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dc.contributor.authorVölske, Michael
dc.contributor.authorBevendorff, Janek
dc.contributor.authorKiesel, Johannes
dc.contributor.authorStein, Benno
dc.contributor.authorFröbe, Maik
dc.contributor.authorHagen, Matthias
dc.contributor.authorPotthast, Martin
dc.contributor.editorReussner, Ralf H.
dc.contributor.editorKoziolek, Anne
dc.contributor.editorHeinrich, Robert
dc.date.accessioned2021-01-27T13:33:55Z
dc.date.available2021-01-27T13:33:55Z
dc.date.issued2021
dc.identifier.isbn978-3-88579-701-2
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/34759
dc.description.abstractWeb archive analytics is the exploitation of publicly accessible web pages and their evolution for research purposes—to the extent organizationally possible for researchers. In order to better understand the complexity of this task, the first part of this paper puts the entirety of the world's captured, created, and replicated data (the “Global Datasphere”) in relation to other important data sets such as the public internet and its web pages, or what is preserved thereof by the Internet Archive. Recently, the Webis research group, a network of university chairs to which the authors belong, concluded an agreement with the Internet Archive to download a substantial part of its web archive for research purposes. The second part of the paper in hand describes our infrastructure for processing this data treasure: We will eventually host around 8 PB of web archive data from the Internet Archive and Common Crawl, with the goal of supplementing existing large scale web corpora and forming a non-biased subset of the 30 PB web archive at the Internet Archive.en
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2020
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-307
dc.subjectBig Data Analytics
dc.subjectWeb Archive
dc.subjectInternet Archive
dc.subjectWebis Infrastructure
dc.titleWeb Archive Analyticsen
mci.reference.pages61-72
mci.conference.sessiontitleData Science
mci.conference.locationKarlsruhe
mci.conference.date28. September - 2. Oktober 2020
dc.identifier.doi10.18420/inf2020_05


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