How to Contribute to the CG
Contribute to the Community Group (CG)
Welcome to W3C AI KR CG
Contributions to the proposed outputs are welcome and encouraged via the CG mailing list and github repo. Submissions may include, but are not limited to, the following:
- Terms and concepts
- Diagrams and conceptual models
- Vocabulary entries and ontological structure
- Definitions (normative or explanatory)
- Demonstrations and worked examples
- Use-case-justified proposals
- Pointers to relevant articles, standards, datasets, or other resources
Contributions should inlcude by a brief explanation of their relevance to the CG’s scope.
Scope and Relevance
Contributions should aim to capture and represent the domain of Knowledge Representation (KR) in relation to Artificial Intelligence — specifically:
How can Knowledge Representation be used to address risks, limitations, and open questions in AI, including AI/ML systems and Large Language Systems (LLS)?
Submissions should make clear:
The problem or risk being addressed (e.g., interpretability, robustness, provenance, bias, alignment, safety, governance, interoperability).
The role of KR methods or structures in addressing that issue.
The use case(s) that justify inclusion within scope.
Use cases serve as the primary justification for inclusion. A contribution should demonstrate how the proposed term, model, vocabulary, or resource supports practical or conceptual advances in applying Knowledge Representation to AI systems.
Resource Submissions
Pointers to external articles, standards, repositories, or tools must include:
A brief description (2–5 sentences) explaining:
What the resource contains,
How it relates to Knowledge Representation,
Why it is relevant to AI risk mitigation, governance, or technical development.
Evaluation Criteria
Considering the relevance and quality of contributions is appreciated, based on:
- Relevance to Natural Language Knowledge Representation
- Explicit connection to AI risks or open questions
- Use-case justification
- Potential for reuse or standardization