Exploration on industrial system-aware dataspace towards smart manufacturing

Thanks to the rapid development of information technology, the concept of smart manufacturing has been widely promoted in recent years, and gave birth to a large number of industrial software. The large amount of data generated and accumulated in industrial software has the characteristics of distributed, multi format and complex relationship. The traditional relational database cannot complete the unified description of these data and respond to their rapid changes. Dataspace is a new data management method that can deal with multi-source heterogeneous data and update dynamically. Therefore, this paper determines the requirements of industrial system data integration. Based on this, a construction and update process of industrial dataspace is proposed. Metadata extraction is used to complete the unified description of data, and then through the construction of data relations and data-service mapping, multi-source heterogeneous data can be effectively organized. Finally, the effectiveness of this method is evaluated through a case study in a nuclear power enterprise.