Bringing data chaos under control

In an Industrie 4.0 environment, production machinery and intermediate goods are able to manage themselves. As self-organizing cyberphysical systems, they use sensor technology to capture data about their environment and their current status within a specific workflow. They are able to swap data via a communication network, work cooperatively with one another and, if necessary, react autonomously to changes in production conditions, production priorities or the availability of material.

This alone increases process efficiency. However, companies can extract even greater value for their production and logistics processes by combining these individual items of information in data spaces and viewing them in their entirety. In a data space, individual items of data are combined with one another and with further data from external systems. This in turn yields information about the operating status of production machinery and the production process itself. Such a setup is able not only to predict the future performance of a production system but also to automatically trigger appropriate measures or recommend a suitable course of action.

A data space is more than just a container or collection point for all the datasets from a system or process. A data space also describes these datasets in a uniform manner and combines them into a package of information. On this basis, decisions can then be made in, for example, an intelligent production operation where production machinery or intermediate goods have the ability to act autonomously within an automated environment.

Order from chaos

This in turn supposes that all the many datasets from different sources and in different formats are already available in a structured form. This is what a data space does: create order from chaos by semantically describing these datasets, processing them and then combining them with one another. Information on, for example, production machinery and processes offers genuine value only once it has been intelligently combined and connected.

This is why we take our expertise in collecting, structuring, combining and organizing data and pool it together with our knowledge of data spaces. We can then make this data available more quickly and more efficiently for proper evaluation. As a result, companies can exploit the information in order to make the right decisions for their business.