Abstract
Information systems are at the core of the digital transformation. To cope with the dynamics of new, emerging markets and ever changing requirements, it is often argued that agile approaches to software development are mandatory. Some even demand to develop information systems without conceptual models, because they were likely to be outdated even before the software is implemented. While such a proposal is not acceptable for serious reasons, conceptual modelling is indeed facing a remarkable challenge in times of change. On the one hand, economics demand for reuse and interoperability, hence, for stable references. On the other hand, freezing structures is likely to compromise a software system’s adaptability. Based on an analysis of this conflict and further challenges, it will be shown how languages for conceptual modelling can be designed to support both, the need for reference and the demand for change.
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Notes
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“Through models we take the reality of the past and the possibilities of the future into the present.”
References
Atkinson, C., & Kühne, T. (2001). The Essence of multilevel metamodeling. In «UML» 2001—the unified modeling language. Modeling languages, concepts, and tools (pp. 19–33). Berlin, London, New York: Springer.
Bateson, G. (1972). Steps to an ecology of mind. Chicago: University of Chicago Press.
Beck, K. (2000). Extreme programming explained: Embrace change. Boston: Addison-Wesley.
Becker, J., Algermissen, L., Niehaves, B., & Delfmann, P. (2005). Business process reference models for reorganizing public administrations-a case study. Schriftenreihe Informatik, Electronic Government, 134–142.
Becker, J., Delfmann, P., & Knackstedt, R. (2007). Adaptive reference modeling: Integrating configurative and generic adaptation techniques for information models. In Reference modeling: Efficient information systems design through reuse of information models (pp. 27–58).
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. New York, London: W.W. Norton & Company.
Clark, T., Sammut, P., & Willans, J. (2008). Superlanguages: Developing languages and applications with XMF. London: Middlesex University London.
Davidson, C., Goldberg, D., & Jones, Z. (2010). The future of thinking: Learning institutions in a digital age. Cambridge, MA: MIT Press.
Derrida, J. (1976). Of grammatology. Baltimore: Johns Hopkins University Press.
Dijkstra, E. W. (1972). The humble programmer. Communications of the ACM, 15(10), 859–866.
Domingos, P. (2017). The master algorithm: How the quest for the ultimate learning machine will remake our world. Penguin Books Ltd.
Evans, J., & Rzhetsky, A. (2010). Machine science. Science, 329(5990), 399–400.
Fettke, P., & Loos, P. (2007). Reference modeling for business systems analysis. Hershey: Idea Group.
Fowler, M., & Beck, K. (2010). Refactoring: Improving the design of existing code. Boston: Addison-Wesley.
Frank, U. (2014). Multilevel modeling: Toward a new paradigm of conceptual modeling and information systems design. Business & Information Systems Engineering, 6(6), 319–337.
Hellmann, S., Lehmann, J., & Auer, S. (2008). Learning of OWL class descriptions on very large knowledge bases. In Proceedings of the 2007 International Conference on Posters and Demonstrations (Vol. 401, pp. 102–103).
Hoppenbrouwers, S. J. B. A. (2003). Freezing language: Conceptualisation processes across ICT-supported organisations.
Kant, I. (1998). Critique of pure reason. In P. Guyer & A. Wood (Eds.), The Cambridge Edition of the Works of Immanuel Kant. Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9780511804649.
King, R. D., Rowland, J., Oliver, S. G., Young, M., Aubrey, W., Byrne, E., et al. (2009). The automation of science. Science, 324(5923), 85–89.
Luhmann, N. (1967). Soziologische Aufklärung. Soziale Welt: Zeitschrift Für Sozialwissenschaftliche Forschung, 18(2/3), 97–123.
Mahr, B. (2015). Modelle und ihre Befragbarkeit: Grundlagen einer allgemeinen Modelltheorie. Erwägen Wissen Ethik, 26(3), 329–342.
Meyer, B. (2014). Agile!: The good, the hype and the ugly. Springer.
Pentland, A. (2015). Social Physics - how social networks can make us smarter. Penguin LCC US.
Rorty, R. (2000). Universality and truth. Rorty and his critics (pp. 1–30). Oxford: Blackwell.
Völker, J., & Niepert, M. (2011). Statistical schema induction. In Proceedings of the 8th Extended Semantic Web Conference on the Semantic Web: Research and Applications-Volume Part I (pp. 124–138). Heidelberg: Springer Verlag.
Wartofsky, M. (1979). Models: Representation and the scientific understanding (R. Cohen, Ed.). Sprinter Netherlands.
Wittgenstein, L. (1973). Philosophical investigations. Wiley-Blackwell.
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Frank, U. (2019). Linguistic Structures in the Light of the Digital Transformation: Addressing the Conflict Between Reference and Change. In: Bergener, K., Räckers, M., Stein, A. (eds) The Art of Structuring. Springer, Cham. https://doi.org/10.1007/978-3-030-06234-7_5
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