Using MathML to Represent Units of Measurement for Improved Ontology Alignment
This addresses the need for technical interoperability in domains relying on precise units, but it is incremental as it builds on existing ontology alignment methods.
The paper tackles the problem of aligning ontologies for units of measurement by proposing a strategy that uses MathML to capture semantic descriptions, resulting in improved mapping accuracy over lexical comparisons for three ontologies.
Ontologies provide a formal description of concepts and their relationships in a knowledge domain. The goal of ontology alignment is to identify semantically matching concepts and relationships across independently developed ontologies that purport to describe the same knowledge. In order to handle the widest possible class of ontologies, many alignment algorithms rely on terminological and structural meth- ods, but the often fuzzy nature of concepts complicates the matching process. However, one area that should provide clear matching solutions due to its mathematical nature, is units of measurement. Several on- tologies for units of measurement are available, but there has been no attempt to align them, notwithstanding the obvious importance for tech- nical interoperability. We propose a general strategy to map these (and similar) ontologies by introducing MathML to accurately capture the semantic description of concepts specified therein. We provide mapping results for three ontologies, and show that our approach improves on lexical comparisons.