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Expressing and Executing Informed Consent Permissions Using SWRL: The All of Us Use Case.

Muhammad Amith1,2, Marcelline R Harris3,2, Cooper Stansbury3

  • 1School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|March 21, 2022
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Summary
This summary is machine-generated.

This study uses Semantic Web Rule Language (SWRL) to enhance the Informed Consent Ontology (ICO), enabling machine reasoning for managing research permissions. This improves data accessibility for stakeholders in biomedical research.

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Area of Science:

  • Biomedical Informatics
  • Semantic Web Technologies
  • Ontology Engineering

Background:

  • The informed consent process is complex, involving numerous entities and actions.
  • Managing and accessing permission-based information can be challenging for stakeholders.
  • Existing ontologies may lack the expressiveness for automated reasoning.

Purpose of the Study:

  • To extend the Informed Consent Ontology (ICO) using Semantic Web Rule Language (SWRL).
  • To enable semantic machine-based reasoning for managing and generating permission-based information.
  • To demonstrate the utility of SWRL in inferring implicit information within informed consent documents.

Main Methods:

  • Utilized Semantic Web Rule Language (SWRL) to extend the Informed Consent Ontology (ICO).
  • Developed SWRL expressions for four use cases of permissions from the 'All of Us' informed consent document.
  • Applied rule-based reasoning to operationalize and infer information from the ICO.

Main Results:

  • SWRL successfully extended ICO, enabling machine-based reasoning for permission management.
  • Demonstrated the ability of SWRL to infer implicit information based on defined rules.
  • Validated the utility of ICO through SWRL extensions with practical use cases.

Conclusions:

  • SWRL is effective for enhancing ontologies like ICO to support automated reasoning in informed consent.
  • The extended ICO facilitates better management and accessibility of permission-related data.
  • Future work includes comprehensive rule development and integration into research software systems.