Deriving Design Aspects from Conceptual Models

Two fundamental issues in aspect orientation are the identification and the composition of aspects. We argue that aspects must be identified at the requirement and the domain analysis phases. We also propose a mechanism for gradually composing aspects throughout the software development process. We illustrate our ideas for the design of a transaction framework

How do we acquire understanding of conceptual models?

In organizations, conceptual models are used for understanding the domain concepts. Such models are crucial in analysis and development of information systems. An important factor of using the conceptual models is how quickly analysts are able to learn the domain concepts as depicted in the models. Using a laboratory experiment, this research used eye tracking technique to capture the speed of acquisition of understanding conceptual models. Two sets of conceptual models were used in this study- one theory based (REA pattern) and the other non-theory based (non REA pattern). It was found that the rate of learning of the domain concepts was faster with theory based models than with non-theory based models. However, users of the non-theory based model were able to catch up with the learning of the model concepts after being repeatedly exposed to the model

Ontology-based model abstraction

In recent years, there has been a growth in the use of reference conceptual models to capture information about complex and critical domains. However, as the complexity of domain increases, so does the size and complexity of the models that represent them. Over the years, different techniques for complexity management in large conceptual models have been developed. In particular, several authors have proposed different techniques for model abstraction. In this paper, we leverage on the ontologically well-founded semantics of the modeling language OntoUML to propose a novel approach for model abstraction in conceptual models. We provide a precise definition for a set of Graph-Rewriting rules that can automatically produce much-reduced versions of OntoUML models that concentrate the models’ information content around the ontologically essential types in that domain, i.e., the so-called Kinds. The approach has been implemented using a model-based editor and tested over a repository of OntoUML models

Towards a unified conceptual model representation

A good documentation or representation is important for communicating simulation conceptual models between stakeholders effectively. A good conceptual model representation may be used as a legal document in a simulation project contract; it may be used as a model description, which is crucial in a distributed simulation environment for model reusability and interoperability and, finally, it can improve the credibility of the model. This paper proposes a unified representation of simulation conceptual models. A conceptual model comprises a number of components, which can be grouped into the problem domain and the model domain. A number of diagrams and textual representations are proposed to represent each of the conceptual model components. Our intention is to initiate the discussion and development of a unified conceptual model representation that will benefit stakeholders involved in a simulation project. A case study in health-care is used to show how the proposed unified conceptual modelling can be applied in practice

Developing Ontological Theories for Conceptual Models using Qualitative Research

Conceptual modelling is believed to be at the core of the IS discipline. There have been attempts to develop theoretical foundations for conceptual models, in particular ontological models as axiomatic reference systems. Although the notion of ontology has become popular in modelling theories, criticism has risen as to its philosophical presuppositions. Taking on this criticism, we discuss the task of developing socially constructed ontologies for modelling domains and outline how to enhance the expressiveness of ontological modelling theories by developing them via qualitative research methods such as Grounded Theory