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The Decision Model and Notation (DMN) is a recent OMG standard for theelicitation and representation of decision models, and for managing theirinterconnection with business processes. DMN builds on the notion of decisiontables, and their combination into more complex decision requirements graphs(DRGs), which bridge between business process models and decision logic models.DRGs may rely on additional, external business knowledge models, whosefunctioning is not part of the standard. In this work, we consider one of themost important types of business knowledge, namely background knowledge thatconceptually accounts for the structural aspects of the domain of interest, andpropose decision knowledge bases (DKBs), which semantically combine DRGsmodeled in DMN, and domain knowledge captured by means of first-order logicwith datatypes. We provide a logic-based semantics for such an integration, andformalize different DMN reasoning tasks for DKBs. We then consider backgroundknowledge formulated as a description logic ontology with datatypes, and showhow the main verification tasks for DMN in this enriched setting can beformalized as standard DL reasoning services, and actually carried out inExpTime. We discuss the effectiveness of our framework on a case study inmaritime security.

Semantic DMN: Formalizing and Reasoning About Decisions in the Presence of Background Knowledge