A Meta-Analysis of Ontological Guidance and Users' Understanding of Conceptual Models

Abstract

Information systems are intended to be faithful accounts of real-world applications. As an integral part of the development process, analysts create conceptual models in order to understand the application and communicate requirements. Failure to do so has been a prominent reason for IT projects' failure. Hence, improving the quality of models could have a major impact on the information systems' success. To guide the modeling process, researchers use ontology to create more expressive representations of reality. However, improving expressiveness can make the models complicated and cause cognitive hurdles for users. Therefore, the question is whether ontological guidance is worth the trade-off between expressiveness and complexity. This paper describes a meta-analysis of empirical research examining the impact of ontological guidance on users' understandability. The results show that ontological guidance can improve users' understanding of conceptual models, especially those requiring deeper understanding, thus providing support for ontological guidance in conceptual modeling.

Narrativization in Information Systems Development

“…Dermeval et al (2016) studied the adoption of ontologies to increase specificity in requirements engineering. They, in line with Saghafi and Wand (2020), pointed out that coping with user communication is a persistent crux. Jarke et al (1998) reviewed the use of scenarios and concluded that they are seen as practical tools for comprehending the future states of the world.…”

“…Thus, system developers cannot fully absorb what users convey. Quite often, the context is simplified or distorted, resulting in unsatisfactory results (Holmström & Sawyer, 2011;Oran et al, 2021;Poels et al, 2013;Saghafi & Wand, 2020;Urquhart, 2001). We argue that limited understanding of the role and influence of narratives are contributing factors in this situation.…”

Cognitive Workload Associated with Different Conceptual Modeling Approaches in Information Systems

“…The trade-off between "expressiveness" and "simplicity" has been studied in a number of previous papers and addressed in the meta-analysis by Saghafi and Wand (2020) [13]. It was found that ERDs with higher ontological expressiveness significantly improved users' understanding of an application domain across different conceptual modeling grammars [13] as well as their performance on tasks that required a deeper understanding of the model, e.g., problem solving [5,8]. These findings indicated a positive influence of ontological expressiveness on user interaction with the model allowing for better performance using the system.…”