The Salmon Ontology Development Working Group will develop a scalable, community-driven method to support salmon biologists and data stewards in publishing controlled vocabularies and ontology modules that align with a broader pre-existing salmon domain ontology. The WG will deliver three key outcomes within 18 months:

1. Establish a reusable, community-informed process to integrate salmon datasets using knowledge models that formalize the semantics required to analyze salmon data across agencies. These models will be designed to support a representative fisheries management and research question and will be demonstrated through a case study that typifies common challenges in data integration.
2. Create an open-access training resource to model salmon knowledge that teaches scientists and data professionals how to use pre-existing tools and the method we develop to formally define terms used by their agency/organization/program, integrate data from disparate sources, and contribute and align their ontology modules into a broader salmon domain ontology.
3. Deliver a workshop to train fisheries scientists to employ, test, and refine this process and training resource towards the latter stages of this WG.

We will use an illustrative case study to select appropriate datasets and constrain the thematic scope of our salmon knowledge modeling process. This will ensure the process remains focused and tractable while addressing meaningful real-world integration challenges. The resulting approach will inform the development of a workshop-based training module that can be applied by others in their own contexts.

The selected case study exemplifies common semantic and data integration challenges that salmon biologists and analysts encounter when collaborating across different jurisdictions:

How does variation in juvenile [any salmon species here] salmon condition across regions and years relate to population trends in [xyz region]?