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Accessing scientific data through knowledge graphs with Ontop.

Diego Calvanese1,2,3, Davide Lanti1, Tarcisio Mendes De Farias4,5

  • 1Faculty of Computer Science, Free University of Bozen-Bolzano, 39100 Bolzano, Italy.

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PubMed
Summary
This summary is machine-generated.

This tutorial introduces the virtual knowledge graph (VKG) approach for accessing legacy data and enriching it with biomedical knowledge. VKG simplifies data access by using ontologies, abstracting away complex storage details for users.

Keywords:
biomedical datadata integrationontology languageontology-based data accessvirtual knowledge graphs

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Area of Science:

  • Computer Science
  • Bioinformatics
  • Data Management

Background:

  • Relational legacy systems often contain valuable data but are difficult to access and integrate.
  • Heterogeneous biomedical resources require sophisticated methods for knowledge enrichment.
  • Existing data access methods may lack a user-friendly conceptual view and domain knowledge integration.

Purpose of the Study:

  • To provide a tutorial on setting up and exploiting the virtual knowledge graph (VKG) approach.
  • To demonstrate how VKG facilitates access to data in relational legacy systems.
  • To showcase the enrichment of data with domain knowledge from diverse biomedical resources.

Main Methods:

  • The virtual knowledge graph (VKG) approach is utilized.
  • An ontology is employed to describe the domain of interest and provide a conceptual data view.
  • Users interact with the data through this high-level conceptual view, abstracting low-level storage details.
  • Ontologies from different sources are integrated.

Main Results:

  • Users can access data from relational legacy systems without needing to understand underlying storage complexities.
  • Data is enriched with domain knowledge from heterogeneous biomedical resources.
  • Richer and more comprehensive answers are obtained through the interaction of data and domain knowledge.
  • The VKG approach simplifies the integration of diverse data and knowledge sources.

Conclusions:

  • The virtual knowledge graph (VKG) approach offers a powerful method for accessing and integrating data from legacy systems.
  • VKG enhances data utility by enabling seamless enrichment with domain-specific knowledge.
  • This approach democratizes data access by providing a user-friendly conceptual interface, crucial for biomedical research and data management.