Semantic interoperability: challenges in the digital transformation age

Humans use words, diagrams, images, context, but also sounds, facial expressions or body language to be understood. Machines use data and information models as well as algorithms to manipulate information, and human concepts need to be translated for machine use.

Due to the exponentially growing number of systems that collect, process, and share data, machines increasingly need to be able to communicate with each other without the intervention of humans. This requires increased interoperability in terms of concepts, data structures, information models as well as digital specifications. In addition to enabling data exchange, so-called semantic interoperability defines the meaning of data without the need for additional programming. It provides the means for two systems to understand each other’s conventions and functions behind the data and the context in which it is used. It allows computer systems to exchange data with unambiguous, shared meaning. Semantic interoperability will be the key to digitalization and the latest industrial revolution.

This white paper outlines what it takes to achieve machine-to-machine communication and how standards can provide structures that will allow machines to interact truly independently.

--------

The white paper was developed by the IEC Market Strategy Board (MSB) semantic ontologies project team with major contributions from Siemens AG and project partner, Prof. Dr.-Ing. Christian Diedrich, ifak e.V. Magdeburg (Germany).