Reasoning about taxonomies and articulations

Taxonomically organized data pervade science, business and everyday life. Unfortunately, taxonomies are often underspecified, limiting their utility in contexts such as data integration, information navigation and autonomous agent communication. This work formalizes taxonomies and relationships between them as formulas in logic. This formalization concretizes notions such as consistency and inconsistency of taxonomies and articulations (inter-taxonomic relations) between them, enables the derivation of new articulations based on a given set of taxonomies and articulations and provides a framework for testing assumptions about underspecified taxonomies.Given the typical intractability of reasoning with taxonomies and articulations, this research investigates many optimizations: from those that reduce the search space, to those that leverage parallel processing, to those investigating logics more tractable than first-order logic (e.g., monadic first-order logic, propositional logic, description logics, and subsets of the RCC-5 spatial algebra). Finally, in addition to reasoning with taxonomies and articulations, this research investigates how to repair inconsistent taxonomies and articulations, how to explain inconsistencies and discovered relations, and how to merge taxonomies given articulations. Critical to this research is the development of a framework for testing logics and support for the development of taxonomies and articulations. This framework, CleanTax is already well under way and has been used to study articulations between two large-scale biological taxonomies.