Analysis of data model correctness by using automated reasoning system

Abstract

Data modeling is one of the most important activities in the process of information systems development which is based on domain knowledge in specific area. This paper presents a model of a system for analyzing data model correctness from the aspect of specific area semantics. The model is based on the use of ontology for domain knowledge representation and formalization of data models and ontology in predicate logic system, to be used in automated reasoning system. Data modeling is one of the most important activities in the process of information systems development, based on domain knowledge in specific area. Model of a system for analyzing data model correctness is created. Ontology presentation, languages and tools are described, data models comparison, data model presentation, formalization and design methodology has been described. Empirical survey is conducted by using student exams errors in the field of database design. It shows that students mainly have faults in semantic aspect of design. List of all error types is given, specially categorized as syntax and semantic errors. We proposed a model of a system for data model evaluation, based on ontology that describes semantic aspect of business domain and axioms that describe reasoning rules. System is an integration of ontology tool, CASE tool and our transformation tool that merge results of ontology and CASE tool with axioms to create clauses form of input to automated reasoning tool. We also presented examples of reasoning rules. All these components are merged and used by PROLOG so the example was tested experimentally. It was shown that PROLOG processed answers to given queries regarding data model evaluation in some aspects.