Multi-model data representation for ontology-driven decision-making

Abstract

Nowadays ontology-driven decision-making is the result of the combination and integration of knowledge and data of different nature and purpose, solving multiple interconnected decision-making problems, synthesizing different points of view on the problem and the decision-making process. For many decision-making problems, the use of only one data model, usually a relational one, is not enough. Today, to solve the problem of "diversity" of data, the concept of multi-model data management is used. Modern aspects of decision-making based on the use of ontologies as a tool of understanding and presentation of decision-making areas and processes, which integrates the methods of system, process and situational analysis are discusses. The possible types of data representations (models) that are necessary for the implementation of ontology-guided decision-making, and also defines the corresponding types of information are defined. In the work, polyglot persistence storage, multi-model storage and cloud-based storage were considered and analyzed for the implementation of multi-model data management. The conclusion is made about the choice of multi-variant storage as a means of multi-model presentation of data within the framework of projects carried out by the authors of the article. The selected software tools for implementing the defined multi-model data representation are described.