International data spaces

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The International Data Spaces (IDS) are an initiative with the aim of creating a secure, cross-domain data space that enables companies in various industries and of all sizes to manage their data with confidence . The basis for this is a reference architecture model is that under the same name, from the Federal Ministry of Education and Research funded research project by twelve institutes of the Fraunhofer-Gesellschaft under the leadership of Boris Otto ( Fraunhofer ISST) was developed. The initiative for the International Data Spaces is not limited by geographical borders, but has a European or international orientation. To stabilize the activities, the initiative has been institutionalized in the form of the registered International Data Spaces Association, which was founded on January 26, 2016 in Berlin. The activities were previously carried out under the name "Industrial Data Space".

Background and goals

The International Data Spaces can be a link between digital production / logistics and smart services.

As part of the currently targeted Industry 4.0 , digitization is fundamentally changing companies, as it enables new business models and changes the self-image of entire industries. Companies are therefore required to join digitization and secure their competitiveness . As a result, digitization means that data makes a significant contribution to corporate success. The exchange of data also leads to the risk of losing your own data sovereignty. International Data Spaces solve this conflict of objectives with their unique architecture concept. The owners of data do not give up their data sovereignty when exchanging data. Data sovereignty is the exclusive and sovereign decision-making authority over the use of one's own data . The implementation of the usage restrictions takes place through special usage policies so that all participants can participate in the transparent data exchange. Confident data exchange is thus a core competence of digitization and the International Data Spaces offer the associated technology.

Logically, their digitization also includes the exchange of data. The secure exchange of data and the simple combination in value creation networks are prerequisites for smart services , innovative services and automated business processes . Against this background, the International Data Spaces have already attracted attention in German and foreign politics.

The data-driven innovation manifests itself in four facets:

Innovation category Example for the International Data Spaces
Product innovation In the pharmaceutical industry, the use of health data allows more effective, more individualized drugs and treatment concepts. To do this, various actors in an ecosystem have to work together, such as suppliers of pharmaceutical products, health insurance companies, healthcare providers and patients. At the same time, the patient must retain control over their own data at all times.
Service innovation Modern traffic management not only uses traditional information such as map material or traffic reports for route planning and navigation of vehicles, but route calculations are made dynamically using various data sources, such as traffic control centers.
Process innovation The retail trade avoids “ out of stock ” situations on the supermarket shelf by linking the flow of goods with the flow of information at all times. Data on the transported goods (location, condition, etc.) are available to all partners in the value-added network at all times, so that retailers, suppliers and logistics service providers can jointly control and monitor their supply chain . In this way, data becomes a common good from which all value creation partners benefit.
Organizational innovation The production of small series in the automotive industry , for example for electric vehicles, is based on the self-control of vehicles and components. For this purpose, master data of the products, order data , transport details, etc. must be managed jointly and securely in the ecosystem of manufacturers, suppliers and logistics service providers.

In order to utilize this innovation potential, the International Data Spaces provide data services that include, for example, the anonymization of data, integration services and the setting of "expiration dates" for data usage. In this way, the International Data Spaces support companies in their digital transformation.

Features and structure

Interaction of the components of the International Data Spaces

The International Data Spaces are made up of the entirety of all endpoints (connectors) as well as various components (software) such as brokers , clearing houses , identity providers and app stores . The connector represents a standardized interface to the International Data Spaces for the participating companies. This access point enables, on the one hand, targeted and controlled provision of their own data, and, on the other hand, authorized access to the data of other participants. The International Data Spaces are therefore not a central data store, but rather follow a federal architecture concept.

Connector

The connector is software that is installed at the participating company or on a platform and thus provides technical access to the IDS ecosystem. The connector can be monolithic or closed software or simply a combination of different existing software that follows the specifications of the reference architecture model and the International Data Spaces certification criteria based on it. The Fraunhofer-Gesellschaft provides a framework for developing an International Data Spaces Connector. The International Data Spaces Framework aims to encapsulate infrastructure components in order to simplify the development of an International Data Spaces Connector. This should enable the developer to concentrate entirely on the implementation of the application logic. The connector architecture uses application container management technology to provide an isolated and secure environment for individual data services.

Broker

The IDS broker consists of a connector and provides the necessary interface for any communication between different connectors in the IDS. Data sources are saved on the broker in the form of a metadata repository and can be accessed by other connectors. The following services are performed by the IDS Broker for data sources: Registration, publication, maintenance and index-based queries . In addition, machine-readable descriptions conforming to the IDS information model can be created and heartbeats can be carried out in order to detect inactive connectors.

Clearing house

The Clearing House (Engl. Clearing House ) is created by an intermediary in the settlement services in the IDS. For this purpose, the financial and data transactions are logged at the clearing house to ensure correct execution. The clearing house and broker are technically separate from each other, but can be carried out by the same organization.

Identity provider

The identity provider (Engl. Identity Provider ) provides an identity management to modern standards and with low organizational requirements for the IDS. The registration authority provides services for the creation, maintenance, monitoring and validation of identity information. The registered connectors are managed by a Dynamic Attribute Provisioning Service attribute server. This is needed to manage requests from connectors to each other. However, access is always approved by the registered connectors themselves.

App Store

Different data applications can be used in one connector to facilitate data processing workflows. For this purpose, data applications, so-called data apps, are provided in an app store. The App Store contains information about data apps that are added by data app providers. The IDS App Store offers various search options to find data apps.

General key characteristics

The following key features result from this concept:

  • Secure data value chain from the creation of the data to its use in smart services
  • Flexible endpoint scenarios, i. H. An International Data Spaces Connector can be implemented in classic corporate IT environments, but also in cloud environments or on devices and vehicles in production and logistics
  • Lightweight semantics based on domain-specific vocabularies
  • Simple combination of different data assets
  • Configurable reference architecture model
  • Support of domain-specific governance models
  • Standardized collaboration processes for data management
  • Open development process

focus

In order to do justice to the actual focus of the initiative and to use existing preparatory work sensibly, the following work is not a goal and part of the International Data Spaces:

  • A central instance for data storage is not provided (see GAIA-X ).
  • The result of the research project is not a product, but the reference architecture model and the pilot implementations. Subsequent product development is possible on this basis.
  • No professional smart services (e.g. freight exchanges or the like) are developed. Rather, through the data services, the International Data Spaces provide the basis for the simple and efficient development of such services.
  • The International Data Spaces do not make a contribution on the data transmission level or for the real-time area , but rather draws on existing approaches.
  • There is no overarching domain-specific technical standardization (e.g. in the form of vocabulary, semantic standards), but existing work is also used here.

Reference architecture model

The architecture of the International Data Spaces describes in a model all components that are required for a secure exchange and a simple combination of data in the ecosystem, and is divided into four sub-architectures:

  1. Governance architecture: It lays down the "rules of the game" and regulates, among other things. a. the visibility of data sources, the data quality and the value-based consideration of the data.
  2. Security architecture : It ensures the secure exchange of data, the detection of anomalies and data protection.
  3. Technical-functional software architecture : It names and describes the software components of the International Data Spaces, which include the International Data Spaces Connector, an AppStore for data services for the International Data Spaces and modules for the registration and certification of data services and sources.
  4. Technical architecture : It comprises the technologies required to pilot the other three sub-architectures in the use cases.

The reference architecture model and the description of these partial architectures contained therein is open and can be taken up and implemented by third parties. Version 3 of the reference architecture model was published in April 2019.

Research projects on the International Data Spaces

The architecture of the International Data Space has been developed by the Fraunhofer-Gesellschaft as part of a research project funded by the Federal Ministry of Education and Research (BMBF) since October 2015 (grant number 01IS15054). The research project had two main goals:

  • Draft of the reference architecture model for the International Data Spaces
  • Piloting the reference architecture model in selected use cases

The second phase, also funded by the Federal Ministry of Education and Research and processed by the Fraunhofer-Gesellschaft , started on October 1, 2017 . Your goal is to establish the reference architecture developed in the first phase internationally. It is important to develop a uniform solution that is compatible with existing international models such as that of the Industrial Internet Consortium from the USA or the Industrial Value Chain Initiative from Japan.

Boris Otto was and is the head of both research projects .

The work is closely interlinked and coordinated with the Industry 4.0 platform . Project participants in the research project work in the working groups of the platform. The International Data Spaces are shown on the "Map of Industry 4.0", which was presented at the 2015 National IT Summit . Further research projects in which the International Data Spaces are further developed or used are (incomplete list):

  • AMable - Additively Manufacturable (EU)
  • T-Systems data intelligence hub
  • Data Ports (EU)
  • EIT Food Digital Twin (EU)
  • EOSCpilot - The European Open Science Cloud for Research Pilot Project (EU)
  • Fraunhofer Cluster of Excellence Cognitive Internet Technologies (CCIT)
  • GAIA-X
  • German Edge Cloud
  • Industry 4.0
  • Industry 4.0 legal testbed (BMWi)
  • MIDIH - Manufacturing Industry Digital Innovation Hubs (EU)

International Data Spaces Association (formerly: Industrial Data Space Association)

The non-profit association Industrial Data Space e. V. was founded on January 26, 2016 in Berlin with 18 founding members and renamed the International Data Spaces Association eV with effect from November 26, 2018. The association offers companies, research institutions, associations and initiatives in several working groups the opportunity to help shape the International Data Spaces. To this end, it bundles the requirements from business to the International Data Spaces, organizes the exchange of experience between science and business and develops guidelines for the certification, standardization and exploitation of the results of the International Data Spaces research project.

The following tasks and goals emerge:

  • Standardization and certification
  • Information and training for SMEs
  • Bundling of user requirements and use cases
  • Cooperation with related initiatives
  • Representation of interests at EU level

In addition to a cooperation with the OPC Foundation , activities for networking with the Industrial Internet Consortium , the Industrial Value Chain Initiative, the FIWARE Foundation and the Industrie 4.0 platform are taking place.

Web links

Individual evidence

  1. ↑ Neugebauer, Reimund; ten Hompel, Michael; Wrobel, Stefan: Industrial Data Space. Digital sovereignty over data and services . Fraunhofer Society brochure.
  2. ↑ BMWi: Platform Industry 4.0 provides a preview of IT summits . Press release, November 5, 2015
  3. ↑ Fraunhofer initiative for a secure data room starts . Press release from the Fraunhofer Society. 23rd August 2015
  4. ^ International Data Spaces Association. In: International Data Spaces Association. Retrieved May 27, 2020 (American English).
  5. ↑ Industrial Data Space eV founded . Press release from the Fraunhofer-Gesellschaft, January 26, 2016. Accessed March 19, 2016.
  6. ↑ THE NAME NOW CLEARLY SHOWS THE STRATEGIC ORIENTATION. In: International Data Spaces Association. Retrieved May 25, 2020 (American English).
  7. ↑ Otto, Boris: Industrial Data Space at a Glance. October 2015, p. 6.
  8. ^ Knüpffer, Gunnar: Industrial Data Space. Data exchange without Google. In: Production, June 17, 2015
  9. ↑ a b c d e f g h i j k l m International Data Spaces Association (Ed.): Reference Architecture Model. Version 3.0. Dortmund April 2019 ( internationaldataspaces.org [PDF; accessed November 26, 2019]).
  10. ↑ International Data Spaces - Business Challenges. In: www.dataspaces.fraunhofer.de. Fraunhofer-Gesellschaft, accessed on May 27, 2020 .
  11. ↑ International Data Spaces - Usage Control. In: dataspaces.fraunhofer.de. Fraunhofer-Gesellschaft, accessed on May 27, 2020 .
  12. ↑ Prof. Dr. Boris Otto: Data sovereignty as a key skill in the age of digitization. In: www.cit.fraunhofer.de. Fraunhofer Cluster of Excellence Cognitive Internet Technologies, accessed on May 27, 2020 .
  13. ^ German Bundestag. Application by the parliamentary groups of the CDU / CSU and SPD: Industry 4.0 and Smart Services , November 10, 2015, p. 8.
  14. ↑ Wanka, J .: Advice on the application from CDU / CSU and SPD "Industry 4.0 and Smart Services - economic, labor, education and research policy measures for digitization and intelligent networking of production and value chains". Speech by the Federal Minister for Education and Research Johanna Wanka in the German Bundestag. November 13, 2015.
  15. ↑ UK Science & Innovation Network: Science and Innovation developments in Germany , March 2015, p. 2.
  16. ↑ Industrial Data Space - data as a strategic resource for business innovation . Fraunhofer Society website. Retrieved November 5, 2015.
  17. ^ Medical Data Space. In: www.medical-data-space.fraunhofer.de/. Fraunhofer-Gesellschaft, accessed on May 27, 2020 .
  18. ↑ BMVI: Linking municipal, regional and national data platforms through data space concepts as well as refining and processing as a mobility data ecosystem - Mobility Data Space. In: www.bmvi.de. Federal Ministry of Transport and Digital Infrastructure, accessed on May 27, 2020 .
  19. ↑ New logistics community pushes forward development of digital business models - Fraunhofer IML. In: Fraunhofer Institute for Material Flow and Logistics IML. Fraunhofer-Gesellschaft, accessed on May 27, 2020 (English).
  20. ↑ Boris Otto, Hubert Österle: Corporate Data Quality: Prerequisite for Successful Business Models . 1st edition. 2016. Springer Gabler, Dortmund, St. Gallen 2016, ISBN 978-3-662-46806-7 .
  21. ^ Otto, Boris: Industrial Data Space. Brief Overview. Dortmund, October 2015, p. 4.
  22. ↑ International Data Spaces - Connector. In: www.dataspaces.fraunhofer.de. Retrieved May 26, 2020 .
  23. ↑ a b International Data Spaces - Framework. In: www.dataspaces.fraunhofer.de. Retrieved May 26, 2020 .
  24. ↑ a b c International Data Spaces - Metadata Broker. In: www.dataspaces.fraunhofer.de. Retrieved May 26, 2020 .
  25. ↑ a b International Data Spaces - Identity Provider. In: www.dataspaces.fraunhofer.de. Retrieved May 26, 2020 .
  26. ↑ International Data Spaces - Appstore. In: www.dataspaces.fraunhofer.de. Retrieved May 26, 2020 .
  27. ↑ Industrial Data Space - key features of the Industrial Data Space website of the Fraunhofer Society. Retrieved November 5, 2015.
  28. ↑ Otto, B .; Lohmann, S. u. a .: Reference Architecture Model for the Industrial Data Space . Ed .: Fraunhofer-Gesellschaft, Munich, 2016
  29. ↑ Industrial Data Space eV: Fraunhofer-Gesellschaft research project on Industrial Data Space enters its second round. ( Memento from September 21, 2017 in the Internet Archive ) Press release, October 2017.
  30. ↑ Fraunhofer ISST: Federal government and Fraunhofer are pushing ahead with the internationalization of Industry 4.0. Press release, July 27, 2017.
  31. ↑ Platform Industry 4.0: Industrial Data Space. Sovereignty over data in the digital economy. ( Memento from November 22, 2015 in the Internet Archive ) Entry on the Industry 4.0 map. 2015
  32. ^ BMWi: National IT Summit 2015. Latest news, November 19, 2015.
  33. ↑ T-Systems: Data Intelligence Hub | Marketplace for data & analytics. In: Deutsche Telekom AG. Retrieved May 27, 2020 .
  34. ↑ Implementing IDS. In: International Data Spaces Association. IDSA, accessed May 27, 2020 (American English).
  35. ↑ Fraunhofer CCIT. In: www.cit.fraunhofer.de. Fraunhofer-Gesellschaft, accessed on May 27, 2020 .
  36. ↑ Karin Zühlke: German Edge Cloud is launched: "The customer has full data control!" In: www.elektroniknet.de. Retrieved May 27, 2020 .
  37. ↑ Industrial Data Space - sovereignty over data in the digital economy. In: www.plattform-i40.de. Platform Industry 4.0, accessed on May 27, 2020 .
  38. ↑ Industrial Data Space eV founded. Press release of the Fraunhofer-Gesellschaft, January 26, 2016. Accessed June 23, 2016.
  39. ↑ https://www.internationaldataspaces.org/
  40. ↑ OPC UA system adapter ensures an easy integration into the IDS ecosystem ( Memento from January 18, 2017 in the Internet Archive ). Press release from the OPC Foundation on the Memorandum of Understanding with the Industrial Data Space Association. Retrieved June 30, 2017.