Enabling Semantics within Industry 4.0

Manufacturing faces increasing requirements from customers which causes the need of exploiting emerging technologies and trends for preserving competitive advantages. The apriori announced fourth industrial revolution (also known as Industry 4.0) is represented mainly by an employment of Internet technologies into industry. The essential requirement is the proper understanding of given CPS (one of the key component of Industry 4.0) data models together with a utilization of knowledge coming from various systems across a factory as well as an external data sources. The suitable solution for data integration problem is an employment of Semantic Web Technologies and the model description in ontologies. However, one of the obstacles to the wider use of the Semantic Web technologies including the use in the industrial automation domain is mainly insufficient performance of available triplestores. Thus, on so called Semantic Big Data Historian use case we are proposing the usage of state of the art distributed data storage. We discuss the approach to data storing and describe our proposed hybrid data model which is suitable for representing time series (sensor measurements) with added semantics. Our results demonstrate a possible way to allow higher performance distributed analysis of data from industrial domain.