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jHound: Large-Scale Profiling of Open JSON Data

  • We 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.

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Metadaten
Author:Mark Lukas Möller, Nicolas Berton, Meike Klettke, Stefanie ScherzingerORCiD, Uta StörlORCiDGND
URL / DOI:https://btw.informatik.uni-rostock.de/index.php/de/tagungsbaende/send/3-tagungsbaende/tagungsband.pdf
ISBN:978-3-88579-683-1
Parent Title (German):Datenbanksysteme für Business, Technologie und Web (BTW 2019), 18. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS) : 4.-8. März 2019 in Rostock
Publisher:GI - Gesellschaft für Informatik
Place of publication:Bonn
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2018
Release Date:2022/07/11
Tag:Datenerhebung; Datenformat; Datenmodell; Eigenschaftskennwert; Hauptspeicher; Histogramm; Zeitüberwachung
Volume:289
First Page:557
Last Page:560
Institutes:Fakultät Informatik und Mathematik
research focus:Digitalisierung
Licence (German):Creative Commons - CC BY-SA - Namensnennung - Weitergabe unter gleichen Bedingungen 3.0 International