SM4MQ

A Semantic Model for Multidimensional Queries

Jovan Varga, Ekaterina Dobrokhotova, Oscar Romero, Torben Bach Pedersen, Christian Thomsen

Publikation: Bog/antologi/afhandling/rapportRapportForskning

Resumé

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.
OriginalsprogEngelsk
Antal sider16
StatusUdgivet - 25 maj 2017
NavnDB Tech Reports
Nummer37

Fingerprint

Semantics
Processing
Semantic Web
Metadata
Data structures
Decision making

Citer dette

Varga, J., Dobrokhotova, E., Romero, O., Pedersen, T. B., & Thomsen, C. (2017). SM4MQ: A Semantic Model for Multidimensional Queries. DB Tech Reports, Nr. 37
Varga, Jovan ; Dobrokhotova, Ekaterina ; Romero, Oscar ; Pedersen, Torben Bach ; Thomsen, Christian. / SM4MQ : A Semantic Model for Multidimensional Queries. 2017. 16 s. (DB Tech Reports; Nr. 37).
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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 vectorrepresentation. 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.",
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Varga, J, Dobrokhotova, E, Romero, O, Pedersen, TB & Thomsen, C 2017, SM4MQ: A Semantic Model for Multidimensional Queries. DB Tech Reports, nr. 37.

SM4MQ : A Semantic Model for Multidimensional Queries. / Varga, Jovan; Dobrokhotova, Ekaterina; Romero, Oscar; Pedersen, Torben Bach; Thomsen, Christian.

2017. 16 s. (DB Tech Reports; Nr. 37).

Publikation: Bog/antologi/afhandling/rapportRapportForskning

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T2 - A Semantic Model for Multidimensional Queries

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AU - Dobrokhotova, Ekaterina

AU - Romero, Oscar

AU - Pedersen, Torben Bach

AU - Thomsen, Christian

N1 - SM4MQ: A Semantic Model for Multidimensional Queries Copyright: 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.

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N2 - 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 vectorrepresentation. 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.

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Varga J, Dobrokhotova E, Romero O, Pedersen TB, Thomsen C. SM4MQ: A Semantic Model for Multidimensional Queries. 2017. 16 s. (DB Tech Reports; Nr. 37).