Enhancing Virtual Ontology Based Access over Tabular Data with Morph-CSV

dc.bibliographicCitation.journalTitleSemantic Webeng
dc.contributor.authorChaves-Fraga, David
dc.contributor.authorRuckhaus, Edna
dc.contributor.authorPriyatna, Freddy
dc.contributor.authorVidal, Maria-Esther
dc.contributor.authorCorchio, Oscar
dc.date.accessioned2021-04-13T09:54:24Z
dc.date.available2021-04-13T09:54:24Z
dc.date.issued2020
dc.description.abstractOntology-Based Data Access (OBDA) has traditionally focused on providing a unified view of heterogeneous datasets, either by materializing integrated data into RDF or by performing on-the fly querying via SPARQL query translation. In the specific case of tabular datasets represented as several CSV or Excel files, query translation approaches have been applied by considering each source as a single table that can be loaded into a relational database management system (RDBMS). Nevertheless, constraints over these tables are not represented; thus, neither consistency among attributes nor indexes over tables are enforced. As a consequence, efficiency of the SPARQL-to-SQL translation process may be affected, as well as the completeness of the answers produced during the evaluation of the generated SQL query. Our work is focused on applying implicit constraints on the OBDA query translation process over tabular data. We propose Morph-CSV, a framework for querying tabular data that exploits information from typical OBDA inputs (e.g., mappings, queries) to enforce constraints that can be used together with any SPARQL-to-SQL OBDA engine. Morph-CSV relies on both a constraint component and a set of constraint operators. For a given set of constraints, the operators are applied to each type of constraint with the aim of enhancing query completeness and performance. We evaluate Morph-CSV in several domains: e-commerce with the BSBM benchmark; transportation with a benchmark using the GTFS dataset from the Madrid subway; and biology with a use case extracted from the Bio2RDF project. We compare and report the performance of two SPARQL-to-SQL OBDA engines, without and with the incorporation of MorphCSV. The observed results suggest that Morph-CSV is able to speed up the total query execution time by up to two orders of magnitude, while it is able to produce all the query answers.eng
dc.description.versionsubmittedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/6147
dc.identifier.urihttps://doi.org/10.34657/5195
dc.language.isoengeng
dc.publisherAmsterdam : IOS Presseng
dc.relation.doihttps://doi.org/10.3233/SW-210432
dc.relation.essn2210-4968
dc.relation.issn1570-0844
dc.relation.urihttps://arxiv.org/abs/2001.09052
dc.rights.licenseCC BY 4.0 Unportedeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/eng
dc.subject.ddc004eng
dc.subject.otherKnowledge graphseng
dc.subject.othertabular dataeng
dc.subject.othermapping languageseng
dc.subject.otherconstraintseng
dc.titleEnhancing Virtual Ontology Based Access over Tabular Data with Morph-CSVeng
dc.typeArticleeng
dc.typeTexteng
tib.accessRightsopenAccesseng
wgl.contributorTIBeng
wgl.subjectInformatikeng
wgl.typeZeitschriftenartikeleng
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