Bounded Federation

This paper introduces bounded federation as a model of purpose-directed semantic exchange between independently governed knowledge graphs. Rather than attempting to establish complete semantic equivalence between participating systems, bounded federation identifies a delimited domain within which sufficient semantic correspondence can be established for a specified purpose. The approach builds on ontology design patterns and competency questions to define the intended competence of an exchange, and uses an intermediate, representation-neutral tuple structure to expose candidate assertions for review.

The model is demonstrated through Wikibase-to-Wikibase exchange between Wikidata and a specialist research Wikibase. Assertions originating in participating graph representations are projected into a bounded relational review space and, where warranted, made available for destination-governed admission or application. The experiment distinguishes between assertions that can be federated, local semantic commitments that require redefinition, candidate exchanges that should be excluded, and subject–predicate intersections that are not applicable because they do not constitute candidate assertions within the federation boundary. The latter distinction demonstrates that a rectangular computational projection may expose potential semantic intersections beyond the actual claim space and that recognising such limits is itself relevant to interoperability.

The paper argues that the quality of semantic federation should not be evaluated primarily by the completeness of ontology alignment or the quantity of exchanged assertions. Better federation is not necessarily fuller federation. A successful federation should maximise warranted semantic exchange while preserving relevant differences and making its boundaries of interpretation, applicability, provenance, and inferential competence explicit. The resulting model provides a basis for reviewable graph-to-graph interoperability without requiring participating knowledge systems to converge on a single overarching ontology.