Intelligent Data and Knowledge Analysis and Verification; Towards a Taxonomy of Specific Problems

This paper addresses the problem of intelligent analysis of data and knowledge. A common model for data and knowledge representation is proposed. The model takes the form of extended relational database table and it is provided logical interpretation. The main interest is in analysis of certain properties of such bodies of data and knowledge. In order to assure satisfactory performance of a system based on such data and knowledge several theoretical properties should be satisfied. The principal issue is then analysis and verification of these properties which are believed to constitute decisive factors for efficiency, reliability, quality and safety of operation. Several theoretical problems concerning data and knowledge are identified, defined and discussed. These problems cover adequate data and knowledge representation, completeness, consistency, correctness, equivalency, generalization and manipulation, similarity and inductive generalization. Influence of selected issues on system reliability, safety and quality is analyzed and a uniform logical framework for discussion is put forward.