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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. Perspectives of the Reference Architecture Model
  2. 4 Perspectives of the Reference Architecture Model
  3. 4.3 Data Governance Perspective

4.3.7 Data Provenance

By creating transparency and offering clearing functionality, the International Data Spaces provides a way to track the provenance and lineage of data. This is strongly linked to the topics of data ownership and data sovereignty. Data provenance tracking can be implemented with local tracking components integrated into IDS Connectors and a centralized provenance storage component attached to the Clearing House (see Section 3.1.1), which receives all logs concerning activities performed in the course of a data exchange transaction, and requests confirmations of successful data exchange from the Data Provider and the Data Consumer. In doing so, data provenance is always recursively traceable. In, addition provenance information can be integrated into the IDS Vocabulary, so as to enable the participants to maintain data provenance as part of the metadata during the process of data exchange.

The International Data Spaces thereby provides the possibility to implement and use appropriate concepts and standards. However, it does not force participants to use these concepts and standards. It is therefore up to the individual participant to provide correct information (i.e., metadata) on the provenance of data.

Last updated 2 years ago