An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs

Median Hilal; Christoph Georg Schütz; Michael Schrefl

An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs

Institut für Wirtschaftsinformatik - Data & Knowledge Engineering

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

Abstract

Exploiting Resource Description Framework (RDF) data for Online Analytical Processing (OLAP), especially Linked Open Data (LOD), could allow analysts to obtain interesting insights. To conduct OLAP analysis over RDF data, analysts should know the specific semantics, structure, and querying mechanisms of such data. Furthermore, these data should ideally adhere to a multidimensional structure to be accessible to OLAP. In this demo paper, we present an OLAP endpoint that allows casual analysts to perform self-service OLAP analysis over RDF datasets. Specifically, analysts can instantiate semantic web analysis graphs, which are predefined models of the analysis processes. Semantic web analysis graphs are built on top of multidimensional structures that can be superimposed over arbitrary RDF datasets. Keywords: Linked Open Data, Multidimensional Model, Self-Service Business Intelligence

Originalsprache	Englisch
Titel	Proc. of the 16th Int. Semantic Web Conference (ISWC 2017) – Posters and Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference (ISWC 2017), Oct. 2017, Vienna
Erscheinungsort	Online at: http://ceur-ws.org/Vol-1963/paper515.pdf
Seitenumfang	4
Band	1963
Publikationsstatus	Veröffentlicht - Okt. 2017

Publikationsreihe

Name	CEUR Workshop Proceedings
ISSN (Print)	1613-0073

Wissenschaftszweige

102 Informatik
102010 Datenbanksysteme
102015 Informationssysteme
102016 IT-Sicherheit
102025 Verteilte Systeme
102027 Web Engineering
102028 Knowledge Engineering
102030 Semantische Technologien
102033 Data Mining
502050 Wirtschaftsinformatik
503008 E-Learning

JKU-Schwerpunkte

Computation in Informatics and Mathematics
Management and Innovation

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Hilal, Median ; Schütz, Christoph Georg ; Schrefl, Michael. / An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs. Proc. of the 16th Int. Semantic Web Conference (ISWC 2017) – Posters and Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference (ISWC 2017), Oct. 2017, Vienna. Band 1963 Online at: http://ceur-ws.org/Vol-1963/paper515.pdf, 2017. (CEUR Workshop Proceedings).

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title = "An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs",

abstract = "Exploiting Resource Description Framework (RDF) data for Online Analytical Processing (OLAP), especially Linked Open Data (LOD), could allow analysts to obtain interesting insights. To conduct OLAP analysis over RDF data, analysts should know the specific semantics, structure, and querying mechanisms of such data. Furthermore, these data should ideally adhere to a multidimensional structure to be accessible to OLAP. In this demo paper, we present an OLAP endpoint that allows casual analysts to perform self-service OLAP analysis over RDF datasets. Specifically, analysts can instantiate semantic web analysis graphs, which are predefined models of the analysis processes. Semantic web analysis graphs are built on top of multidimensional structures that can be superimposed over arbitrary RDF datasets. Keywords: Linked Open Data, Multidimensional Model, Self-Service Business Intelligence",

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year = "2017",

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series = "CEUR Workshop Proceedings",

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Hilal, M, Schütz, CG & Schrefl, M 2017, An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs. in Proc. of the 16th Int. Semantic Web Conference (ISWC 2017) – Posters and Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference (ISWC 2017), Oct. 2017, Vienna. Bd. 1963, CEUR Workshop Proceedings, Online at: http://ceur-ws.org/Vol-1963/paper515.pdf.

An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs. / Hilal, Median; Schütz, Christoph Georg ; Schrefl, Michael.
Proc. of the 16th Int. Semantic Web Conference (ISWC 2017) – Posters and Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference (ISWC 2017), Oct. 2017, Vienna. Band 1963 Online at: http://ceur-ws.org/Vol-1963/paper515.pdf, 2017. (CEUR Workshop Proceedings).

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs

AU - Hilal, Median

AU - Schütz, Christoph Georg

AU - Schrefl, Michael

PY - 2017/10

Y1 - 2017/10

N2 - Exploiting Resource Description Framework (RDF) data for Online Analytical Processing (OLAP), especially Linked Open Data (LOD), could allow analysts to obtain interesting insights. To conduct OLAP analysis over RDF data, analysts should know the specific semantics, structure, and querying mechanisms of such data. Furthermore, these data should ideally adhere to a multidimensional structure to be accessible to OLAP. In this demo paper, we present an OLAP endpoint that allows casual analysts to perform self-service OLAP analysis over RDF datasets. Specifically, analysts can instantiate semantic web analysis graphs, which are predefined models of the analysis processes. Semantic web analysis graphs are built on top of multidimensional structures that can be superimposed over arbitrary RDF datasets. Keywords: Linked Open Data, Multidimensional Model, Self-Service Business Intelligence

AB - Exploiting Resource Description Framework (RDF) data for Online Analytical Processing (OLAP), especially Linked Open Data (LOD), could allow analysts to obtain interesting insights. To conduct OLAP analysis over RDF data, analysts should know the specific semantics, structure, and querying mechanisms of such data. Furthermore, these data should ideally adhere to a multidimensional structure to be accessible to OLAP. In this demo paper, we present an OLAP endpoint that allows casual analysts to perform self-service OLAP analysis over RDF datasets. Specifically, analysts can instantiate semantic web analysis graphs, which are predefined models of the analysis processes. Semantic web analysis graphs are built on top of multidimensional structures that can be superimposed over arbitrary RDF datasets. Keywords: Linked Open Data, Multidimensional Model, Self-Service Business Intelligence

UR - http://www.dke.jku.at/research/publications/index.xq

UR - https://www.scopus.com/pages/publications/85033455259

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Hilal M, Schütz CG , Schrefl M. An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs. in Proc. of the 16th Int. Semantic Web Conference (ISWC 2017) – Posters and Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference (ISWC 2017), Oct. 2017, Vienna. Band 1963. Online at: http://ceur-ws.org/Vol-1963/paper515.pdf. 2017. (CEUR Workshop Proceedings).