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Knowledge-Based Systems for Data Modelling: Review and Challenges

Knowledge-Based Systems for Data Modelling: Review and Challenges
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Author(s): Sabrina Šuman (Polytechnic of Rijeka, Croatia), Alen Jakupović (Polytechnic of Rijeka, Croatia)and Mile Pavlić (University of Rijeka, Croatia)
Copyright: 2017
Pages: 21
Source title: Enterprise Information Systems and the Digitalization of Business Functions
Source Author(s)/Editor(s): Madjid Tavana (La Salle University, USA)
DOI: 10.4018/978-1-5225-2382-6.ch016

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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 lack of designers' expertise in that process negatively affects the quality of created models which has a significant impact on the quality of successive phases of information systems development. This chapter provides an overview of data modelling, especially the entity relationship method, main actors in the modelling process, and highlights the main problems and challenges in this field. Knowledge based system for data modelling support has a potential to minimize and prevent most of the problems that occur in modelling process. Therefore, a systematic review of the existing KB systems, methods, and tools for the data modelling process is made. By summarizing their main characteristics, some important desirable features of the new KB system for data modelling support are identified. With this in mind, a new KB system for data modelling support is proposed, which applies formal language theory (particularly translation) during the process of conceptual modelling.

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