This paper presents a general framework called ontographs that relies on a graphical notation and enables the tool-independent and reliable evaluation of human understandability of knowledge representation languages. An experiment with 64 participants is presented that applies this framework and compares a controlled natural language to a common formal language. The results show that the controlled natural language is easier to understand, needs less learning time, and is more accepted by its users.
This work was funded by the research grant (Forschungskredit) programs 2006 and 2008 of the University of Zurich. I would like to thank Alain Cohn, Norbert E. Fuchs, Kaarel Kaljurand, Marc Lutz, Cerstin Mahlow, Philipp Müller and Michael Piotrowski for their suggestions and corrections. Furthermore, I would like to acknowledge the Institute for Empirical Research in Economics of the University of Zurich for organizing the recruitment of the participants for the experiment.