Categorical Representation of Evolving Structure of an Ontology for Clinical Fungus

Abstract

With increasing popularity of using ontologies, many industrial and clinical applications have employed ontologies as their conceptual backbone. Ontologies try to capture knowledge from a domain of interest and when the knowledge changes, the definitions will be altered. We study change management in the FungalWeb Ontology, which is the result of integrating numerous biological databases and web accessible textual resources. The fungal taxonomy is currently unstable and evolves over time. This evolution can be seen in both nomenclature and the taxonomic structure. In an experiment we have focused on changes in medical species of fungus which can potentially alter the related disease name and description in an integrated clinical system. In order to address certain aspects of representation of changes in an ontology driven clinical application we propose a methodology based on category theory as a mathematical notation, which is independent of a specific choice of ontology language and any particular implementation.

Incremental Biomedical Ontology Change Management through Learning Agents

“…Many of the problems in ontology evolution are basically problems about the nature and representation of change. For the formal representation of changes, we use Description Logics, and for diagrammatical representation, we employ a method based on discrete state model and category theory [4].…”

“…As presented in [4], category theory has great potential as a mathematical medium to represent, track, and analyze changes in biomedical ontologies. In addition we demonstrated [4] its capability to analyze some of the common operations during ontology evolution.…”

“…In addition we demonstrated [4] its capability to analyze some of the common operations during ontology evolution. After describing the ontological concepts within categories representing a modular hierarchy of domain knowledge, we have employed category theory as a formalism to analyze ontological changes and agent interaction in different stages of the RLR framework.…”

“…Many names and terms are highly dependent on individual or regional preferences [24], causing redundancy, vagueness, and misclassification in current vocabularies. We study various alterations in fungal taxonomy [4]. As another example, the pathogenic fungus Candida glabrata is now called Torulopsis glabrata [26].…”

“…Based on our application we designed our class diagrams following the method described in [27,4] (Figure 6), which can be used to create patterns for learning agents. The Opi arrows in this figure represent the operations for the class, wherein the operation or event Op1 causes an object in state St1 to undergo a transition to state St2.…”