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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.<\/jats:p>","DOI":"10.3233\/ao-210260","type":"journal-article","created":{"date-parts":[[2022,1,7]],"date-time":"2022-01-07T11:40:35Z","timestamp":1641555635000},"page":"321-336","source":"Crossref","is-referenced-by-count":4,"title":["Evaluating and extending the Informed Consent Ontology for representing permissions from the clinical domain"],"prefix":"10.1177","volume":"17","author":[{"given":"Elizabeth E.","family":"Umberfield","sequence":"first","affiliation":[{"name":"Health Policy & Management, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA"},{"name":"Center for Biomedical Informatics, Regenstrief Institute Inc., Indianapolis, IN, USA. 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