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jHound: Large-Scale Profiling of Open JSON Data

dc.contributor.authorMöller, Mark Lukas
dc.contributor.authorBerton, Nicolas
dc.contributor.authorKlettke, Meike
dc.contributor.authorScherzinger, Stefanie
dc.contributor.authorStörl, Uta
dc.contributor.editorGrust, Torsten
dc.contributor.editorNaumann, Felix
dc.contributor.editorBöhm, Alexander
dc.contributor.editorLehner, Wolfgang
dc.contributor.editorHärder, Theo
dc.contributor.editorRahm, Erhard
dc.contributor.editorHeuer, Andreas
dc.contributor.editorKlettke, Meike
dc.contributor.editorMeyer, Holger
dc.date.accessioned2019-04-11T07:21:35Z
dc.date.available2019-04-11T07:21:35Z
dc.date.issued2019
dc.description.abstractWe present jHound, a tool for profiling large collections of JSON data, and apply it to thousands of data sets holding open government data. jHound reports key characteristics of JSON documents, such as their nesting depth. As we show, jHound can help detect structural outliers, and most importantly, badly encoded documents: jHound can pinpoint certain cases of documents that use string-typed values where other native JSON datatypes would have been a better match. Moreover, we can detect certain cases of maladaptively structured JSON documents, which obviously do not comply with good data modeling practices. By interactively exploring particular example documents, we hope to inspire discussions in the community about what makes a good JSON encoding.en
dc.identifier.doi10.18420/btw2019-44
dc.identifier.isbn978-3-88579-683-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/21731
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofBTW 2019
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) – Proceedings, Volume P-289
dc.titlejHound: Large-Scale Profiling of Open JSON Dataen
gi.citation.endPage558
gi.citation.startPage555
gi.conference.date4.-8. März 2019
gi.conference.locationRostock
gi.conference.sessiontitleDemonstrationen

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