5 research outputs found

    Modeling styles in conceptual data modeling: Reflecting observations in a series of multimodal studies

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    A modeling style characterizes a modeler’s sequencing of processing a modeling task in terms of applying the modeling language and its language concepts while constructing a conceptual model. Presently, surprisingly little is known about the different modeling styles modelers exhibit when performing conceptual data modeling. In this research, we combine complementary modes of observation including audio-visual protocols, recorded modeler-tool interactions, and pre-/post-modeling surveys of modelers to identify modeling styles in 24 data modeling processes performed by modelers at different stages of experience in data modeling. Our study identifies and characterizes three distinct modeling styles refining our current knowledge about data modeling processes and informing design science research on style-specific, targeted modeling (software tool) support for data modelers

    Process Modeling Recommender Systems - A Generic Data Model and Its Application to a Smart Glasses-based Modeling Environment

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    The manual construction of business process models is a time-consuming, error-prone task and presents an obstacle to business agility. To facilitate the construction of such models, several modeling support techniques have been suggested. However, while recommendation systems are widely used, e.g., in e-commerce, these techniques are rarely implemented in process modeling tools. The creation of such systems is a complex task since a large number of requirements and parameters have to be taken into account. In order to improve the situation, the authors have developed a data model that can serve as a backbone for the development of process modeling recommender systems (PMRS). This article outlines the systematic development of this model in a stepwise approach using established requirements and validates it against a data model that has been reverse-engineered from a real-world system. In a last step, the paper illustrates an exemplary instantiation of the data model in a Smart Glasses-based modeling environment and discusses business process agility issues. The authors expect their contribution to provide a useful starting point for designing the data perspective of process modeling recommendation features that support business agility in process-intensive environments

    Toward a Taxonomy of Modeling Difficulties: A Multi-Modal Study on Individual Modeling Processes

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    Conceptual modeling is an essential activity during information systems development and, accordingly, a learning task faced by students of Information Systems. Presently, surprisingly little is known about how learning processes of conceptual modeling proceed, and about modeling difficulties learners experience. In this study, we integrate complementary modes of observation of learners\u27 modeling processes to identify modeling difficulties these learners face while performing a data modeling task using a modeling tool. We use the concept of cognitive breakdowns to analyze verbal protocols, recordings of learner-tool interactions and video recordings of learners\u27 modeling processes and survey learners about modeling difficulties. Our study identifies five types of modeling difficulties relating to different aspects of constructing conceptual data models, i.e., entity types, relationship types, attributes, and cardinalities. The identified types of modeling difficulties motivate a taxonomic theory of modeling difficulties intended to inform design science research on tool support for learners of conceptual modeling
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