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

  • Matt Selway
  • , Markus Stumptner
  • , Wolfgang Mayer
  • , Andreas Jordan
  • , Georg Grossmann
  • , Michael Schrefl

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)85-111
Number of pages27
JournalData and Knowledge Engineering
Volume109
DOIs
Publication statusPublished - May 2017

Fields of science

  • 102 Computer Sciences
  • 102010 Database systems
  • 102015 Information systems
  • 102016 IT security
  • 102025 Distributed systems
  • 102027 Web engineering
  • 102028 Knowledge engineering
  • 102030 Semantic technologies
  • 102033 Data mining
  • 102035 Data science
  • 502050 Business informatics
  • 503008 E-learning

JKU Focus areas

  • Digital Transformation

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