Abstract
On-Line Analytical Processing (OLAP) is a data analysis approach to support decision-making. On top of that, Exploratory OLAP is a novel initiative for the convergence of OLAP and the Semantic Web (SW) that enables the use of OLAP techniques on SW data. Moreover, OLAP approaches exploit different metadata artifacts (e.g., queries) to assist users with the analysis. However, modeling and sharing of most of these artifacts are typically overlooked. Thus, in this paper we focus on the query metadata artifact in the Exploratory OLAP context and propose an RDF-based vocabulary for its representation, sharing, and reuse on the SW. As OLAP is based on the underlying multidimensional (MD)
data model we denote such queries as MD queries and define SM4MQ: A Semantic Model for Multidimensional Queries. Furthermore, we propose a method to automate the exploitation of queries by means of SPARQL. We apply the method to a use case of transforming queries from SM4MQ to a vector
representation. For the use case, we developed the prototype and performed an evaluation that shows how our approach can significantly ease and support user assistance such as query recommendation.
data model we denote such queries as MD queries and define SM4MQ: A Semantic Model for Multidimensional Queries. Furthermore, we propose a method to automate the exploitation of queries by means of SPARQL. We apply the method to a use case of transforming queries from SM4MQ to a vector
representation. For the use case, we developed the prototype and performed an evaluation that shows how our approach can significantly ease and support user assistance such as query recommendation.
Original language | English |
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Number of pages | 16 |
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Publication status | Published - 25 May 2017 |
Series | DB Tech Reports |
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Number | 37 |
Bibliographical note
SM4MQ: A Semantic Model for Multidimensional QueriesCopyright: Springer (2017). This is the authors’ version of the work. It is posted here by permission of Springer for your personal use. Not for redistribution.
The definitive version was published in Proceedings of the Semantic
Web - Fourteenth International Conference, ESWC (2017). The final
publication is available at Springer via http://doi.org/10.1007/
978-3-319-58068-5_28.