Interest in evaluating conceptual modelling techniques has recently experienced a revival, in part due to widespread adoption of the Unified Modelling Language (UML). In addition, the use of ontology as a framework for evaluating conceptual modelling techniques has gained acceptance. In this paper, we consider implications of applying one aspect of the ontology of Mario Bunge to conceptual mode...

Whilst algorithmic modeling is taught intensively both in school and higher education, conceptual modeling, or modeling of data to be used by algorithms, is less highlighted in the teaching curricula. However, understanding basic conceptual modeling principles plays a very important role in practice, as the cost of wrong solutions taken at the level of conceptual modeling is usually high. Tools...

Conceptual data models, as means of communication, must have semantic quality. Such quality relies on the model’s completeness and validity in relation to the concepts it is supposed to represent. Since the modeler acquires such concepts mostly from texts created in a natural language, a semantic-oriented linguistic approach should be adopted for building unambiguous conceptualizations. Also, t...

Within the information systems field, the task of conceptual modeling involves building a representation of selected phenomena in some domain. High-quality conceptualmodeling work is important because it facilitates early detection and correction of system development errors. It also plays an increasingly important role in activities like business process reengineering and documentation of best...

1 Introduction Since the late 1960s, the importance of conceptual modeling grew substantially due to the many information system project failures that were the consequence of faulty requirement analysis. Conceptual modeling was introduced as a means to enable early detection and correction of errors. Over the years, conceptual modeling has become a fundamental discipline in several subdomains o...