Projects
Our standards development efforts target key gaps in data interoperability across the source-to-outcome (S2O) continuum. Working with subject matter experts and stakeholder communities, we are expanding the Biolink Model and related frameworks to better represent chemical fate, exposure, dosimetry, and health outcome data in a way that supports integrated, machine-readable analyses.
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A LinkML schema for representing Key Event and Outcome measurements, assays, and experimental protocols in the context of environmental health sciences (EHS) outcomes research.
A LinkML-based data model schema, developed through expert working group engagement, is applied to a PM₂.₅ Adverse Outcome Pathway Bayesian Network to demonstrate probabilistic prediction of mechanistic key events.
A preliminary Adverse Outcome Pathway Bayesian Network linking PM₂.₅ exposure to decreased lung function is developed as a quantitative test system for evaluating data interoperability standards.
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A phased, community-driven approach to developing and testing Biolink Model standards across environmental health science subdomains, demonstrated through a PM₂.₅ pilot use case with synthetic population modelling.
A coordinated effort to expand data standards and terminologies across environmental health science subdomains to improve interoperability along the source-to-outcome continuum.
