Mapping Patterns for Virtual Knowledge Graphs

TL;DR

This paper introduces a comprehensive catalog of sophisticated mapping patterns for Virtual Knowledge Graphs, aiding in the management of data source-to-ontology mappings throughout their lifecycle.

Contribution

It extends established data management patterns to VKGs, validated on real-world benchmarks and use cases, addressing the impedance mismatch challenge.

Findings

Catalog covers most patterns in VKG scenarios

Validated on real-world benchmarks

Supports lifecycle management of mappings

Abstract

Virtual Knowledge Graphs (VKG) 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 mappings that link data sources to a domain ontology. To support the management of mappings throughout their entire lifecycle, we propose 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 patterns present therein.