Linked Data as Integrating Technology for Industrial Data

In a globalised world the process industry faces great challenges regarding data management. Rising demands for agility and rapid shortening of innovation cycles have lead to project-based collaborations. Highly specialised small and medium enterprises are forming so-called virtual companies to profit from each other. Today, however, industrial data structures are characterised by high heterogeneity. This complicates collaborative work and hinders the flow of data between different stakeholders from various domains. Existing solutions are much too rigid and potentially cumbersome. There still is a broad gap between the need of virtual companies to share data from mixed sources in a controlled way and the available technologies to accomplish this. Our approach to close this gap is the usage of semantic web technologies for representing industrial data in a generic way. Major advantages in comparison to traditional approaches arise from the inherent merging abilities and from the extensibility of Linked Data. Distributed information spaces from different domains can be condensed into an interlinked cloud. Existing data can be integrated either on-the-fly using appropriate adapters or by complete migration. Furthermore, operations from graph theory can be performed on the Linked Data networks to generate aggregated views. This paper discusses a set of proven web technologies for cloud-driven industrial data sharing in virtual companies and presents preliminary results.