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Knowledge Organization Systems for Systematic Chemical Assessments.

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Title: Knowledge Organization Systems for Systematic Chemical Assessments.
Authors: Whaley, Paul1,2, Edwards, Stephen W.3, Kraft, Andrew4, Nyhan, Kate5, Watford, Sean6, Wattam, Steve7, Wolffe, Taylor2, Angrish, Michelle8 angrish.michelle@epa.gov
Source: Environmental Health Perspectives. Dec2020, Vol. 128 Issue 12, p125001-1-125001-11. 11p. 4 Diagrams, 3 Charts.
Subject Terms: *Environmental health, Chemical safety, Information retrieval, Information science, Subject headings, Knowledge management, Access to information, Ontologies (Information retrieval)
Abstract: 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 assessmentrelevant 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. [ABSTRACT FROM AUTHOR]
Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Knowledge Organization Systems for Systematic Chemical Assessments.
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Health+Perspectives%22">Environmental Health Perspectives</searchLink>. Dec2020, Vol. 128 Issue 12, p125001-1-125001-11. 11p. 4 Diagrams, 3 Charts.
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  Data: *<searchLink fieldCode="DE" term="%22Environmental+health%22">Environmental health</searchLink><br /><searchLink fieldCode="DE" term="%22Chemical+safety%22">Chemical safety</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Information+science%22">Information science</searchLink><br /><searchLink fieldCode="DE" term="%22Subject+headings%22">Subject headings</searchLink><br /><searchLink fieldCode="DE" term="%22Knowledge+management%22">Knowledge management</searchLink><br /><searchLink fieldCode="DE" term="%22Access+to+information%22">Access to information</searchLink><br /><searchLink fieldCode="DE" term="%22Ontologies+%28Information+retrieval%29%22">Ontologies (Information retrieval)</searchLink>
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  Data: 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 assessmentrelevant 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Environmental Health Perspectives is the property of National Institute of Environmental Health Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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