AIMar 21, 2023

Disentangling Domain Ontologies

arXiv:2304.00004v14 citationsh-index: 1
Originality Incremental advance
AI Analysis

This addresses the challenge of semantic clarity in ontology engineering for domain experts, though it appears incremental as it builds on existing modeling levels without broad empirical validation.

The paper tackles the problem of Conceptual Entanglement in domain ontologies, which arises from representational manifoldness during incremental modeling across five levels, and proposes Conceptual Disentanglement as a multi-level strategy to enforce semantic bijections, resulting in a framework for engineering disentangled ontologies.

In this paper, we introduce and illustrate the novel phenomenon of Conceptual Entanglement which emerges due to the representational manifoldness immanent while incrementally modelling domain ontologies step-by-step across the following five levels: perception, labelling, semantic alignment, hierarchical modelling and intensional definition. In turn, we propose Conceptual Disentanglement, a multi-level conceptual modelling strategy which enforces and explicates, via guiding principles, semantic bijections with respect to each level of conceptual entanglement (across all the above five levels) paving the way for engineering conceptually disentangled domain ontologies. We also briefly argue why state-of-the-art ontology development methodologies and approaches are insufficient with respect to our characterization.

Foundations

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