PNNL

Abstract

Science—and biology in particular—has a rich tradition in categorical knowledge management. This continues today in the generation and use of formal ontologies. Unfortunately, the link between hard data and ontological content is predominately qualitative, not quantitative. The usual approach is to construct ontologies of qualitative concepts, and then annotate the data to the ontologies. This process has seen great value, yet it is laborious, and the success to which ontologies are managing and organizing the full information content of the data is uncertain. An alternative approach is the converse: use the data itself to quantitatively drive ontology creation. Under this model, one generates ontologies at the time they are needed, allowing them to change as more data influences both their topology and their concept space. We outline a combined approach to achieve this, taking advantage of two technologies, the mathematical approach of Formal Concept Analysis (FCA) and the semantic web technologies of the Web Ontology Language (OWL).