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Laying a Community-Based Foundation for Data-Driven Semantic Standards in Environmental Health Sciences. | LitMetric

AI Article Synopsis

  • There is a growing amount of environmental health science data, but creating effective semantic standards has not kept pace, making it difficult to analyze how environmental factors impact human health.
  • The National Institute of Environmental Health Sciences held a workshop to bring together various stakeholders to discuss the creation of a framework for EHS language, aiming to enhance data standardization and sharing.
  • The ongoing development of a common EHS language requires community involvement, resource accessibility, and the establishment of a web-based toolkit to support collaborative research efforts and educational resources.

Article Abstract

Background: Despite increasing availability of environmental health science (EHS) data, development, and implementation of relevant semantic standards, such as ontologies or hierarchical vocabularies, has lagged. Consequently, integration and analysis of information needed to better model environmental influences on human health remains a significant challenge.

Objectives: We aimed to identify a committed community and mechanisms needed to develop EHS semantic standards that will advance understanding about the impacts of environmental exposures on human disease.

Methods: The National Institute of Environmental Health Sciences sponsored the "Workshop for the Development of a Framework for Environmental Health Science Language" hosted at North Carolina State University on 15-16 September 2014. Through the assembly of data generators, users, publishers, and funders, we aimed to develop a foundation for enabling the development of community-based and data-driven standards that will ultimately improve standardization, sharing, and interoperability of EHS information.

Discussion: Creating and maintaining an EHS common language is a continuous and iterative process, requiring community building around research interests and needs, enabling integration and reuse of existing data, and providing a low barrier of access for researchers needing to use or extend such a resource.

Conclusions: Recommendations included developing a community-supported web-based toolkit that would enable a) collaborative development of EHS research questions and use cases, b) construction of user-friendly tools for searching and extending existing semantic resources, c) education and guidance about standards and their implementation, and d) creation of a plan for governance and sustainability.

Citation: Mattingly CJ, Boyles R, Lawler CP, Haugen AC, Dearry A, Haendel M. 2016. Laying a community-based foundation for data-driven semantic standards in environmental health sciences. Environ Health Perspect 124:1136-1140; http://dx.doi.org/10.1289/ehp.1510438.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4977056PMC
http://dx.doi.org/10.1289/ehp.1510438DOI Listing

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