The EU-funded TrustED project is moving privacy-preserving data sharing from technical design into real-world validation. Its two pilots combine digital identity, user-controlled credentials and privacy-enhancing technologies to help organisations collaborate and analyse information without routinely exposing sensitive underlying data. For European businesses, the work offers a practical view of how future data spaces could support cooperation while preserving privacy and control.
TrustED stands for Enabling Trustworthy European Data Spaces through Self-Sovereign Identity and Privacy Preserving Technologies. The project is developing a secure, interoperable identity framework designed to work with the European Digital Identity Wallet. Its aim is not simply to transfer data more securely. It is to let people and organisations prove relevant facts, manage verifiable credentials and participate in data-sharing arrangements with greater control over what is disclosed.
The European Commission's CORDIS feature on TrustED highlights the project as part of Europe's effort to create secure, human-centred digital infrastructure. TrustED has also been featured as a CORDIS Project of the Month, reflecting its place in the wider European data-sharing and digital-identity landscape.
From identity design to two applied pilots
TrustED's current work is most concrete in two pilots. One focuses on collaboration between volunteers and non-governmental organisations. The other examines clinical data analysis across institutions. They address different sectors, but both test a shared proposition: useful collaboration should not require every participant to hand over all of their underlying sensitive information.
| Area | TrustED pilot | What it is evaluating |
|---|---|---|
| Volunteering and NGOs | A self-sovereign identity wallet for managing verifiable credentials, linked to a data-space dashboard for volunteering opportunities. | Cross-organisation collaboration and user control over credentials. |
| Clinical data analysis | A federated learning setup for analysing clinical data without sharing raw data. | Governance, clinical workflows and trust in cross-institution collaboration. |
In the volunteering pilot, a wallet gives volunteers and NGOs a way to manage verifiable credentials. The related data-space dashboard is intended to support access to volunteering opportunities across organisations. The pilot therefore tests a common data-sharing obstacle: how several organisations can rely on trustworthy credentials without creating unnecessary copies of personal information in each system.
The clinical pilot uses federated learning, an approach in which data analysis can be performed while raw data remains with the institution that holds it. TrustED is evaluating this setup alongside governance, clinical workflows and trust. That scope matters because privacy-preserving technology has to fit real operational processes, not only work in a technical demonstration.
The privacy technologies behind the pilots
TrustED brings several privacy-enhancing technologies, often called PETs, together with self-sovereign identity and the European Digital Identity Wallet. The official project materials cite:
- Federated learning, which supports analysis without centrally sharing raw data.
- Zero-knowledge proofs, which can enable a party to demonstrate a fact without disclosing more information than necessary.
- Homomorphic encryption, a technique intended to enable computation on encrypted information.
- Differential privacy, which is designed to reduce the risk of identifying individuals in analytical outputs.
These technologies serve different purposes. Federated learning addresses where data is analysed, while cryptographic and statistical techniques can limit what is revealed in verification and analysis. TrustED's contribution is the attempt to make these elements work together in a data-space setting where digital identity, consent, credentials and collaboration need to interact.
What TrustED could mean for business data strategies
TrustED does not establish a finished, generally available business product or a universal data-sharing standard. The project is still advancing through implementation and pilot evaluation. Its relevance is that it tests building blocks that may be useful where organisations need to collaborate but cannot, or should not, freely exchange raw personal or commercially sensitive data.
For example, a company working with partners may need to verify that an individual has a valid role, qualification or permission. A verifiable credential could potentially reduce the need for repeated manual checks and avoid sharing a full record when only one attribute needs to be confirmed. Similarly, organisations with complementary datasets may be interested in joint analysis, but unable to centralise those datasets because of sensitivity or trust concerns. Federated approaches point to a different model: take analysis to the data rather than automatically moving data to a shared repository.
The pilots also underline that privacy is not only an encryption question. A workable arrangement needs clear identity controls, credible credentials, compatible systems and workflows that participants can actually use. Businesses considering participation in European data spaces should therefore assess more than the volume of data they possess. They should identify which data can be shared, which facts need to be verified, who controls access and whether a proposed collaboration can deliver value without disclosing raw records.
What happens next will depend on the results of TrustED's pilots and its continuing work on integration with Europe's digital-identity and data-space infrastructure. The confirmed progress is meaningful, but the supplied project information does not specify a commercial rollout date, broad market availability or pricing. Readers should treat TrustED as an active validation effort, rather than assume that all of its capabilities are ready for routine deployment.
For businesses exploring secure partner data flows, the lessons from TrustED are immediate: define the minimum information a process needs, then design identity and access around that requirement. Scalevise can help translate that principle into an adoption roadmap, assess suitable AI and privacy-focused use cases, and connect practical technology choices to existing operations. Explore Scalevise's AI consultancy to request a consultation on a practical data and AI strategy.
Frequently Asked Questions
What is the TrustED project?
TrustED is an EU-funded project developing a secure, interoperable digital identity framework for European data spaces. It combines self-sovereign identity with privacy-enhancing technologies and is designed to work with the European Digital Identity Wallet.
What pilots has TrustED demonstrated?
TrustED has demonstrated a self-sovereign identity wallet for volunteers and NGOs, linked to a volunteering data-space dashboard, and a federated learning setup for secure clinical data analysis across institutions.
How does federated learning protect sensitive data?
Federated learning enables data analysis without sharing raw data centrally. In TrustED's clinical pilot, it is being evaluated for cross-institution collaboration alongside governance, clinical workflows and trust.
Is TrustED a commercially available product?
The supplied project information describes TrustED as an active research and validation project. It does not specify broad commercial availability, a rollout date or pricing.
Why should businesses follow TrustED?
TrustED is testing approaches that could help organisations verify credentials and conduct collaborative analysis while limiting exposure of personal or sensitive data. Its results may be relevant to organisations planning participation in European data spaces.
Conclusion
TrustED's significance lies in its shift from architecture to applied testing. By validating identity wallets and privacy-preserving analytics in volunteering and clinical settings, the project is examining whether European data spaces can support useful collaboration without making broad raw-data sharing the default. The pilots will not answer every implementation question, but they provide a concrete reference point for organisations building more privacy-conscious data strategies.
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