Citation:

Mortensen, H., M. Martens, J. Senn, T. Levey, C. Evelo, E. Willighagan, AND T. Exner. The AOP-DB RDF: Applying FAIR Principles to the Semantic Integration of AOP Data Integration using the Research Description Framework. Frontiers in Toxicology. Frontiers, Lausanne, Switzerland, 4(803983):1, (2022). https://doi.org/10.3389/ftox.2022.803983

Impact/Purpose:

As part of OpenRiskNet, a 3-year project supported by the European Commission within Horizon2020 EINFRA-22-2016, the US EPA Adverse Outcome Pathway Database (AOP-DB) was selected as an Implementation Challenge winner. The Implementation Challenge was created to select external tools for use in risk assessment to be prioritized for integration in the OpenRiskNet e-Infrastructure [https://openrisknet.org/], and foster collaborative interaction between project partners. In contribution to this effort, US EPA and Maastricht University project partners have completed the semantic mapping of several AOP-DB data tables into RDF. RDF is a standard model for data interchange (W3C).

Description:

There is a need for more efficient use of existing data to characterize human toxicological response data for environmental chemicals in the US and Europe. The Adverse Outcome Pathway (AOP) framework helps to organize existing mechanistic information, where AOP knowledge and data are currently submitted directly by users and stored in the AOP-Wiki (https://aopwiki.org/). Automatic and systematic parsing of AOP-Wiki data is challenging, so we have created the EPA Adverse Outcome Pathway Database. The AOP-DB is an AOP profiler, developed by the US EPA to assist in biological and mechanistic characterization of AOP data and provide a broad, systems-level overview of the biological context of AOPs. Recent updates to AOP-DB include 262 AOPs from the AOP-Wiki XML. Here we describe the recent semantic mapping efforts for the AOP-DB, and how this process integrates AOP-DB data with other toxicologically relevant datasets. This abstract does not reflect EPA Policy Computational toxicology is central to the current transformation occurring in toxicology and chemical risk assessment. There is a need for more efficient use of existing data to characterize human toxicological response data for environmental chemicals in the US and Europe. The Adverse Outcome Pathway (AOP) framework helps to organize existing mechanistic information and contributes to what is currently being described as New Approach Methodologies (NAMs). AOP knowledge and data are currently submitted directly by users and stored in the AOP-Wiki (https://aopwiki.org/). Automatic and systematic parsing of AOP-Wiki data is challenging, so we have created the EPA Adverse Outcome Pathway Database. The AOP-DB, developed by the US EPA to assist in the biological and mechanistic characterization of AOP data, provides a broad, systems-level overview of the biological context of AOPs. Here we describe the recent semantic mapping efforts for the AOP-DB, and how this process facilitates the integration of AOP-DB data with other toxicologically relevant datasets through a use case example

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