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dc.contributor.authorO'Mahony, C.
dc.contributor.authorArmstrong, T.
dc.contributor.authorLaKind, Judy S.
dc.date.accessioned2019-03-29T14:42:02Z
dc.date.available2019-03-29T14:42:02Z
dc.date.issued2019
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85060719306&doi=10.1016%2fj.envres.2019.01.039&partnerID=40&md5=504c9b51efed498b65c07e3a0b9e1df9
dc.identifier.urihttp://hdl.handle.net/10713/8594
dc.description.abstractRecent rapid technological advances are producing exposure data sets for which there are no available data quality assessment tools. At the same time, regulatory agencies are moving in the direction of data quality assessment for environmental risk assessment and decision-making. A transparent and systematic approach to evaluating exposure data will aid in those efforts. Any approach to assessing data quality must consider the level of quality needed for the ultimate use of the data. While various fields have developed approaches to assess data quality, there is as yet no general, user-friendly approach to assess both measured and modeled data in the context of a fit-for-purpose risk assessment. Here we describe ExpoQual, an instrument developed for this purpose which applies recognized parameters and exposure data quality elements from existing approaches for assessing exposure data quality. Broad data streams such as quantitative measured and modeled human exposure data as well as newer and developing approaches can be evaluated. The key strength of ExpoQual is that it facilitates a structured, reproducible and transparent approach to exposure data quality evaluation and provides for an explicit fit-for-purpose determination. ExpoQual was designed to minimize subjectivity and to include transparency in aspects based on professional judgment. ExpoQual is freely available on-line for testing and user feedback (exposurequality.com). © 2019en_US
dc.description.sponsorshipJSL, CO and TA received support by the American Chemistry Council's (ACC) Center for Advancing Risk Assessment and Science Policy (ARASP). ACC/ARASP was not involved in the design, collection, management, analysis, or interpretation of the data; or in the preparation or approval of the manuscript. JSL and TA consult to both governmental and private concerns. RT is employed by ExxonMobil Biomedical Sciences and declares no conflict of interest relating to the material presented in this article; its contents, including any opinions and/or conclusions expressed, are solely those of the author. BB and DQN declare no potential conflicts of interest. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention, Johns Hopkins University, Creme Global or ExxonMobil Biomedical Sciences.en_US
dc.description.urihttps://dx.doi.org/10.1016/j.envres.2019.01.039en_US
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.relation.ispartofEnvironmental Research
dc.subjectBEES-Cen_US
dc.subjectbiomonitoringen_US
dc.subjectExpoQualen_US
dc.subjectexposureen_US
dc.subjectfit-for-purposeen_US
dc.subjectinstrumenten_US
dc.subjectmodel uncertaintyen_US
dc.subjectqualityen_US
dc.subject.meshHumansen_US
dc.titleExpoQual: Evaluating measured and modeled human exposure dataen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.envres.2019.01.039
dc.identifier.pmid30708234


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