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Modeling, Generating, and Publishing Knowledge as Linked Data Read chapter Read first chapter

2017 | OriginalPaper | Chapter

A Proposal for Self-Service OLAP Endpoints for Linked RDF Datasets

Author : Median Hilal

Published in: Knowledge Engineering and Knowledge Management

Publisher: Springer International Publishing

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Abstract

Leveraging external RDF data for OLAP analysis opens a wide variety of possibilities that enable analysts to gain interesting insights related to their businesses. While variations of statistical linked data are easily accessible to OLAP systems, exploiting non-statistical linked data, such as DBpedia, for OLAP analysis is not trivial. An OLAP system for these data should, on the one hand, take into account the big volume, heterogeneity, graph nature, and semantics of the RDF data. On the other hand, dealing with external RDF data requires a degree of self-sufficiency of the analyst, which can be met via self-service OLAP, without assistance of specialists. In this paper, we argue the need for self-service OLAP endpoints for linked RDF datasets. We review the related literature and sketch an approach. In particular, we propose the use of multidimensional schemas and analysis graphs over linked RDF datasets, which will empower users to perform self-service OLAP analysis on the linked RDF datasets.

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previous chapter Extracting Knowledge Claims for Automatic Evidence Synthesis Using Semantic Technology
next chapter Ontology Learning from Software Requirements Specification (SRS)
Footnotes
1
Though our main motive is LOD, the principles presented apply to other variations of RDF datasets. Thus, we use the term RDF datasets in general from now on.
 
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Metadata
Title
A Proposal for Self-Service OLAP Endpoints for Linked RDF Datasets
Author
Median Hilal
Copyright Year
2017
Book
Knowledge Engineering and Knowledge Management

Print ISBN: 978-3-319-58693-9

Electronic ISBN: 978-3-319-58694-6

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-58694-6_38

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