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A Survey of Dataspace Connector Implementations

Tobias Dam, Lukas Daniel Klausner, Sebastian Neumaier, Torsten Priebe

TL;DR

The paper tackles the interoperability and maturity challenges of dataspace connectors that implement IDS standards, aiming to enable secure, sovereign data exchange across organizations. It conducts a targeted survey of four open-source, IDS-compliant connectors (DSC, EDC, TRUE, Trusted Connector) and evaluates their architecture, data model, identity management, and usage control. The findings reveal consistent IDS architecture claims but divergent policy languages (ODRL, IDS Usage Control Language, LUCON) and substantial documentation deficits, which threaten cross-connector interoperability and uptake. The work highlights the need for standardized core components and benchmarking efforts to assess interoperability, performance, and scalability for practical deployment in industry.

Abstract

The concept of dataspaces aims to facilitate secure and sovereign data exchange among multiple stakeholders. Technical implementations known as "connectors" support the definition of usage control policies and the verifiable enforcement of such policies. This paper provides an overview of existing literature and reviews current open-source dataspace connector implementations that are compliant with the International Data Spaces (IDS) standard. To assess maturity and readiness, we review four implementations with regard to their architecture, underlying data model and usage control language.

A Survey of Dataspace Connector Implementations

TL;DR

The paper tackles the interoperability and maturity challenges of dataspace connectors that implement IDS standards, aiming to enable secure, sovereign data exchange across organizations. It conducts a targeted survey of four open-source, IDS-compliant connectors (DSC, EDC, TRUE, Trusted Connector) and evaluates their architecture, data model, identity management, and usage control. The findings reveal consistent IDS architecture claims but divergent policy languages (ODRL, IDS Usage Control Language, LUCON) and substantial documentation deficits, which threaten cross-connector interoperability and uptake. The work highlights the need for standardized core components and benchmarking efforts to assess interoperability, performance, and scalability for practical deployment in industry.

Abstract

The concept of dataspaces aims to facilitate secure and sovereign data exchange among multiple stakeholders. Technical implementations known as "connectors" support the definition of usage control policies and the verifiable enforcement of such policies. This paper provides an overview of existing literature and reviews current open-source dataspace connector implementations that are compliant with the International Data Spaces (IDS) standard. To assess maturity and readiness, we review four implementations with regard to their architecture, underlying data model and usage control language.
Paper Structure (27 sections, 5 figures, 2 tables)

This paper contains 27 sections, 5 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Background and Related Work
  3. Architecture.
  4. Data Model.
  5. Identity Management.
  6. Usage Control.
  7. Dataspace Connector Survey
  8. IDS Dataspace Connector (DSC)
  9. Architecture.
  10. Data Model.
  11. Identity Management.
  12. Usage Control.
  13. Eclipse Dataspace Connector (EDC)
  14. Architecture
  15. Data Model.
  16. ...and 12 more sections

Figures (5)

  • Figure 1: Interactions between the connectors and the other components in an IDS ecosystem, according to the IDS Reference Architecture idsram.
  • Figure 2: Example of an IDS catalog, resource, contract offer and permission in RDF Turtle syntax. The example uses the IDS Information Model Lange2022TheExchange.
  • Figure 3: Example Java code of an EDC policy for allowing read access and disallowing further distribution of an asset.
  • Figure 4: Example of a Contract Agreement in the MyData Usage Control Data App, written in the IDS Usage Control Language. The contract restricts the use by a given time interval.
  • Figure 5: Example of a LUCON policy to anonymize personal data before they are transmitted.