Abstract: Data modeling is a difficult topic for students to learn. Worse yet is the fact that practitioners, who look to academia for methods and techniques to perform such model building have found little on which to standardize, although many techniques exist. Entity relationship (ER) modeling was developed in order to help database developers visualize their (relational) database design with its data stores and internal relationships. This technique was certainly an important step forward, yet data collected over the past 11 years would indicate database developers are still having difficulty learning, assimilating, and using design techniques (cf. Blaha, 2004). Confounding the issue is the arrival of the object-oriented paradigm. The Unified Modeling Language (UML) was introduced in order to speed, simplify, and clarify design of systems. Portions of the UML are derived from ER modeling and are useful in merging the front end portion of the system with the back end data storage so a picture of the entire system can be viewed by the designer. While providing functionality that ER modeling lacks, the UML approach to data modeling also leaves some developers indecisive and confused as to which technique to use in practice. The same indecision appears to haunt the academic world. So how should data modeling be taught? In order to shed light on this question, we asked contributors to focus on whether this new system of modeling (the UML) yields a better understanding of the database design to the extent that better database designs result. We detected a buzz in the literature and in the IT world that a dichotomy of opinion over this question exists, and so this special issue was born. Educators need to air their opinions, facts, and results and discuss this controversial topic to encourage refinement in this important area. We hope that research ideas can be generated and practitioners informed that this topic is being addressed in academia. As expected, the contributors to this issue provided a dichotomy of opinion but surprisingly, their experiences and opinions moved the issue in a direction far different than what we could have predicted. We now provide you with insight into this poignant topic by presenting this special issue.
Keywords: Data modeling, UML, ER models
Download this article: JISE - Volume 17 Number 1, Page 17.pdf
Recommended Citation: Chilton, M. A., McHaney, R., & Chae, B. (2006). Data Modeling Education: The Changing Technology. Journal of Information Systems Education, 17(1), pp. 17-20.