Knowledge-Based Systems for Data Modelling

Knowledge-Based Systems for Data Modelling

Sabrina Šuman, Alen Jakupović, Francesca Gržinić Kuljanac
Copyright: © 2016 |Pages: 13
DOI: 10.4018/IJEIS.2016040101
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Abstract

Data modelling is a complex process that depends on the knowledge and experience of the designers who carry it out. The quality of created models has a significant impact on the quality of successive phases of information systems development. This paper, in short, reviews the data modelling process, the entity-relationship method (ERM) and actors in the data modelling process. Further, in more detail it presents systems, methods, and tools for the data modelling process and identifies problems that occur during the development phase of an information system. These problems also represent the authors' motivation for conducting research that aims to develop a knowledge-based system (KBS) in order to support the data modelling process by applying formal language theory (particularly translation) during the process of conceptual modelling. The paper describes the main identified characteristics of the authors' new KB system that are derived from the analysis of existing systems, methods, and tools for the data modelling process. This represents the focus of the research.
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2. Research Motivation

The data modelling research motivation has derived from a number of problems arising in the information systems development. Some of these problems in the analysis and design phase are:

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    complexity of the process model to data model translation

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    lack of data modelling knowledge

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    non-existent or insufficient data modelling knowledge formalisation required in computer- systems

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    error occurrence in data modelling

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    low efficiency of the process model to the data model translation (time, money, and other resources)

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    possible low effectiveness of the data model in the case of business process changes

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