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

Area of Science:

• Environmental Health Sciences
• Bioinformatics
• Data Science

Background:

• Environmental health science (EHS) data availability is increasing, but semantic standards development has lagged.
• This hinders the integration and analysis of data crucial for modeling environmental influences on human health.

Purpose of the Study:

• To identify a community and mechanisms for developing EHS semantic standards.
• To advance the understanding of environmental exposures' impacts on human disease.

Main Methods:

• A workshop was convened by the National Institute of Environmental Health Sciences, bringing together data generators, users, publishers, and funders.
• The goal was to establish a foundation for community-based, data-driven EHS semantic standards.

Main Results:

• Creating and maintaining a common EHS language requires continuous community building.
• Integration and reuse of existing data, with low barriers to access, are essential.

Conclusions:

• Recommendations include a community-supported web-based toolkit.
• This toolkit should facilitate collaborative development of research questions, user-friendly tools, education on standards, and a governance plan.