Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized Language
Harmonized language is critical for helping researchers to find data, collecting scientific data to facilitate comparison, and performing pooled and meta-analyses. Using standard terms to link data to knowledge systems facilitates knowledge-driven analysis, allows for the use of biomedical knowledge...
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doaj-436b579fe8f644cca6afa3e687a0868b2021-09-09T13:44:32ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012021-08-01188985898510.3390/ijerph18178985Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized LanguageStephanie D. Holmgren0Rebecca R. Boyles1Ryan D. Cronk2Christopher G. Duncan3Richard K. Kwok4Ruth M. Lunn5Kimberly C. Osborn6Anne E. Thessen7Charles P. Schmitt8Office of Data Science, National Institute of Environmental Health Sciences (NIEHS), Durham, NC 27709, USAResearch Computing, RTI International, Durham, NC 27709, USAHealth Sciences, ICF, Durham, NC 27713, USAGenes, Environment, and Health Branch, Division of Extramural Research and Training, NIEHS, Durham, NC 27709, USAEpidemiology Branch, Division of Intramural Research, NIEHS, Durham, NC 27709, USAIntegrative Health Assessment Branch, Division of the National Toxicology Program, NIEHS, Durham, NC 27709, USAHealth Sciences, ICF, Fairfax, VA 22031, USAEnvironmental and Molecular Toxicology Department, Oregon State University, Corvallis, OR 97331, USAOffice of Data Science, National Institute of Environmental Health Sciences (NIEHS), Durham, NC 27709, USAHarmonized language is critical for helping researchers to find data, collecting scientific data to facilitate comparison, and performing pooled and meta-analyses. Using standard terms to link data to knowledge systems facilitates knowledge-driven analysis, allows for the use of biomedical knowledge bases for scientific interpretation and hypothesis generation, and increasingly supports artificial intelligence (AI) and machine learning. Due to the breadth of environmental health sciences (EHS) research and the continuous evolution in scientific methods, the gaps in standard terminologies, vocabularies, ontologies, and related tools hamper the capabilities to address large-scale, complex EHS research questions that require the integration of disparate data and knowledge sources. The results of prior workshops to advance a harmonized environmental health language demonstrate that future efforts should be sustained and grounded in scientific need. We describe a community initiative whose mission was to advance integrative environmental health sciences research via the development and adoption of a harmonized language. The products, outcomes, and recommendations developed and endorsed by this community are expected to enhance data collection and management efforts for NIEHS and the EHS community, making data more findable and interoperable. This initiative will provide a community of practice space to exchange information and expertise, be a coordination hub for identifying and prioritizing activities, and a collaboration platform for the development and adoption of semantic solutions. We encourage anyone interested in advancing this mission to engage in this community.https://www.mdpi.com/1660-4601/18/17/8985community of practicecommunity-drivencontrolled vocabularymetadatataxonomyontology |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Stephanie D. Holmgren Rebecca R. Boyles Ryan D. Cronk Christopher G. Duncan Richard K. Kwok Ruth M. Lunn Kimberly C. Osborn Anne E. Thessen Charles P. Schmitt |
spellingShingle |
Stephanie D. Holmgren Rebecca R. Boyles Ryan D. Cronk Christopher G. Duncan Richard K. Kwok Ruth M. Lunn Kimberly C. Osborn Anne E. Thessen Charles P. Schmitt Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized Language International Journal of Environmental Research and Public Health community of practice community-driven controlled vocabulary metadata taxonomy ontology |
author_facet |
Stephanie D. Holmgren Rebecca R. Boyles Ryan D. Cronk Christopher G. Duncan Richard K. Kwok Ruth M. Lunn Kimberly C. Osborn Anne E. Thessen Charles P. Schmitt |
author_sort |
Stephanie D. Holmgren |
title |
Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized Language |
title_short |
Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized Language |
title_full |
Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized Language |
title_fullStr |
Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized Language |
title_full_unstemmed |
Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized Language |
title_sort |
catalyzing knowledge-driven discovery in environmental health sciences through a community-driven harmonized language |
publisher |
MDPI AG |
series |
International Journal of Environmental Research and Public Health |
issn |
1661-7827 1660-4601 |
publishDate |
2021-08-01 |
description |
Harmonized language is critical for helping researchers to find data, collecting scientific data to facilitate comparison, and performing pooled and meta-analyses. Using standard terms to link data to knowledge systems facilitates knowledge-driven analysis, allows for the use of biomedical knowledge bases for scientific interpretation and hypothesis generation, and increasingly supports artificial intelligence (AI) and machine learning. Due to the breadth of environmental health sciences (EHS) research and the continuous evolution in scientific methods, the gaps in standard terminologies, vocabularies, ontologies, and related tools hamper the capabilities to address large-scale, complex EHS research questions that require the integration of disparate data and knowledge sources. The results of prior workshops to advance a harmonized environmental health language demonstrate that future efforts should be sustained and grounded in scientific need. We describe a community initiative whose mission was to advance integrative environmental health sciences research via the development and adoption of a harmonized language. The products, outcomes, and recommendations developed and endorsed by this community are expected to enhance data collection and management efforts for NIEHS and the EHS community, making data more findable and interoperable. This initiative will provide a community of practice space to exchange information and expertise, be a coordination hub for identifying and prioritizing activities, and a collaboration platform for the development and adoption of semantic solutions. We encourage anyone interested in advancing this mission to engage in this community. |
topic |
community of practice community-driven controlled vocabulary metadata taxonomy ontology |
url |
https://www.mdpi.com/1660-4601/18/17/8985 |
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