International Data Spaces

The research project pursues two goals:

• Design of a reference architecture model for the Industrial Data Space
• Piloting the reference architecture model in selected use cases

The research project started on October 1, 2015, and runs over a period of three years. The project consortium consists of twelve Fraunhofer institutes, thus leverages the expertise of large parts of Fraunhofer. 

The activities are organized in 9 work packages:

• Reference architecture model
• Software implementation
• Use cases
• Standardization
• Certification
• Digital Business Engineering methodology
• Recommendations for action
• Institutionalization
• Project management

The work is closely aligned with the Plattform Industrie 4.0. Research project staff engages in the working groups of the platform. The research project activities are led by Prof. Dr. Boris Otto.

The Industrial Data Space initiative institutionalizes as research project on the one hand side and as a chartered association on the other hand. The chartered association was founded in 2016.
 

The chartered association aims at strengthening the user interests, in particular:

• Pooling user requirements
• Providing a forum where association members can exchange experiences
• Setting up expert committees, task forces, and initiatives, particularly for scientific-technical standardization issues and certification processes
• Information and further training measures
• PR and communication
• Helping to draw up and frame guidelines and regulatory processes  
   

The following organizations have already agreed on the foundation of the chartered association by signing a Memorandum of Understanding (MoU):       

• Atos IT Solutions and Services GmbH
  
• Bayer HealthCare AG
• Boehringer Ingelheim Pharma GmbH & Co.KG
• Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.
• KOMSA Kommunikation Sachsen AG
• PricewaterhouseCoopers AG
• REWE Systems GmbH
• Robert Bosch GmbH
• Salzgitter AG
• SICK AG
• TyssenKrupp AG
• TÜV Nord AG
• Volkswagen AG
• ZVEI - Zentralverband Elektrotechnik- und Elektronikindustrie e.V.
   

The chartered association will be open for all enterprises, industry associations and non-for-profit organizations.

The Industrial Data Space architecture comprises all components necessary for the secure exchange and easy combination of data within business ecosystems. The overall architecture can be divided into four sub-architectures:   

• Governance architecture lays down the "rules of the game" and addresses issues around the visibility of data sources, data quality, and the consideration of data in terms of value.
  
• Security architecture addresses issues around the secure exchange of data, the recognition of anomalies, and data protection.
  
• Functional software architecture identifies and describes the Industrial Data Space software components, which include the Industrial Data Space Connector, an app store for Industrial Data Space data services, and components for the registration and certification of data services and data sources.
  
• Technology architecture comprises the technologies required to pilot the other three sub-architectures in the use cases.
  
  

All sub-architectures are described in the reference architecture model which is open and designed to be implemented also by third party technology providers.

The Industrial Data Space materializes as the entirety of all endpoints, i.e. all Industrial Data Space Connectors. Thus, the Industrial Data Space is no central data lake, but rather follows a federated architectural approach.

Key features are:

• Secure data supply chain from data capture to data use in smart services.
• Flexible endpoint scenarios: in other words, the Industrial Data Space Connector can be implemented in traditional company IT environments, but also in cloud environments and in production and logistics devices and vehicles .
  
• Lightweight semantics.
• Easy combination of different data goods.
• Configurable reference architecture model.
• Support of domain-specific governance models.
• Standardized collaborative data management processes.
• Open development process . 
   

The Industrial Data Space pursues an ambitious goal. Thus, the following aspects are out of scope:

• The Industrial Data Space does not aim at a central data storage instance.
• The research project does not result in a market-ready product, but in a reference architecture model and its use case pilots. The latter, of course, form the foundation for marketable products.
• The Industrial Data Space itself will not deliver functional smart services (such as freight exchanges etc.). It rather offers data services that form the infrastructural foundation for the easy and efficient development of the former.
• The Industrial Data Space does not contribute to data transmission networks or to real-time applications on shop floor level. Instead, it uses existing approaches. The Industrial Data Space focuses on data and data services.
• The Industrial Data Space itself does not drive domain-specific standardization (e.g. related to vocabularies or semantic standards). It rather makes use of existing standards and implements those in pilot applications.