Analysing the cognitive effectiveness of the WebML visual notation

Abstract

WebML is a domain-specific language used to design complex data-intensive Web applications at a conceptual level. As WebML was devised to support design tasks, the need to define a visual notation for the language was identified from the very beginning. Each WebML element is consequently associated with a separate graphical symbol which was mainly defined with the idea of providing simple and expressive modelling artefacts rather than by adopting a rigorous scientific approach. As a result, the graphical models defined with WebML may sometimes prevent proper communication from taking place between the various stakeholders. In fact, this is a common issue for most of the existing model-based proposals that have emerged during the last few years under the umbrella of model-driven engineering. In order to illustrate this issue and foster in using a scientific basis to design, evaluate, improve and compare visual notations, this paper analyses WebML according to a set of solid principles, based on the theoretical and empirical evidence concerning the cognitive effectiveness of visual notations. As a result, we have identified a set of possible improvements, some of which have been verified by an empirical study. Furthermore, a number of findings, experiences and lessons learnt on the assessment of visual notations are presented.