ArticleEnvironmental health perspectives2016
Laying a Community-Based Foundation for Data-Driven Semantic Standards in Environmental Health Sciences.
Article in Environmental health perspectives, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 25 citations in OpenAlex.
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- FAIR environmental and health registry (FAIREHR)- supporting the science to policy interface and life science research, development and innovation.Frontiers in toxicology · 2023Article
- Implementation of Zebrafish Ontologies for Toxicology Screening.Frontiers in toxicology · 2022Article
- Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized Language.International journal of environmental research and public health · 2021Article
- Semantic standards of external exposome data.Environmental research · 2021Review
- Community Approaches for Integrating Environmental Exposures into Human Models of Disease.Environmental health perspectives · 2020Article
- Integration of curated and high-throughput screening data to elucidate environmental influences on disease pathways.Computational toxicology (Amsterdam, Netherlands) · 2019Article
- The Comparative Toxicogenomics Database: update 2019.Nucleic acids research · 2019Article
- Creating a Structured AOP Knowledgebase via Ontology-Based Annotations.Applied in vitro toxicology · 2017Article
- Community-based participatory research for the study of air pollution: a review of motivations, approaches, and outcomes.Environmental monitoring and assessment · 2017Review
- The Comparative Toxicogenomics Database: update 2017.Nucleic acids research · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundDespite 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.
objectivesWe 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.
methodsThe 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.
conclusionsRecommendations 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.