title: Building a Human Health Risk Assessment Ontology (RsO): A Proposed Framework.
abstract: Over the last decade the health and environmental research communities have made significant progress in collecting and improving access to genomic, toxicology, exposure, health, and disease data useful to health risk assessment. One of the barriers to applying these growing volumes of information in fields such as risk assessment is the lack of informatics tools to organize, curate, and evaluate thousands of journal publications and hundreds of databases to provide new insights on relationships among exposure, hazard, and disease burden. Many fields are developing ontologies as a way of organizing and analyzing large amounts of complex information from multiple scientific disciplines. Ontologies include a vocabulary of terms and concepts with defined logical relationships to each other. Building from the recently published exposure ontology and other relevant health and environmental ontologies, this article proposes an ontology for health risk assessment (RsO) that provides a structural framework for organizing risk assessment information and methods. The RsO is anchored by eight major concepts that were either identified by exploratory curations of the risk literature or the exposure-ontology working group as key for describing the risk assessment domain. These concepts are: (1) stressor, (2) receptor, (3) outcome, (4) exposure event, (5) dose-response approach, (6) dose-response metric, (7) uncertainty, and (8) measure of risk. We illustrate the utility of these concepts for the RsO with example curations of published risk assessments for ionizing radiation, arsenic in drinking water, and persistent pollutants in salmon.
authors.affiliation: University of California, School of Public Health, Berkeley, CA, USA.|University of California, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
authors.forename: Thomas E
authors.initials: TE
authors.lastname: McKone
authors.affiliation: University of California, School of Public Health, Berkeley, CA, USA.
authors.forename: Lydia
authors.initials: L
authors.lastname: Feng
mesh_terms: D006801:Humans; D018570:Risk Assessment; D035501:Uncertainty
keywords: Dose response; exposure; measure of risk; ontology; receptor; stressor; uncertainty