Domain-specific diagrammatic modelling: a source of machine-readable semantics for the Internet of Things

Robert Andrei Buchmann, Dimitris Karagiannis

Publications: Contribution to journalArticlePeer Reviewed

Abstract

The Internet of Things (IoT) must address not only the data-level communication across networks of sensors and cyber-physical systems, but also the machinereadable semantics that can enrich and elevate sensor data to superior layers of abstraction and interoperability. In this respect, IoT may benefit from the technological space established by the SemanticWeb paradigm for the desideratum of semantic interoperability. Another complementary ingredient, proposed in this paper, is the domain-specific knowledge captured in diagrammatic models that describe complex IoT environments with dedicated modelling languages. Such models are traditionally employed to support communication and sense-making among business analysts, or to support software design tasks. The paper at hand advocates a novel role of diagrammatic models-their underlying graph nature combined with an agile approach to modelling semantics are harnessed in order to semantically lift sensor data in a Linked Data environment, consequently enabling a richer back-end to IoT client applications.

Original languageEnglish
Pages (from-to)895-908
Number of pages14
JournalCluster Computing
Volume20
Issue number1
DOIs
Publication statusPublished - Mar 2017

Austrian Fields of Science 2012

  • 102028 Knowledge engineering

Keywords

  • CLOUD
  • Diagrammatic conceptual modelling
  • INFORMATION
  • Internet of Things
  • Linked Data
  • Mobile maintenance
  • Sensor semantics

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