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Knowledge Organization Systems for Systematic Chemical Assessments
Citation:
Whaley, P., S. Edwards, A. Kraft, K. Nyhan, A. Shapiro, S. Watford, S. Wattman, T. Wolffe, AND M. Angrish. Knowledge Organization Systems for Systematic Chemical Assessments. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, , 1-11, (2020). https://doi.org/10.1289/EHP6994
Impact/Purpose:
This work describes how systematic methods combined with controlled vocabularies and ontologies can be used as a point of interoperability for the information and tools used in SR-guided chemical assessments. This work also exemplifies how systematic methods, controlled vocabularies, and ontologies can be applied in an AOP context and leveraged using computationally intelligent (AI) approaches.
Description:
Background: Although the implementation of systematic review and evidence mapping methods stands to improve the transparency and accuracy of chemical assessments, they also accentuate the challenges that assessors face in ensuring they have located and included all the evidence that is relevant to evaluating the potential health effects an exposure might be causing. This challenge of information retrieval can be characterized in terms of “semantic” and “conceptual” factors that render chemical assessments vulnerable to the streetlight effect. Objectives: This commentary presents how controlled vocabularies, thesauruses, and ontologies contribute to overcoming the streetlight effect in information retrieval, making up the key components of Knowledge Organization Systems (KOSs) that enable more systematic access to assessment-relevant information than is currently achievable. The concept of Adverse Outcome Pathways is used to illustrate what a general KOS for use in chemical assessment could look like. Discussion: Ontologies are an underexploited element of effective knowledge organization in the environmental health sciences. Agreeing on and implementing ontologies in chemical assessment is a complex but tractable process with four fundamental steps. Successful implementation of ontologies would not only make currently fragmented information about health risks from chemical exposures vastly more accessible, it could ultimately enable computational methods for chemical assessment that can take advantage of the full richness of data described in natural language in primary studies.
