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RODI: Benchmarking relational-to-ontology mapping generation quality

Pinkel, Christoph ; Binnig, Carsten ; Jimenez-Ruiz, Ernesto ; Kharlamov, Evgeny ; May, Wolfgang ; Nikolov, Andriy ; Sasa Bastinos, Ana ; Skjæveland, Martin G. ; Solimando, Alessandro ; Taheriyan, Mohsen ; Heupel, Christian ; Horrocks, Ian (2018)
RODI: Benchmarking relational-to-ontology mapping generation quality.
In: Semantic Web, 9 (1)
doi: 10.3233/SW-170268
Artikel, Bibliographie

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Kurzbeschreibung (Abstract)

Accessing and utilizing enterprise or Web data that is scattered across multiple data sources is an important task for both applications and users. Ontology-based data integration, where an ontology mediates between the raw data and its consumers, is a promising approach to facilitate such scenarios. This approach crucially relies on useful mappings to relate the ontology and the data, the latter being typically stored in relational databases. A number of systems to support the construction of such mappings have recently been developed. A generic and effective benchmark for reliable and comparable evaluation of the practical utility of such systems would make an important contribution to the development of ontology-based data integration systems and their application in practice. We have proposed such a benchmark, called RODI. In this paper, we present a new version of RODI, which significantly extends our previous benchmark, and we evaluate various systems with it. RODI includes test scenarios from the domains of scientific conferences, geographical data, and oil and gas exploration. Scenarios are constituted of databases, ontologies, and queries to test expected results. Systems that compute relational-to-ontology mappings can be evaluated using RODI by checking how well they can handle various features of relational schemas and ontologies, and how well the computed mappings work for query answering. Using RODI, we conducted a comprehensive evaluation of seven systems.

Typ des Eintrags: Artikel
Erschienen: 2018
Autor(en): Pinkel, Christoph ; Binnig, Carsten ; Jimenez-Ruiz, Ernesto ; Kharlamov, Evgeny ; May, Wolfgang ; Nikolov, Andriy ; Sasa Bastinos, Ana ; Skjæveland, Martin G. ; Solimando, Alessandro ; Taheriyan, Mohsen ; Heupel, Christian ; Horrocks, Ian
Art des Eintrags: Bibliographie
Titel: RODI: Benchmarking relational-to-ontology mapping generation quality
Sprache: Englisch
Publikationsjahr: 1 Januar 2018
Verlag: IOS Press
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Semantic Web
Jahrgang/Volume einer Zeitschrift: 9
(Heft-)Nummer: 1
DOI: 10.3233/SW-170268
Kurzbeschreibung (Abstract):

Accessing and utilizing enterprise or Web data that is scattered across multiple data sources is an important task for both applications and users. Ontology-based data integration, where an ontology mediates between the raw data and its consumers, is a promising approach to facilitate such scenarios. This approach crucially relies on useful mappings to relate the ontology and the data, the latter being typically stored in relational databases. A number of systems to support the construction of such mappings have recently been developed. A generic and effective benchmark for reliable and comparable evaluation of the practical utility of such systems would make an important contribution to the development of ontology-based data integration systems and their application in practice. We have proposed such a benchmark, called RODI. In this paper, we present a new version of RODI, which significantly extends our previous benchmark, and we evaluate various systems with it. RODI includes test scenarios from the domains of scientific conferences, geographical data, and oil and gas exploration. Scenarios are constituted of databases, ontologies, and queries to test expected results. Systems that compute relational-to-ontology mappings can be evaluated using RODI by checking how well they can handle various features of relational schemas and ontologies, and how well the computed mappings work for query answering. Using RODI, we conducted a comprehensive evaluation of seven systems.

Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Data Management (2022 umbenannt in Data and AI Systems)
Hinterlegungsdatum: 26 Feb 2020 10:03
Letzte Änderung: 29 Mai 2024 10:09
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