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Ontology-based data access – Beyond relational sources

Botoeva, Elena, Calvanese, Diego, Cogrel, Benjamin, Corman, Julien, Xiao, Guohui, Ghidini, Chiara, Magnini, Bernardo, Passerini, Andrea (2019) Ontology-based data access – Beyond relational sources. Intelligenza Artificiale, 13 (1). pp. 21-36. ISSN 1724-8035. E-ISSN 2211-0097. (doi:10.3233/IA-190023) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:90809)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
https://doi.org/10.3233/IA-190023

Abstract

The database (DB) landscape has been significantly diversified during the last decade, resulting in the emergence of a variety of non-relational (also called NoSQL) DBs, e.g., xml and json-document DBs, key-value stores, and graph DBs. To enable access to such data, we generalize the well-known ontology-based data access (OBDA) framework so as to allow for querying arbitrary data sources using sparql. We propose an architecture for a generalized OBDA system implementing the virtual approach. Then, to investigate feasibility of OBDA over non-relational DBs, we compare an implementation of an OBDA system over MongoDB, a popular json-document DB, with a triple store. This article is an extended and revised version of an article that appeared in the proceedings of the 17th International Conference of the Italian Association for Artificial Intelligence (AI*IA) [4].

Item Type: Article
DOI/Identification number: 10.3233/IA-190023
Uncontrolled keywords: Ontology-based data access; NoSQL; JSON; MongoDB; query optimization
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Amy Boaler
Date Deposited: 12 Oct 2021 08:47 UTC
Last Modified: 13 Oct 2021 10:26 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/90809 (The current URI for this page, for reference purposes)
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