www.data360.org/index.aspx>`_
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* `Datamob.org <http://datamob.org/datasets>`_
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* `Data.World <https://data.world>`_
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* `Google <http://www.google.com/publicdata/directory>`_
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* `Infochimps <http://www.infochimps.com/>`_
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* `KDNuggets Data Collections <http://www.kdnuggets.com/datasets/index.html>`_
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* `Skytrax' Air Travel Reviews Dataset <https://github.com/quankiquanki/skytrax-reviews-dataset>`_
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* `Social Twitter Data <http://snap.stanford.edu/data/egonets-Twitter.html>`_
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* `SourceForge.net Research Data <http://www3.nd.edu/~oss/Data/data.html>`_
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* `Twitter Data for Sentiment Analysis <http://help.sentiment140.com/for-students/>`_
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* `Twitter Data for Online Reputation Management <http://nlp.uned.es/replab2013/>`_
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* `Twitter Data for Sentiment Analysis <http://help.sentiment140.com/for-students/>`_
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* `Twitter Graph of entire Twitter site <http://an.kaist.ac.kr/traces/WWW2010.html>`_
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* `Twitter Scrape Calufa May 2011 <http://archive.org/details/2011-05-calufa-twitter-sql>`_
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* `UNIMI/LAW Social Network Datasets <http://law.di.unimi.it/datasets.php>`_
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* `Texas Inmates Executed Since 1984 <http://www.tdcj.state.tx.us/death_row/dr_executed_offenders.html>`_
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* `Titanic Survival Data Set <https://github.com/caesar0301/awesome-public-datasets/tree/master/Datasets>`_ or `on Kaggle <https://www.kaggle.com/c/titanic/data>`_
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* `UCB's Archive of Social Science Data (D-Lab) <http://ucdata.berkeley.edu/>`_
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* `Uppsala Conflict Data Program <http://ucdp.uu.se/>`_
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* `UCLA Social Sciences Data Archive <http://dataarchives.ss.ucla.edu/Home.DataPortals.htm>`_
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* `UN Civil Society Database <http://esango.un.org/civilsociety/>`_
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* `Universities Worldwide <http://univ.cc/>`_
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* `UPJOHN for Labor Employment Research <http://www.upjohn.org/services/resources/employment-research-data-center>`_
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* `Uppsala Conflict Data Program <http://ucdp.uu.se/>`_
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* `World Bank Open Data <http://data.worldbank.org/>`_
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* `WorldPop project - Worldwide human population distributions <http://www.worldpop.org.uk/data/get_data/>`_
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@ -594,8 +593,8 @@ Complementary Collections
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* `Data Packaged Core Datasets <https://github.com/datasets/>`_
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* `Database of Scientific Code Contributions <https://mozillascience.org/collaborate>`_
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* DataWrangling: `Some Datasets Available on the Web <http://www.datawrangling.com/some-datasets-available-on-the-web>`_
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* A growing collection of public datasets: `CoolDatasets. <http://cooldatasets.com/>`_
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* DataWrangling: `Some Datasets Available on the Web <http://www.datawrangling.com/some-datasets-available-on-the-web>`_
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* Inside-r: `Finding Data on the Internet <http://www.inside-r.org/howto/finding-data-internet>`_
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* OpenDataMonitor: `An overview of available open data resources in Europe <http://opendatamonitor.eu>`_
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* Quora: `Where can I find large datasets open to the public? <http://www.quora.com/Where-can-I-find-large-datasets-open-to-the-public>`_
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