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IDS-RAM 4
IDS-RAM 4
  • README
  • Front Matter
    • Front Matter
    • Contributing Projects
  • Introduction
    • 1. Introduction
      • 1.1 Goals of the International Data Spaces
      • 1.2 Purpose and Structure of the Reference Architecture
      • 1.3 Relation to other IDSA assets
  • Context of the International Data Spaces
    • 2. Context of the International Data Spaces
      • 2.1 Data-Driven Business Ecosystems
      • 2.2 Data Sovereignty as a Key Capability
      • 2.3 Data as an Economic Good
      • 2.4 Data Exchange and Data Sharing
      • 2.5 Meaningful data
      • 2.6 Industrial Cloud Platforms
      • 2.7 Big Data and Artificial Intelligence
      • 2.8 The Internet of Things and the Industrial Internet of Things
      • 2.9 Blockchain
      • 2.10 Federated frameworks for data sharing agreements and terms of use
      • 2.11 General Data Protection Regulation
      • 2.12 Contribution of the International Data Spaces to Industry 4.0 and the Data Economy
      • 2.13 Privacy in the connected world
  • Layers of the Reference Architecture Model
    • 3 Layers of the Reference Architecture Model
      • 3.1 Business Layer
        • 3.1.1 Roles in the International Data Spaces
        • 3.1.2 Interaction of Roles
        • 3.1.3 Digital Identities
        • 3.1.4 Usage Contracts
      • 3.2 Functional Layer
      • 3.3 Information Layer
      • 3.4 Process Layer
        • 3.4.1 Onboarding
        • 3.4.2 Data Offering
        • 3.4.3 Contract Negotiation
        • 3.4.4 Exchanging Data
        • 3.4.5 Publishing and using Data Apps
        • 3.4.6 Policy Enforcement
      • 3.5 System Layer
        • 3.5.1 Identity Provider
        • 3.5.2 IDS Connector
        • 3.5.3 App Store and App Ecosystem
        • 3.5.4 Metadata Broker
        • 3.5.5 Clearing House
        • 3.5.6 Vocabulary Hub
  • Perspectives of the Reference Architecture Model
    • 4 Perspectives of the Reference Architecture Model
      • 4.1 Security Perspective
        • 4.1.1 Security Aspects addressed by the different Layers
        • 4.1.2 Identity and Trust Management
        • 4.1.3 Securing the Platform
        • 4.1.4 Securing Applications
        • 4.1.5 Securing Interactions between IDS components
        • 4.1.6 Usage Control
      • 4.2 Certification Perspective
        • 4.2.1 Certification Aspects Addressed by the Different Layers of the IDS-RAM
        • 4.2.2 Roles
        • 4.2.3 Operational Environment Certification
        • 4.2.4 Component Certification
        • 4.2.5 Processes
      • 4.3 Data Governance Perspective
        • 4.3.1 Governance Aspects Addressed by the Different Layers of the IDS-RAM
        • 4.3.2 Data Governance Model
        • 4.3.3 Data as an Economic Good
        • 4.3.4 Data Ownership
        • 4.3.5 Data Sovereignty
        • 4.3.6 Data Quality
        • 4.3.7 Data Provenance
        • 4.3.8 Data Space Instances
        • 4.3.9 IDS Rulebook
        • 4.3.10 Privacy Perspective
        • 4.3.11 Governance for Vocabularies
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  1. Context of the International Data Spaces
  2. 2. Context of the International Data Spaces

2.4 Data Exchange and Data Sharing

Last updated 2 years ago

Cross-company data exchange with the help of inter-organizational information systems is not a new topic; it has been around for decades. With the proliferation of Electronic Data Interchange (EDI) in the 1980s, many different data exchange scenarios have emerged over time, which were accompanied by the development of certain technical standards.

Figure 2.4.1: Evolution of technical standards for data exchange

The Figure above shows the evolution of technical standards for data exchange since the 1980s, using the example of automotive logistics. Data sovereignty, which is one of the main goals of the International Data Spaces, materializes in 'terms and conditions' that are linked to data before it is exchanged and shared. However, these terms and conditions (such as time to live, forwarding rights, pricing information etc.) have not been standardized yet. In order to foster the establishment of data sovereignty in the exchange of data within business ecosystems, more standardization activities are needed.

This does not mean that existing standards will become obsolete. Instead, the overall set of standards companies need to comply with when exchanging and sharing data needs to be extended. It is therefore necessary to distinguish between data exchange and data sharing (see also the Figure below:

  • Data exchange takes place in the vertical cooperation between companies to support, enable or optimize value chains and supply chains (e.g. EDI messages in logistics or HL7 in medical scenarios).

  • Data sharing takes place in the vertical and horizontal collaboration between companies to achieve a common goal (e.g. predictive maintenance scenarios in manufacturing) or to enable new business models by generating additional value out of data (e.g. in data marketplaces). Furthermore, data sharing implies a mode of collaboration towards coopetition.

Figure 2.4.2 : Data Exchange and Data Sharing

Evolution of technical standards for data exchange
Data exchange vs. data sharing