Show simple item record

dc.contributor.authorRudolf, Michael
dc.contributor.authorVoigt, Hannes
dc.contributor.authorLehner, Wolfgang
dc.contributor.editorMitschang, Bernhard
dc.contributor.editorNicklas, Daniela
dc.contributor.editorLeymann, Frank
dc.contributor.editorSchöning, Harald
dc.contributor.editorHerschel, Melanie
dc.contributor.editorTeubner, Jens
dc.contributor.editorHärder, Theo
dc.contributor.editorKopp, Oliver
dc.contributor.editorWieland, Matthias
dc.date.accessioned2017-06-20T20:24:46Z
dc.date.available2017-06-20T20:24:46Z
dc.date.issued2017
dc.identifier.isbn978-3-88579-659-6
dc.identifier.issn1617-5468
dc.description.abstractWith the rapid growth of open RDF data in recent years, being able to perform multidimensional analytics with it has become more and more important, in particular for the data analyst performing explorative business intelligence tasks. Existing analytic approaches are often not flexible enough to address the needs of data analysts and enthusiasts with iterative exploratory workflows. In this paper we propose SPARQLytics, a tool that exposes the concepts of multidimensional graph analytics by offering standard OLAP cube operations and generating SPARQL queries. Our evaluation shows that SPARQLytics unburdens data analysts from writing many lines of SPARQL code in iterative data explorations and at the same time it does not impose any overhead to query execution. SPARQLytics fits well with interactive computing tools, such as Jupyter, providing data enthusiasts with a familiar work environment.en
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2017)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-265
dc.titleSPARQLytics: Multidimensional Analytics for RDFen
dc.typeText/Conference Paper
mci.reference.pages51-60
mci.conference.sessiontitleQuery Processing and Languages
mci.conference.locationStuttgart
mci.conference.date6.-10. März 2017


Files in this item

Thumbnail

Show simple item record