Design, Science and Conceptual Analysis

Philosophers expend considerable effort on the analysis of concepts, but the value of such work is not widely appreciated. This paper principally analyses some arguments, beliefs, and presuppositions about the nature of design and the relations between design and science common in the literature to illustrate this point, and to contribute to the foundations of design theory.

Should optional properties be used in conceptual modelling? A theory and three empirical tests

An important feature of some conceptual modelling grammars is the features they provide to allow database designers to show real-world things may or may not possess a particular attribute or relationship. In the entity-relationship model, for example, the fact that a thing may not possess an attribute can be represented by using a special symbol to indicate that the attribute is optional. Similarly, the fact that a thing may or may not be involved in a relationship can be represented by showing the minimum cardinality of the relationship as zero. Whether these practices should be followed, however, is a contentious issue. An alternative approach is to eliminate optional attributes and relationships from conceptual schema diagrams by using subtypes that have only mandatory attributes and relationships. In this paper, we first present a theory that led us to predict that optional attributes and relationships should be used in conceptual schema diagrams only when users of the diagrams require a surface-level understanding of the domain being represented by the diagrams. When users require a deep-level understanding, however, optional attributes and relationships should not be used because they undermine users' abilities to grasp important domain semantics. We describe three experiments which we then undertook to test our predictions. The results of the experiments support our predictions.

Extracting ontological concepts for tendering conceptual structures

It has been argued that beyond software engineering and process engineering, ontological engineering is the third capability needed if successful e-commerce is to be realized. In our experience of building an ontological-based tendering system, we face the problem of building an ontology. In this paper, we demonstrate how to build ontologies in the tendering domain. The ontology life cycle is identified. Extracting concepts from existing resources like on-line catalogs is described. We have reused electronic data interchange (EDI) to build conceptual structures in the tendering domain. An algorithm to extract abstract ontological concepts from these structures is proposed.

Research commentary: Information systems and conceptual modeling - A research agenda

Within the information systems field, the task of conceptual modeling involves building a representation of selected phenomena in some domain. High-quality conceptual-modeling 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-practice data and process models in enterprise resource planning systems. Yet little research has been undertaken on many aspects of conceptual modeling. In this paper, we propose a framework to motivate research that addresses the following fundamental question: How can we model the world to better facilitate our developing, implementing, using, and maintaining more valuable information systems? The framework comprises four elements: conceptual-modeling grammars, conceptual-modeling methods, conceptual-modeling scripts, and conceptual-modeling contexts. We provide examples of the types of research that have already been undertaken on each element and illustrate research opportunities that exist.

Conceptual modelling and ontology: Possibilities and pitfalls

Conceptual modelling is an activity undertaken during information systems development work to build a representation of selected semantics about some real-world domain. Ontological theories have been developed to account for the structure and behavior of the real world in general. In this paper, I discuss why ontological theories can be used to inform conceptual modelling research, practice, and pedagogy. I provide examples from my research to illustrate how a particular ontological theory has enabled me to improve my understanding of certain conceptual modelling practices and grammars. I describe, also, how some colleagues and I have used this theory to generate several counter-intuitive, sometimes surprising predictions about widely advocated conceptual modelling practices - predictions that subsequently were supported in empirical research we undertook. Finally, I discuss several possibilities and pitfalls I perceived to be associated with our using ontological theories to underpin research on conceptual modelling.