Making Interoperability Visible A Novel Approach to Understand Interoperability in Cyber-Physical Systems Toolchains

University dissertation from Stockholm : KTH Royal Institute of Technology

Abstract: In CPS development and production environments, tightly integrated processes include different engineering disciplines, development and production departments, and software tools working together, where all of the technical engineering processes become strictly intertwined. CPS development and production toolchains have a highly heterogeneous nature, and supporting toolchain architects is necessary for improving the understanding of the interrelationships between tools. To this end, this thesis mainly concentrates on the interoperability of CPS toolchains with an ambition to improve the understanding of interoperability.A literature survey was conducted to analyze the literature on interoperability with an aim to understand how the interoperability is assessed. Findings of the literature review showed that the existing methods mainly use maturity-like assessment models to assess interoperability and they focus on selective aspects of interoperability. These models use distinct levels and do not guide the stakeholders on how to improve the current state of interoperability. This revealed the need for a more flexible approach for assessing interoperability of CPS toolchains.A case study was developed and exercised with an ambition to test the applicability of the visualization approach. In total, three different visualization techniques were evaluated: circular ideogram, node-link diagram, and balloon layout with a clustering algorithm as an extended version of node-link diagram.This thesis concluded by highlighting that data visualizations and visual analytics are not only a method for understanding the interoperability of CPS toolchains, but also a necessity. Data visualization approaches create many opportunities to make interoperability finally visible and the CPS industry should focus its effort on appropriate data collection, usage, and sharing methods in order to best use data visualization and visual analytics technologies.