Experiences in mapping the business intelligence model to description logics, and the case for parametric concepts

BIM is a new language for capturing business models containing information relevant for strategic analysis of business operations. It has been used in several large case studies and is being pursued in industry. The paper introduces the key notions of BIM, including goals, evidence, and influence. It also outlines their translation into DL axioms, forming an upper-level ontology. Specific BIM domain models then result from the addition of axioms to this. The result provides both a formal semantics of the BIM language, and all the familiar advantages of decidable DL reasoning, including consistency checking, defined-concept classification, and, in our case "What if" scenario analysis. We focus on the parts of the translation which are most interesting, including: i) modeling "evidence and pursuit propagation" about goals, ii) dealing with "meta-properties", which were introduced as a result of an ontological analysis of previous BI languages, and iii) the repeated need for too many similar axioms. For the last two, we sketch how parametrized concepts, together with rules, would significantly help knowledge-base maintenance. This opens up a new research area in hybrid DL+rule KBs, involving rules that generate new axioms.