Interoperability Unleashed: The TCK Approach to Flawless Data Spaces

Data spaces are evolving rapidly, and ensuring interoperability between various centralized, federated, and decentralized services across different versions is a complex challenge.

Peter Koen has written a new LinkedIn article about A multi-layered perspective on Dataspaces & Trusted Data Sharing , which aligns well with your focus on interoperability in data spaces. His multi-layered perspective on data spaces provides a comprehensive framework that can help explain the importance of certification in achieving interoperability, particularly in the context of Catena-X .

Peters approach a general-purpose conceptual layered framework for interoperable data spaces involves:

1. Technical Layer: This layer focuses on "connecting agents" and involves the protocols and technologies that enable data sharing
2. Business Layer: This layer is about "connecting organizations" and deals with the economic models and business relationships within dataspaces
3. Legislation Layer: This layer addresses "connecting nations" and considers the legal and regulatory aspects of data sharing across jurisdictions

Catena-X providing a service map . Open-Source and Commercial Business applications addressing pressing challenges of the industry and using the data space operating components.

For the interoperability of business applications and the centralized and decentralized data space services you can use:

1. International Data Spaces Association (IDSA) defined a high level certification scheme and Criteria Catalogue: Components - Connector and Operational Environments in the certification working group.
2. The Eclipse DataSpace Working Group (EDWG ) is working on the TCK toolkit to ensure the data space compliance with existing standards.
3. Catena-X published the industrial grade certification process and a conformity assessment handbook .

What is a TCK?

While the Technology Compatibility Kit (TCK) is primarily associated with Java platform compliance, the concept of compatibility testing can be applied to data spaces as well.

The Technology Compatibility Kit was introduced by Sun Microsystems to run 130.000+ automated tests for Java 8 and 11. The Java SE TCK is intellectual property of Oracle and needs to be licensed. The Java Enterprise Edition (JEE) TCK its published under a open-source license.

With the data space specific Compliance Verification Framework (CVF) we want to ensure the interoperability with an automated test suite of

• Dataspace connectors with the Dataspace Protocol (DSP): https://lnkd.in/g8pGFswP
• Identitity providers with the Decentralzed Claims Protocol (DCP)

The TCK approach define testing combinations in an agile development lifecycle for data spaces:

Benefits of a TCK-like Approach for Data Spaces

• Ensuring Interoperability: A TCK test suite for data spaces verify that different components and services can interact correctly, regardless of their versions or providers.
• Standardization: promote adherence to common standards and specifications, crucial for the decentralized nature of data spaces.
• Rapid Validation: In an agile development cycle, quick validation of new versions against established standards during the development process its very beneficial.
• Cross-Version Testing: testing of various combinations of minor and major versions of different services within one and different data space ecosystems

Challenges and Considerations

• Complexity: Data spaces involve multiple components and standards, making comprehensive testing more complex than traditional TCKs.
• Evolving Standards: As data space standards and reference implementations are still evolving, the test suite would need frequent updates.
• Decentralized Nature: Unlike Java's centralized TCK, a data space TCK might need to be more distributed to reflect the decentralized architecture. Especially to test commercial applications independently.
• Performance Considerations: data space testing need to incorporate performance metrics crucial for real-world operations. Every little change on basis components can have a huge impact to the performance of complex data processing in a global network

Implementation of TCK

• TCK Working Group: setup a subproject Eclipse Dataspace TCK in the Open Source Community (EDWG)
• Automated Test Suites: create a code repository for a Compliance Verification Framework, can easily integrated into CI/CD pipelines for continuous validation
• Modular Testing: Create modular tests that can be combined to test different aspects of data spaces (e.g., data sovereignty, interoperability, security).
• Version Matrix: Implement a version matrix to systematically test combinations of different component versions.
• Real-world Scenarios: Include tests that simulate real-world data sharing scenarios across different domains via REST-API based end-to-end tests
• Compliance Certification: Extend the manual a certification process for data space components with automated tests

Best Practises to implement TCK Testing environments

Test Data Management for Integration Tests

• Version-specific Test Data: Create and maintain separate datasets for each version of each application and system components.
• Data Versioning: versioning system for our test data, aligning it with our software versions.
• Synthetic Data Generation: generate synthetic data mimicking real-world positive and negative scenarios for each version.
• Data Subsets: different integration scenarios and versions for each data application

Environment Management for Integration Tests

• Sandboxes: Catena-X defines a new role Sandbox Provider that provide a development (Sandboxes ) and test environment for application development
• Environment Versioning: Maintain separate test environments for different versions. Use docker containers to create isolated, version-specific environments.
• Environment Configuration Management: maintain different configurations for each version. You can use Github environments or Terragrunt .

Best Practices to implement TCK

• Central Test Repository: Maintain all test cases on a central place and give access to the open source community
• Demand Management: allocate test environments based on version- and application specific testing needs.
• Automation: Automate as much of the test data and environment management process as possible to ensure consistency across versions.
• Clear Version Mapping: between software versions, test data versions, and environment configurations.
• Continuous Integration, Deployment and Tests: Every check-in will start various integration tests in the CI/CD pipeline

Rules for Test Generation

General Test Rules

• All tests must be version-specific and clearly labeled.
• Tests must be reproducible and deterministic.
• Each test should focus on a single aspect of interoperability.

Test Result Reporting

• Generate detailed reports for each test run
• including version information and environmental details.
• Establish clear pass/fail criteria for each test case.
• Provide for the certification process for applications that pass all relevant TCK tests.

Dataspace Core and Enablement Services Testing

Datapace Connectivity (EDC)

• Test of various dataspace connectors with the Dataspace Protocol (DSP)
• Test data transfer between participants using different protocols.
• Verify data integrity during exchange.
• Test handling of different data formats and schemas.

Identity and Access Management

• Test cases for Identitity providers comply Decentralized claims protocol (DCP)
• Test user authentication across different dataspace participants.
• Verify role-based access control consistency.
• Ensure identity federation works across various identity providers.

Data Sovereignty (ODRL Policies)

• Verify enforcement of data access and later usage policies across participants.
• Test policy negotiation and conflict resolution mechanisms.
• Ensure data deletion and right to be forgotten are respected across the dataspace.

Metadata Management (DCAT catalog, Digital Twins)

• Test consistency of metadata across different dataspace nodes.
• Verify semantic interoperability of metadata from different sources.
• Test metadata search and discovery across the dataspace.

Extended TCK Tests

TCK is focusing on verification on international standards like DSP and DCP. Catena-X also defines further standards. Longterm TCK can be extended to these Catena-X standards.

Standards and Guidelines

• support developers in order to accelerate the development of services and applications to contribute significantly to the rapid scaling. Catena-X ecosystem provides the KITS .
• Publish standards for each provider for applications, core and enablement services for each release. Catena-X is provide all standards for each provider role
• Define the incoming and outgoing dependencies of all standards

Other Tests to Ensure the Stability

End-to-end Integration Testing

TCK focuses specifically on verifying compliance with specifications, while E2E testing validates the entire system's functionality from a user perspective and is part of the Test Management of the Catena-X Working Model :

• Create isolated sandbox environments for each major version of dataspace components.
• Sandboxes should mimic real-world dataspace configurations, including multiple participants.
• Each sandbox should have predefined datasets and configurations for reproducible testing.
• Implement automated setup and teardown of sandbox environments for each test run.

Dependency Version Testing

TCKs are designed for compatibility testing, which is distinct from product testing. They are not concerned with aspects like robustness, performance, or ease of use. This part will be covered by the Life Cycle Management of the Catena-X operating model .

• Test interactions between different versions of dataspace components.
• Verify backward compatibility with at least two previous major versions.
• Test scenarios involving multiple dataspace participants using different software versions.
• Include cross-domain data space interoperability tests

Performance and Scalability

In summary, while TCK testing is crucial for ensuring specification compliance and interoperability, it does not address performance and scalability aspects. These factors would need to be evaluated through separate performance testing and real-world usage scenarios.

• Test data exchange performance across different scales of dataspace participants.
• Verify system behavior under varying loads and data volumes - define load tests with JMeter
• Test the scalability of metadata management and search across large numbers of data assets.
• Store the results of each load test run and compare it with the run before, to detect performance issues during the development time already

Security and Compliance

While not part of the TCK, there are separate tools like OWASP Dependency-Check that can be used to scan for known vulnerabilities in project dependencies

• Establish a Security Release Guideline and automated security tools in the development pipeline. Catena-X established the TRG guidelines for Security .
• Setup a private vulnerability reporting
• Test enforcement of encryption standards across dataspace communications.
• Test security measures against common attack vectors in a distributed web environment with OWASP Security guide and WSAP plugin .
• Verify compliance with data protection regulations (e.g., natural persons of GDPR)

Logging and Auditing

While logging and auditing are important aspects of many software systems, especially for security and compliance purposes, they do not appear to be within the scope of standard TCK testing:

• Test consistency of audit logs across different services and participants.
• Verify the integrity and non-repudiation of distributed logs.
• Test log aggregation and analysis across the dataspace.