Enhancing Semantic Interoperability in Environmental Health Sciences Research
Submitted by Stephanie Holmgren
- To introduce a prospective Environmental Health Sciences Semantic Interoperability IG to the RDA community
- To assess the relevance and interest for the proposed IG within the RDA community
- To obtain feedback and input on the next steps from the RDA community
- To network among the researchers, industrial members, and related RDA groups interested in discussing and advancing this topic
Collaborative meeting notes:
The Nature of Environmental Health Sciences Research, Gwen Collman, National Institute of Environmental Health Sciences
Brief overview of the breadth of environmental health studies and generated data type
The Value of Standardized EHS Terminologies
How terminologies are being applied to advance EHS research. Presenters will also address the challenges they overcame and/or that still remain.
- Ontology-driven approaches to adverse outcome pathway development and use (Stephen Edwards, RTI International)
- Moving toward a single ontology in land use science, climate change, and epidemiology (Bill Pan, Duke University)
- Knowledge modelling and data harmonization across diverse environmental health studies: Experiences from the HHEAR Data Center (Jeanette Stingone, Columbia University)
- Towards metadata FAIRification in European Human Exposome Network (EHEN) (Morris Swertz, University Medical Center Groningen)
Brief Presentation Q&A
Aims of the Prospective RDA Interest Group
- Road to RDA
- Draft goals for the IG
- Draft elements of charter
- Present use cases
- Gauge level of interest to form EHS IG
- Feedback on draft goals and charter elements
- How best to coordinate the EHS IG with other RDA domain and cross-cutting groups
Even with the promise of modern genomics, our ability to understand human disease and realize precision health is limited without considering the effect of the environment. Achieving integration of phenotype, genotype, and environmental information will require an extensive translation of data into a computable form and the extension of the gene/phenotype data model.
Unfortunately, environmental health and toxicology data remain extremely difficult to search, integrate, and compute upon—not only due to the complexity but also the lack of convergence on standards and terminologies. Development of the standards for associating environmental exposures to phenotypic outcomes and the associated metadata is a vast undertaking that requires substantial community engagement. Despite advances such as the Exposure Ontology (ExO), the Environmental Conditions, Treatments, and Exposures Ontology (ECTO), more work is needed, particularly in implementing the sociological aspects of community-driven standards development.
A few workshops have been held in the past few years to mobilize the community around standards development and a strategy for toxicology ontology development has been proposed. See the recommended links for further information on these efforts.
This BoF proposal is a first step towards creating a sustainable community to support the need for not only awareness and coordination, but also the development and adoption of standards in fostering environmental health data access, interoperability, and reuse. RDA provides a unique forum to coordinate with other international efforts underway to develop toxicological, exposome, and other environmental health ontologies and standards. Furthermore, the objectives of several RDA cross-cutting (vocabulary services, metadata, ...) and domain-specific (earth sciences, ELIXIR, chemistry, health data, ...) interest groups align with our objectives and would be worthwhile collaborators on specific goals.
1. Boyles RR, Thessen AE, and Haendel MA (2019). Ontology-based data integration for advancing toxicological knowledge. Current Opinion in Toxicology. 16: 67-74. https://doi.org/10.1016/j.cotox.2019.05.005.
2. Hardy B, Apic G, Carthew P, et al. (2012). A toxicology ontology roadmap. ALTEX. 29(20): 129-37. https://doi.org/10.14573/altex.2012.2.129
3. Mattingly CJ, Boyles R, Lawler CP, et al. (2016). Laying a community-based foundation for data-driven semantic standards in environmental health sciences. Environmental Health Perspectives. 124: 1136-1140. https://dx.doi.org/10.1289/ehp.1510438.
4. Thessen AE, Grondin CJ, Kulkarni RD, et al. (2020). Community approaches for integrating environmental exposures into human models of disease. Environmental Health Perspectives. 128(12): 125002. https://dx.doi.org/10.1289/EHP7215.
5. Whaley P. Edwards SW, Kraft A., et al. (2020). Knowledge organization systems for systematic chemical assessments. Environmental Health Perspectives. https://doi.org/10.1289/EHP6994.
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