Conceptually-grounded Mapping Patterns for Virtual Knowledge Graphs

Diego Calvanese, Avigdor Gal, Davide Lanti, Marco Montali, Alessandro Mosca, and Roee Shraga

Data and Knowledge Engineering. 145:102157 2023.

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.


@article{DKE-2023,
   title = "Conceptually-grounded Mapping Patterns for Virtual Knowledge
Graphs",
   year = "2023",
   author = "Diego Calvanese and Avigdor Gal and Davide Lanti and Marco
Montali and Alessandro Mosca and Roee Shraga",
   journal = "Data and Knowledge Engineering",
   pages = "102157",
   volume = "145",
   doi = "10.1016/j.datak.2023.102157",
}
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