Workshop Report: Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Harmonized Language.


Journal

International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455

Informations de publication

Date de publication:
28 01 2023
Historique:
received: 01 12 2022
revised: 20 01 2023
accepted: 25 01 2023
entrez: 11 2 2023
pubmed: 12 2 2023
medline: 15 2 2023
Statut: epublish

Résumé

Harmonized language is essential to finding, sharing, and reusing large-scale, complex data. Gaps and barriers prevent the adoption of harmonized language approaches in environmental health sciences (EHS). To address this, the National Institute of Environmental Health Sciences and partners created the Environmental Health Language Collaborative (EHLC). The purpose of EHLC is to facilitate a community-driven effort to advance the development and adoption of harmonized language approaches in EHS. EHLC is a forum to pinpoint language harmonization gaps, to facilitate the development of, raise awareness of, and encourage the use of harmonization approaches and tools, and to develop new standards and recommendations. To ensure that EHLC's focus and structure would be sustainable long-term and meet the needs of the field, EHLC launched an inaugural workshop in September 2021 focused on "Developing Sustainable Language Solutions" and "Building a Sustainable Community". When the attendees were surveyed, 91% said harmonized language solutions would be of high value/benefit, and 60% agreed to continue contributing to EHLC efforts. Based on workshop discussions, future activities will focus on targeted collaborative use-case working groups in addition to offering education and training on ontologies, metadata, and standards, and developing an EHS language resource portal.

Identifiants

pubmed: 36767684
pii: ijerph20032317
doi: 10.3390/ijerph20032317
pmc: PMC9915042
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Stephanie Holmgren (S)

Office of Data Science, National Institute of Environmental Health Sciences (NIEHS), Durham, NC 27709, USA.

Shannon M Bell (SM)

Research Triangle Institute, Durham, NC 27709, USA.

Jessica Wignall (J)

Health Sciences, ICF, Reston, VA 20190, USA.

Christopher G Duncan (CG)

Genes, Environment, and Health Branch, Division of Extramural Research and Training, National Institute of Environmental Health Sciences (NIEHS), Durham, NC 27709, USA.

Richard K Kwok (RK)

Division of Neuroscience, National Institute on Aging (NIA), Bethesda, MD 20892, USA.

Ryan Cronk (R)

Health Sciences, ICF, Reston, VA 20190, USA.

Kimberly Osborn (K)

Health Sciences, ICF, Reston, VA 20190, USA.

Steven Black (S)

Health Sciences, ICF, Reston, VA 20190, USA.

Anne Thessen (A)

Center for Health Artificial Intelligence, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.

Charles Schmitt (C)

Office of Data Science, National Institute of Environmental Health Sciences (NIEHS), Durham, NC 27709, USA.

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Classifications MeSH