Data Analytics Using Ontologies of Management Theories: Towards Implementing 'From Theory to Practice'

We explore how computational ontologies can be impactful vis-à-vis the developing discipline of “data science.” We posit an approach wherein management theories are represented as formal axioms, and then applied to draw inferences about data that reside in corporate databases. That is, management theories would be implemented as rules within a data analytics engine. We demonstrate a case study development of such an ontology by formally representing an accounting theory in First-Order Logic. Though quite preliminary, the idea that an information technology, namely ontologies, can potentially actualize the academic cliché, “From Theory to Practice,” and be applicable to the burgeoning domain of data analytics is novel and exciting.

Keywords: computational ontologies, data analytics, data science, data driven decision-making, auditor decision-making, Belief-Desires-Intentions

JEL Classification: M00, M40

Suggested Citation: Suggested Citation

Kim, Henry M. and Gel, Iryna and Cheung, Ho-Nam and Laskowski, Marek, Data Analytics Using Ontologies of Management Theories: Towards Implementing 'From Theory to Practice' (June 21, 2016). Proceedings of the 17th IEEE International Conference on Information Reuse, 2016., Available at SSRN: https://ssrn.com/abstract=2138121 or http://dx.doi.org/10.2139/ssrn.2138121