Applying Grounded Theory to Conceptual Data Modeling: Effects of Constant Comparative Method

This article presents an experimental design and the pilot experiment results of applying grounded theory to conceptual data modeling. The objective of this study is to develop a procedural method for concept discovery, which is essential in data modeling. The research focuses on addressing the lack of procedural methods for understanding domain knowledge by data modeler. The key idea of this article is that conceptual modeling can be strengthened by applying a constant comparative method of coding and analysis, which has been used to discover concepts in the social sciences. This article contributes new knowledge about the effects of applying interdisciplinary concept discovery in the context of conceptual data modeling. The results of the pilot experiment show that the proposed approach would have positive results.