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This work has received funding from the INESData project (Infrastructure to Investigate Data Spaces in Distributed Environments at UPM) , a project funded under the UNICO I+D CLOUD call by the Spanish Ministry for Digital Transformation and the Civil Service, within the framework of the recovery plan PRTR financed by the European Union (NextGenerationEU) .

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Intermediate triple table: A general architecture for virtual knowledge graphs

Publicado en:Knowledge-Based Systems. 314 113179- - 2025-04-08 314(), DOI: 10.1016/j.knosys.2025.113179

Autores: Arenas-Guerrero, Julian; Corcho, Oscar; Perez, Maria S

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Resumen

Virtual knowledge graphs (VKGs) have been widely applied to access relational data with a semantic layer by using an ontology in use cases that are dynamic in nature. However, current VKG techniques focus mainly on accessing a single relational database and remain largely unstudied for data integration with several heterogeneous data sources. To overcome this limitation, we propose intermediate triple table (ITT), a general VKG architecture to access multiple and diverse data sources. Our proposal is based on data shipping and addresses heterogeneity by adopting a schema-oblivious graph representation that intervenes between the sources and the queries. We minimize data computation by just materializing a relevant subgraph fora specific query. We employ star-shaped query processing and extend this technique to mapping candidate selection. For rapid materialization of the ITT, we apply a mapping partitioning technique to parallelize mapping execution, which also guarantees duplicate-free subgraphs and reduces memory consumption. We use SPARQL-to-SQL query translation to homogeneously evaluate queries over the ITT and execute them with an in-process analytical store. We implemented ITT on top of a knowledge graph materialization engine and evaluated it with two VKG benchmarks. The experimental results show that our proposal outperforms state-of-the-art techniques for complex graph queries in terms of execution time. It also decreases the number of timeouts although it uses more memory as a trade-off. The experiments also demonstrate the source independence of the architecture on a mixed distribution of data with SQL and document stores together with various file formats.

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