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A conceptual framework for large-scale ecosystem interoperability and industrial product lifecycles

Authors: M. Selway, M. Stumptner, W. Mayer, A. Jordan, G. Grossmann, M. Schrefl
Paper: Schr17d (2017)
Citation: Journal Data & Knowledge Engineering (DKE), Vol. 109, May 2017, DOI: https://doi.org/10.1016/j.datak.2017.03.006, pp. 85-111, 2017.
Resources: Copy  (In order to obtain the copy please send an email with subject  Schr17d  to dke.win@jku.at)


Abstract (English):

One of the most significant challenges in information system design is the constant and increasing need to establish interoperability between heterogeneous software systems at increasing scale. The automated translation of data between the data models and languages used by information ecosystems built around official or de facto standards is best addressed using model-driven engineering techniques, but requires handling both data and multiple levels of metadata within a single model. Standard modelling approaches are generally not built for this, compromising modelling outcomes. We establish the SLICER conceptual framework built on multilevel modelling principles and the differentiation of basic semantic relations (such as specialisation, instantiation, specification and categorisation) that dynamically structure the model. Moreover, it provides a natural propagation of constraints over multiple levels of instantiation. The presented framework is novel in its flexibility towards identifying the multilevel structure, the differentiation of relations often combined in other frameworks, and a natural propagation of constraints over multiple levels of instantiation.