Conceptually-grounded mapping patterns for Virtual Knowledge GraphsShow others and affiliations
2023 (English)In: Data & Knowledge Engineering, ISSN 0169-023X, E-ISSN 1872-6933, Vol. 145, article id 102157Article in journal (Refereed) Published
Abstract [en]
Virtual Knowledge Graphs (VKGs) constitute one of the most promising paradigms for integrating and accessing legacy data sources. A critical bottleneck in the integration process involves the definition, validation, and maintenance of mapping assertions that link data sources to a domain ontology. To support the management of mappings throughout their entire lifecycle, we identify a comprehensive catalog of sophisticated mapping patterns that emerge when linking databases to ontologies. To do so, we build on well-established methodologies and patterns studied in data management, data analysis, and conceptual modeling. These are extended and refined through the analysis of concrete VKG benchmarks and real-world use cases, and considering the inherent impedance mismatch between data sources and ontologies. We validate our catalog on the considered VKG scenarios, showing that it covers the vast majority of mappings present therein.
Place, publisher, year, edition, pages
Elsevier, 2023. Vol. 145, article id 102157
Keywords [en]
Data integration, Mapping patterns, Ontology-based data access, Virtual knowledge graphs
National Category
Computer Sciences Computer Systems
Identifiers
URN: urn:nbn:se:umu:diva-206015DOI: 10.1016/j.datak.2023.102157ISI: 000957798500001Scopus ID: 2-s2.0-85150258864OAI: oai:DiVA.org:umu-206015DiVA, id: diva2:1746358
Funder
EU, Horizon 2020, 863410Wallenberg AI, Autonomous Systems and Software Program (WASP)Knut and Alice Wallenberg Foundation2023-03-282023-03-282023-09-05Bibliographically approved