[2304.00004] Disentangling Domain Ontologies
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Computer Science > Artificial Intelligence

arXiv:2304.00004 (cs)
[Submitted on 21 Mar 2023]

Title:Disentangling Domain Ontologies

Authors:Mayukh Bagchi, Subhashis Das
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Abstract: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.
Comments: In: Proceedings of the 19th Italian Research Conference on Digital Libraries (IRCDL), February 23-24, 2023, Bari, Italy
Subjects: Artificial Intelligence (cs.AI)
Report number: IRCDL2023
Cite as: arXiv:2304.00004 [cs.AI]
  (or arXiv:2304.00004v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2304.00004

Submission history

From: Mayukh Bagchi [view email]
[v1] Tue, 21 Mar 2023 08:36:14 UTC (281 KB)
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