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

Median Hilal, Christoph Georg Schütz, Michael Schrefl

Institute of Business Informatics - Data and Knowledge Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

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

Original language	English
Title of host publication	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
Place of Publication	Online at: http://ceur-ws.org/Vol-1963/paper515.pdf
Number of pages	4
Volume	1936
Publication status	Published - Oct 2017

Publication series

Name	CEUR Workshop Proceedings

Fields of science

102 Computer Sciences
102010 Database systems
102015 Information systems
102016 IT security
102025 Distributed systems
102027 Web engineering
102028 Knowledge engineering
102030 Semantic technologies
102033 Data mining
502050 Business informatics
503008 E-learning

JKU Focus areas

Computation in Informatics and Mathematics
Management and Innovation

Cite this

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. Vol. 1936 Online at: http://ceur-ws.org/Vol-1963/paper515.pdf, 2017. (CEUR Workshop Proceedings).

@inproceedings{51100c1b41a14305a495129198f92a5d,

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",

author = "Median Hilal and Sch{\"u}tz, {Christoph Georg} and Michael Schrefl",

year = "2017",

month = oct,

language = "English",

volume = "1936",

series = "CEUR Workshop Proceedings",

booktitle = "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",

}

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. vol. 1936, 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. Vol. 1936 Online at: http://ceur-ws.org/Vol-1963/paper515.pdf, 2017. (CEUR Workshop Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

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

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M3 - Conference proceedings

VL - 1936

T3 - CEUR Workshop Proceedings

BT - 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

CY - Online at: http://ceur-ws.org/Vol-1963/paper515.pdf

ER -

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. Vol. 1936. Online at: http://ceur-ws.org/Vol-1963/paper515.pdf. 2017. (CEUR Workshop Proceedings).

An OLAP Endpoint for RDF Data Analysis Using Analysis Graphs

Abstract

Publication series

Fields of science

JKU Focus areas

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Cite this