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A change language for ontologies and knowledge graphs.

Harshad Hegde1, Jennifer Vendetti2, Damien Goutte-Gattat3

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Summary
This summary is machine-generated.

Managing changes in knowledge graphs (KGs) and ontologies is challenging. We developed the Knowledge Graph Change Language (KGCL) and tools to standardize and simplify KG and ontology evolution for diverse stakeholders.

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Area of Science:

  • Computer Science
  • Bioinformatics
  • Knowledge Representation

Background:

  • Ontologies and knowledge graphs (KGs) are vital for information systems but evolve over time.
  • Managing these dynamic changes presents challenges for users and contributors.
  • Standardized methods for tracking and applying KG/ontology updates are needed.

Purpose of the Study:

  • To introduce the Knowledge Graph Change Language (KGCL) as a standard data model for KG and ontology changes.
  • To provide a human-readable Controlled Natural Language (CNL) for KGCL.
  • To develop tools that facilitate the management and application of these changes.

Main Methods:

  • Developed KGCL, a high-level data model for describing changes to KGs and ontologies.
  • Created a Controlled Natural Language (CNL) for KGCL, enabling both change requests and descriptions of past changes.
  • Built automated tools, including a GitHub agent and a BioPortal component, for change management.

Main Results:

  • KGCL provides a standardized way to represent KG and ontology modifications.
  • The CNL allows for intuitive, human-readable change specifications (e.g., adding synonyms, restructuring hierarchies).
  • Integrated tools automate change application and facilitate user contributions via platforms like GitHub and BioPortal.

Conclusions:

  • KGCL, its CNL, and associated tooling simplify the management and processing of changes in ontologies and KGs.
  • This facilitates easier collaboration and evolution of complex knowledge structures.
  • The approach enhances the usability and maintainability of knowledge graphs and ontologies.