Abstract
The field of conceptual modeling continues to evolve and be applied to important modeling problems in many domains. With a goal of articulating the breadth and depth of the field, our initial work focused on the many implicit and explicit definitions of conceptual modeling, resulting in the Characterizing Conceptual Modeling (CCM) framework. In this paper, we focus on conceptual modeling research, presenting a Characterizing Conceptual Model Research (CCMR) framework and a series of evaluations to assess the coverage and usability of CCMR, the utility and independence of the individual fields in the framework, and likelihood of consistent use.
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Notes
- 1.
As examples of philosophical grounding, Wand and Weber take an ontological perspective to understanding information systems from a conceptual modeling perspective [44]. Guizzardi provides another kind of ontological foundation for conceptual models [11]. Guarino has long argued for the role of ontologies in conceptual modeling [10].
- 2.
Note that our characterizations of these and the other \(3+6\) papers have not been vetted by the original authors of the research work. We, and not the original authors, are solely responsible for these characterizations.
- 3.
We use the term metadata fields here as used in the digital library field: metadata describes the library item of interest. Typical metadata fields include such items as author and subject.
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Acknowledgments
We thank the participants of the interactive workshop at ER2018 and other research seminar participants who shared their characterizations of CM research papers using CCMR. We also thank Roel Wieringa for his comments on an earlier version of this paper. This work was supported in part by Brigham Young University, Georgia State University, and the Universitat Politècnica de València.
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Delcambre, L.M.L., Liddle, S.W., Pastor, O., Storey, V.C. (2019). Characterizing Conceptual Modeling Research. In: Panetto, H., Debruyne, C., Hepp, M., Lewis, D., Ardagna, C., Meersman, R. (eds) On the Move to Meaningful Internet Systems: OTM 2019 Conferences. OTM 2019. Lecture Notes in Computer Science(), vol 11877. Springer, Cham. https://doi.org/10.1007/978-3-030-33246-4_3
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