Expansion of the digital transformation age is generating entirely new businesses and markets. Urbanization, increased life expectancy, climate change, the expanding reach of the global supply chain and the “digitalization of almost everything” have become central to business models and capabilities across all industries.

Pressure is growing on companies and market participants to use data from this digital revolution to make the right decisions concerning investment, research, market assessments and adaptions. Furthermore, with the explosion of available data and the resulting demand for increasingly interactive systems, it is becoming more and more difficult to build applications that can function conjointly in such a complex environment. Semantic interoperability can help resolve some of the challenges involved as a choice element of the digital transformation age.

Semantic interoperability influences the entire information life cycle, both horizontally between individual devices and systems and vertically across dissimilar systems. In this white paper, it is assumed that the interoperability considered in this document is among two or more systems whose information models and syntaxes are mutually different. It is defined as “the ability of computer systems to exchange data with unambiguous, shared meaning” and as “a requirement to enable machine computable logic, inferencing, knowledge discovery, and data federation between information systems.”1 

With the digitization of functions at every level, providing systems with the means to handle more of their day-to-day operations without direct human control or brittle programming constitutes a key element of adaption for moving forward, but this requires the existence of information models that are flexible and unambiguous. Standards can form the foundation for domain-based information models, and indeed a number of such standards already are in place. Thus, the issue of standards and their relation to semantic interoperability is essential to assessing how machine understanding works and determining how to connect industryrelated standards to effectively address this concern.

Another aspect of this challenge involves understanding why semantic interoperability has moved forward so slowly and why there exists a lack of semantic best practices. To address this challenge adequately, semantic best practices must be developed, embraced, adhered to and enforced in the same way that software development has matured to support object-oriented programming (OOP), software patterns, libraries and application programming interfaces (API). Furthermore, and to a much greater extent, because information models are shared (at least in interoperability scenarios), best practices must be extended to include aspects of model development.

This white paper offers an assessment of current and future challenges involving semantic interoperability in industrial domains and related industry-based standards. The main goal of the paper is to identify conditions in which the application of ontologybased semantic technologies, together with already existing information models, can be used to improve interoperability within and between applications and domains, and to formulate recommendations based on a review of use cases versus existing technology and standards.