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OBG-gen: Ontology-Based GraphQL Server Generation for Data Integration
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University.ORCID iD: 0000-0003-1881-3969
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-1741-2090
Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University.ORCID iD: 0000-0002-5571-0814
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. The Swedish e-Science Research Centre, Linköping University.ORCID iD: 0000-0002-9084-0470
2023 (English)In: Proceedings of the ISWC 2023 Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice: co-located with 22nd International Semantic Web Conference (ISWC 2023) / [ed] Irini Fundulaki, Kouji Kozaki, Daniel Garijo, Jose Manuel Gomez-Perez, 2023Conference paper, Published paper (Refereed)
Abstract [en]

A GraphQL server contains two building blocks: (1) a GraphQL schema defining the types of data objects that can be requested; (2) resolver functions fetching the relevant data from underlying data sources. GraphQL can be used for data integration if the GraphQL schema provides an integrated view of data from multiple data sources, and the resolver functions are implemented accordingly.However, there does not exist a semantics-aware approach to use GraphQL for data integration.We proposed a framework using GraphQL for data integration in which a global domain ontology informs the generation of a GraphQL server. Furthermore, we implemented a prototype of this framework, OBG-gen. In this paper, we demonstrate OBG-gen in a real-world data integration scenario in the materials design domain and in  a synthetic benchmark scenario.

Place, publisher, year, edition, pages
2023.
Series
CEUR Workshop Proceedings, ISSN 1613-0073 ; 3632
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-198287OAI: oai:DiVA.org:liu-198287DiVA, id: diva2:1801993
Conference
22nd International Semantic Web Conference, November 6–10, 2023, Athens, Greece
Funder
Swedish e‐Science Research CenterSwedish Agency for Economic and Regional GrowthCUGS (National Graduate School in Computer Science)Available from: 2023-10-03 Created: 2023-10-03 Last updated: 2024-02-02

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Li, HuanyuHartig, OlafArmiento, RickardLambrix, Patrick

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