An extended taxonomy of advanced information visualization and interaction in conceptual modeling
Conceptual modeling is integral to computer science research and is widely adopted in industrial practices, e.g., business process and enterprise architecture management. Providing adequate and usable modeling tools is necessary to adopt modeling languages efficiently. Meta-modeling platforms provid...
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Veröffentlicht in: | Data & knowledge engineering 2023-09, Vol.147, p.102209, Article 102209 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Conceptual modeling is integral to computer science research and is widely adopted in industrial practices, e.g., business process and enterprise architecture management. Providing adequate and usable modeling tools is necessary to adopt modeling languages efficiently. Meta-modeling platforms provide a rich and mature set of functionalities for realizing state-of-the-art modeling tools. These tools, albeit their stability and rich set of features, often lack a modern look and feel considering (i) how they visualize the models, and (ii) how modelers interact with the models. Current web technologies enable much richer, advanced opportunities for visualizing and interacting with conceptual models. However, a structured and comprehensive overview of possible information visualization and interaction techniques linked to conceptual models and modeling tools must be established. This paper aims to fill this gap by presenting an extended taxonomy of advanced information visualization and interaction in conceptual modeling. We present a generic taxonomy that is afterward contextualized within the specific domain of conceptual modeling. The taxonomy serves orientation in the vast developing field of information visualization and interaction and hopefully sparks innovation if future modeling tool development.
•We propose a taxonomy for advanced information visualization and interaction in conceptual modeling.•We show the current design space of visualization and interaction in conceptual modeling.•We exemplify the taxonomy dimensions with many illustrative examples.•We discuss opportunities and future research directions. |
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ISSN: | 0169-023X 1872-6933 |
DOI: | 10.1016/j.datak.2023.102209 |