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Evaluating and extending the Informed Consent Ontology for representing permissions from the clinical domain

  • Elizabeth E. Umberfield
  • , Cooper Stansbury
  • , Kathleen Ford
  • , Yun Jiang
  • , Sharon L.R. Kardia
  • , Andrea K. Thomer
  • , Marcelline R. Harris

Research output: Contribution to journalArticlepeer-review

Abstract

The purpose of this study was to evaluate, revise, and extend the Informed Consent Ontology (ICO) for expressing clinical permissions, including reuse of residual clinical biospecimens and health data. This study followed a formative evaluation design and used a bottom-up modeling approach. Data were collected from the literature on US federal regulations and a study of clinical consent forms. Eleven federal regulations and fifteen permission-sentences from clinical consent forms were iteratively modeled to identify entities and their relationships, followed by community reflection and negotiation based on a series of predetermined evaluation questions. ICO included fifty-two classes and twelve object properties necessary when modeling, demonstrating appropriateness of extending ICO for the clinical domain. Twenty-six additional classes were imported into ICO from other ontologies, and twelve new classes were recommended for development. This work addresses a critical gap in formally representing permissions clinical permissions, including reuse of residual clinical biospecimens and health data. It makes missing content available to the OBO Foundry, enabling use alongside other widely-adopted biomedical ontologies. ICO serves as a machine-interpretable and interoperable tool for responsible reuse of residual clinical biospecimens and health data at scale.

Original languageEnglish (US)
Pages (from-to)321-336
Number of pages16
JournalApplied Ontology
Volume17
Issue number2
DOIs
StatePublished - 2022
Externally publishedYes

Keywords

  • biological specimen banks
  • evaluation study
  • informatics
  • informed consent
  • Knowledge bases

ASJC Scopus subject areas

  • General Computer Science
  • Language and Linguistics
  • Linguistics and Language

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