In organisations, conceptual models are used for understanding domain concepts. Learning the domain from models is crucial for the analysis and design of information systems that are intended to support the domain. Past research has proposed theories to structure conceptual models in order to improve learning. It has, however, never been investigated how quickly domain knowledge is acquired when using theory-guided conceptual models. Based on theoretical arguments, we hypothesise that theory-guided conceptual models expedite the initial stages of learning. Using the REA ontology pattern as an example of theoretical guidance, we show in a laboratory experiment how an eye-tracking procedure can be used to investigate the effect of using theory-guided models on the speed of learning. Whereas our experiment shows positive effects on both outcome and speed of learning in the initial stages of learning, the real contribution of our paper is methodological, i.e. an eye-tracking procedure to observe the process of learning from conceptual models.

This paper investigates the effect of construct redundancy on readers' understanding of conceptual models. Conceptual models play a crucial role in understanding the domain related to information system development. The clarity of such models can be compromised if they are constructed using a conceptual modelling grammar exhibiting construct redundancy where one real-world phenomenon maps to two or more grammar constructs. With two empirical studies on solving domain-related problems using Unified Modeling Language (UML) class diagrams as conceptual domain models, it was found that when construct redundancy is present at different strengths, then the effect of the redundancy on the understanding of a model depends on the modeling knowledge of the reader. Novice readers with minimal modeling knowledge find models difficult to interpret when a strong level of redundancy caused by distinct construct redundancy exists. However, when the models have a weak level of redundancy then these readers find them easier to understand compared to models without redundancy. In contrast, trained readers are indifferent to a weak level of redundancy in a model.

Business processes are designed to execute strategies that aim at achieving organisational goals. During the last decade, several methods have been proposed that prescribe the use of goal-oriented requirements engineering techniques for supporting different business process management activities, in particular business process modelling. The integration of goal modelling and business process modelling aims at increasing the alignment between business strategies and the processes with their supporting IT systems. This new research area, which the authors call Goal-Oriented Requirements Engineering for Business Processes (GORE-for-BP), is developing rapidly, but without a clear conceptualization of the focus and scope of the proposed GORE-for-BP methods. Furthermore, an overview is lacking of which methods exist and what their level of maturity is. This paper therefore presents a research review of the GORE-for-BP area, with the aim of identifying relevant methods and assessing their focus, scope, and maturity. This study used Systematic Literature Review and Method Meta-Modelling as research methods to identify and evaluate the state of the GORE-for-BP research area and to propose a research agenda for directing future research in the area. Nineteen methods were identified, which is an indication of an active research area. Although some similarities were found with respect to how goal models are transformed into business process models (or vice-versa), there is also considerable divergence in modelling languages used and the extent of coverage of typical requirements engineering and business process management lifecycle phases. Furthermore, the exploitation of requirements engineering techniques in the full business process management lifecycle is currently under researched. Also, the maturity of the methods found in terms of the formalisation of the transformation activity, the elaboration of method guidelines, and the extent to which methods are validated, can be further improved.

This research note shows that the scope of conceptual data modeling patterns can be identified, clarified, and explicitly represented by positioning them into an ontology-based framework. A clear and explicit definition of scope could help deciding which patterns match which parts of the domain to be represented. The authors demonstrate their argument by positioning existing conceptual data modeling patterns into a two-dimensional structuring framework that is constructed using two ontology-derived ‘benchmark’ patterns: an enterprise pattern for representing transactions (derived from the REA domain ontology) and an abstraction pattern for representing reality at different levels of abstraction (derived from the UFO foundational ontology). By means of an application scenario dealing with the conceptual design of a transactional enterprise database, the authors illustrate how the framework can be used to evaluate the relevancy and completeness of candidate patterns with respect to the problem at hand.

The quality of conceptual models directly affects the quality of the understanding of the application domain and the quality of the final software products that are ultimately based on them. This paper describes a systematic literature review (SLR) of peer-reviewed conference and journal articles published from 1997 through 2009 on the quality of conceptual models written in UML, undertaken to understand the state-of-the-art, and then identify any gaps in current research. Six digital libraries were searched, and 266 papers dealing specifically with the quality of UML models were identified and classified into five dimensions: type of model quality, type of evidence, type of research result, type of diagram, and research goal. The results indicate that most research focuses on semantic quality, with relatively little on semantic completeness; as such, this research examines new modeling methods vs. quality frameworks and metrics, as well as quality assurance vs. understanding quality issues. The results also indicate that more empirical research is needed to develop a theoretical understanding of conceptual model quality. The classification scheme developed in this paper can serve as a guide for both researchers and practitioners.

In this paper, the author investigates the effect on understanding of using business domain models that are constructed with Resource-Event-Agent (REA) modeling patterns. First, the author analyzes REA modeling structures to identify the enabling factors and the mechanisms by means of which users recognize these structures in a conceptual model and description of an information retrieval and interpretation task. Based on this understanding, the author hypothesizes positive effects on model understanding for situations where REA patterns can be recognized in both task and model. An experiment is then conducted to demonstrate a better understanding of models with REA patterns compared to information equivalent models without REA patterns. The results of this experiment indicate that REA patterns can be recognized with minimal prior patterns training and that the use of REA patterns leads to models that are easier to understand for novice model users.

Business Process Management is a paradigm for enterprise computing that uses IT not only to support or execute business processes but also to continuously monitor and improve these processes to better achieve business objectives. A variant on Business Process Management, called Semantic Business Process Management, is meant to further close the gap between business and IT by attaching business semantics to the technology artifacts used for Business Process Management. A current problem in Semantic Business Process Management is that the specification of the business requirements that processes must respond to and that follow from the enterprise's strategic decisions, is not fully integrated within the design of the processes themselves. In this paper, we propose an approach in which business requirements for business processes are formally modeled and the skeleton of the designs of these business processes is automatically generated from these models. The approach presented here focuses upon the modeling of policies (i.e., a kind of business requirements for business processes) and on the subsequent design of business processes that comply to these policies. A first contribution is extending an existing goal-oriented requirements specification language, i.e. Formal Tropos, to incorporate policies, called Policy-extended Formal Tropos. A second contribution is offering an automated transformation to create business process design skeletons out of the Policy-extended Formal Tropos models. The paper also reports upon three pilot studies that were conducted as a first, though preliminary, empirical test of our approach. © 2010 Wiley Periodicals, Inc.

This paper presents a replication study that investigates the efficacy and likely adoption of a measurement procedure for sizing Web applications from conceptual models (OOmFPWeb). The goal of the replication was to provide evidence for the generalization of the results by repeating the experiment in a different environment, using different subjects. The results of the replica carried out in Austria have confirmed the results of the original experiment, which was carried out in Spain. OOmFPWeb is efficient when compared to current industry practices. It provides reproducible functional size measurements and is perceived as easy to use and useful by its users, who also expressed their intention to use OOmFPWeb in the future. The analysis further supports the validity and reliability of Moody’s Method Evaluation Model for evaluating functional size measurement methods.

Navigability in use, defined as the efficiency, effectiveness and satisfaction with which a user navigates through the system in order to fulfil her goals under specific conditions, has a definite impact on the overall success of Web applications. This quality attribute can be measured based on the navigational model (NM) provided by Web engineering (WE) methodologies. Most of the measures currently defined for NMs are tightly coupled with particular WE methodologies, however. Furthermore, modifications to the design of the NM, carried out with the aim of improving navigability, are performed manually. Both practices have seriously hampered the reusability and adoption of proposed navigability measures and improvement techniques. In this paper, we present a Model-Driven Engineering approach to solving these problems. On the one hand, we propose a generic approach for the definition of navigability measurement models that can be integrated into any WE methodology. On the other hand, we present a model-driven improvement process for the NM design that incurs no increase in costs or in time-to-market of Web applications. This process is divided into two phases: evaluation (i.e. assessment of the model through objective measures) and evolution (i.e. transformation of the model when the measurement results do not fall inside the boundaries set by certain quality decision criteria that have been defined previously).