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Trusted Secure Data Sharing Space

Periodic Reporting for period 1 - TRUSTS (Trusted Secure Data Sharing Space)

Reporting period: 2020-01-01 to 2021-06-30

With data being a resource of high significance in most industry sectors, a vibrant data economy and a successful Data Services Ecosystem in Europe are key factors conducive to sustainable employment, growth, societal stability and well-being. Rapid and sustainable adoption of data-driven innovation and digital transformation ensures competitiveness at international level.

TRUSTS aims to holistically enable the promise of the Digital Single Market by securing trust in the concept of data markets. Hence the TRUSTS platform is based on the experience of two major national projects (International Data Spaces and Data Market Austria), while allowing the integration and adoption of future platforms via interoperability. Concurrently TRUSTS maintains its strong focus on secure data sharing via privacy-preserving technologies. The TRUSTS platform is envisioned to act independently and as a platform federator. TRUSTS investigates the legal and ethical aspects across the entire data value chain, from data providers to consumers by i) setting up a fully operational and GDPR-compliant European Data Marketplace for (non-)personal data targeting individual and industrial use, and ii) demonstrating and validating the potential of the TRUSTS Platform in 3 use cases with corporate business data in the financial and operator industries. The integration is tested by 6 companies, including 2 data providers, thus co-creating a viable, compliant and impactful governance, legal and business model for the TRUSTS technology and use cases.
TRUSTS established (WP1) its framework, governance, roles, planning and monitoring guidelines, collaborative infrastructure, procedures and quality mechanisms for timely delivery of high quality project results.

Analysis of challenges and trends and definition of concrete, comprehensive functional requirements (WP2) considered the needs of vertical users and providers for concurrent, cross-domain, secure and scalable end-to-end (E2E) data marketplace services. Industry specific scenarios were enriched with long-term KPIs. The set up framework for the technological and business validation of the E2E data marketplace service evolves for trials evaluation, benchmarking and E2E expandable architecture.

As per DevOps principles, continuous releases of the TRUSTS platform (WP3) identified requirements to integrate future platforms. The specification of TRUSTS’ semantic layer, taxonomies, ontologies and metadata schemas support the functionality of its knowledge graph, whose flexibility allows extensions via additional services without affecting the existing mechanism for metadata ingestion.

Methods, e.g. homomorphic encryption, multiparty computation and data (de-)anonymization (WP4), were implemented and tested on financial, textual, and spatio-temporal datasets, yielding scientific papers and functionalities for the TRUSTS platform; e.g. deep transfer learning model combined with homomorphic encryption, leading to fast runtimes and high performance on classification problems.

The test environment for the 3 use cases was set up (WP5) for the advanced field trials in the sectors of Financial Institutions, Telecom Operators and Corporate data providers. The testbench demonstrated via actual field trials that the TRUSTS Platform can support KPI requirements, overall planning, deployment and testing activities.

Thorough analysis of relevant European laws and regulations (WP6) focused on legal and ethical aspects of data markets and data sharing, i.e. privacy, data protection, regulation on free flow of non-personal data, data ownership, sovereignty, contractual considerations of data sharing agreements, role of platforms and/or intermediaries in data sharing, financial data framework, anti-money laundering rules, Payment Service Directive, convergences/divergences with GDPR, competition law, information exchange, refusal to deal data, intersection of competition law, data protection law, blockchain technology, data-driven discrimination, data bias, and AI ethical guidelines.

Research in data markets and data market federation yielded the business-model centric, unified taxonomy as basis to identify and select viable business models (WP7). The initial approach to exploitation and commercialization will further integrate business model options into product-market-fit, via stakeholder engagement. Data stewardship and IP protection inform auxiliary services of a future data market operator, and ease data preparation for onboarding of data sellers.

The strategy for dissemination and communication (WP8) is implemented via the exact media mix, maximising impact towards a vast range of audiences, including brand, visual identity, channels, action plans, and digital tools to disseminate results.

The Ethics Screening (EthSR) resulted in 6 resolved pre-grant (POPD) and 10 addressed post-grant ethics requirements (WP9). As requested, consent forms were updated and further information on ML/AI and anonymisation was collected.

Hence the key objectives are on a good path towards achieving the DoA requirements and adhering to the DSM strategy.
TRUSTS produces numerous multidisciplinary innovations. Its process for combining data with technology support in a GDPR compliant manner does not currently exist in a uniform nor sustainable manner in large and sensitive business environments, e.g. financial institutes and operators. Its privacy-aware recommender systems minimise data volume and optimise the accuracy-privacy trade-off.

The TRUSTS toolkit provides privacy metrics and anonymisation methods, exceeding tabular data limitations of current SoA open-source tools and working with complex, high-dimensional datasets. The TRUSTS metadata schema builds on top of existing schemas, e.g. DCMI, and is designed to cover data assets, i.e. data sets, products and related applications or ML models. The TRUSTS protocol is designed for interoperability between a selected set of third-party data markets and EOSC initiatives. It will be built on top of and extend existing solutions, e.g. OAI-PMH and ResourceSync. A module that can be integrated into a common data management platform (CKAN) enables information exchange about data products across federated data markets networks. An external data market should be able to integrate this software library with ease and expose information about its data products to TRUSTS, serving as a basis for connecting TRUSTS with EOSC. Current SOA tools upload, archive, and share data sets, whereas interoperability with existing third parties, e.g. other data markets or EOSC, is not part of their portfolio; thus the TRUSTS component will close this gap.

Prototypical implementations are aligned with architectural goals, design principles and policies of the IDS and Gaia-X initiatives. TRUSTS supports innovative approaches and the vision for a European data market based on European values and standards. TRUSTS provides a unified business-model centric taxonomy for data markets and their federation, prioritising standardization requirements to enhance interoperability within the European data economy. It contributes to the implementation of the European Data Strategy, via feasibility demonstration, seeding for ubiquitous explorability and use of data assets availed in open data cloud-systems (e.g. EODC). TRUSTS collaborates with local and pan-European initiatives and projects, such as DMS Accelerator, SEED, and Gaia-X.