How do practitioners use conceptual modeling in practice?

Much research has been devoted over the years to investigating and advancing the techniques and tools used by analysts when they model. As opposed to what academics, software providers and their resellers promote as should be happening, the aim of this research was to determine whether practitioners still embraced conceptual modeling seriously. In addition, what are the most popular techniques and tools used for conceptual modeling? What are the major purposes for which conceptual modeling is used? The study found that the top six most frequently used modeling techniques and methods were ER diagramming, data flow diagramming, systems flowcharting, workflow modeling, UML, and structured charts. Modeling technique use was found to decrease significantly from smaller to medium-sized organizations, but then to increase significantly in larger organizations (proxying for large, complex projects). Technique use was also found to significantly follow an inverted U-shaped curve, contrary to some prior explanations. Additionally, an important contribution of this study was the identification of the factors that uniquely influence the decision of analysts to continue to use modeling, viz., communication (using diagrams) to/from stakeholders, internal knowledge (lack of) of techniques, user expectations management, understanding models' integration into the business, and tool/software deficiencies. The highest ranked purposes for which modeling was undertaken were database design and management, business process documentation, business process improvement, and software development. (c) 2005 Elsevier B.V. All rights reserved.

A reference methodology for conducting ontological analyses

The ontological analysis of conceptual modelling techniques is of increasing popularity. Related research did not only explore the ontological deficiencies of classical techniques such as ER or UML, but also business process modelling techniques such as ARIS or even Web services standards such as BPEL4WS. While the selected ontologies are reasonably mature, it is the actual process of an ontological analysis that still lacks rigor. The current procedure leaves significant room for individual interpretations and is one reason for criticism of the entire ontological analysis. This paper proposes a procedural model for the ontological analysis based on the use of meta models, the involvement of more than one coder and metrics. This model is explained with examples from various ontological analyses.

MQL: A powerful extension to OCL for MOF queries

The Meta-Object Facility (MOF) provides a standardized framework for object-oriented models. An instance of a MOF model contains objects and links whose interfaces are entirely derived from that model. Information contained in these objects can be accessed directly, however, in order to realize the Model-Driven Architecture@trade; (MDA), we must have a mechanism for representing and evaluating structured queries on these instances. The MOF Query Language (MQL) is a language that extends the UML's Object Constraint Language (OCL) to provide more expressive power, such as higher-order queries, parametric polymorphism and argument polymorphism. Not only do these features allow more powerful queries, but they also encourage a greater degree of modularization and re-use, resulting in faster prototyping and facilitating automated integrity analysis. This paper presents an overview of the motivations for developing MQL and also discusses its abstract syntax, presented as a MOF model, and its semantics