eBOS RnD

Trusted Secure Data Sharing Space

Duration: 01/01/2020 – 31/12/2022
Total Funding: € 5,977,631.25

Overview

Developing a cohesive Digital Single Market (DSM) in Europe is complex due to the fragmented landscape of national research projects, industry initiatives, and EU-level efforts. Legal and ethical challenges arise from competition law, intellectual property, data protection, and privacy regulations. The lack of trusted and secure platforms and privacy-aware analytics methods for sharing personal, proprietary, and industrial data hampers the creation of a viable data market and economy, confining most data sharing to open data. This trend will persist if differing technical standards, quality levels, and legal frameworks are allowed to diverge uncontrollably, undermining interoperability, trust, and cross-border collaboration.

The TRUSTS project addressed these challenges by building a secure, GDPR-compliant data sharing platform based on two major national initiatives: Data Market Austria and Industrial Data Space. Acting both independently and as a federator, TRUSTS integrated platforms across jurisdictions, supported privacy-aware analytics (e.g. multi-party computation), and ensured legal and ethical compliance across the data chain. It involved six companies across three use cases and included universities, SMEs, and national multipliers to ensure long-term sustainability. TRUSTS fostered trust through transparency, stakeholder engagement, and a clear business model, helping to establish a unified European Data Market grounded in secure and trustworthy data exchanges.

Objectives

1

Analyse the EU and worldwide challenges and trends for data-sharing and define the requirements for the provision of a multi, concurrent and cross-domain, secure and scalable end-to-end (E2E) data marketplace service.

2

Leverage existing data markets technologies and components (Industrial Data Space and the Data Market Austria) and integrate them in the innovative TRUSTS Platform.

3

Expand and enrich the TRUSTS Platform with additional well proven and enterprise ready technologies and methodologies in the field of secure data sharing and federated data processing.

4

Demonstrate the added value of the TRUSTS Platform in 3 business-oriented use cases which showcase the sharing, trading, (re)use of data and services and result in added value generated through innovative applications built on multiple open and proprietary data sources.

5

Develop a robust legal and ethical framework for the TRUSTS Platform to ensure sustainability and compliance of the innovation brought by the project with all relevant regulations and ethics principles.

6

Create a sustainable business model and plan (incl. products & service portfolio, clear SLAs, pricing and billing etc.) for the TRUSTS Platform supported by a wide-reaching Data Innovation Environment, ensuring the governance and business model for the data marketplace adheres to (privacy) regulation, provides smart contracting to assure quality and service levels, and incentivises providers, users and owners of data.

7

Disseminate the results of the projects widely, on national, European and international levels, to increase participation in the Ecosystem, and internationally, drawing international attention to ground-breaking developments in Data sharing platforms.

eBOS Role in the Project

In TRUSTS, eBOS was involved in the planning, implementation and evaluation of the three business-oriented TRUSTS use cases. eBOS played a central role in the Anti-Money Laundering use case, acting both as an open/public data provider and as an aggregator, leveraging its bespoke WiseBOS Suite solution for Risk Intelligence, Scoring and Compliance. eBOS took a leading role in the development and demonstration of the TRUSTS Platform, contributing to the architecture design, technical specifications, platform development and integration. Additionally, eBOS led the testing framework and benchmarking activities, and was responsible for the design, development and integration of new adaptive analytics algorithms and cognitive self-learning models. Finally, eBOS contributed to the dissemination and communication activities.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871481.