Research & Development
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Trusted Secure Data Sharing Space

Duration: 01/01/2020 - 31/12/2022

Total funding: EUR 5,977,631.25

Challenge & Objectives

The lack of trusted and secure platforms and privacy-aware analytics methods for secure sharing of personal data and proprietary/commercial/industrial data hampers the creation of a data market and data economy by limiting data sharing mostly to open data. This trend will continue if different technical standards, quality levels, and legal aspects are allowed to diverge uncontrollably.

TRUSTS will ensure trust in the concept of data markets as a whole via its focus on developing a platform based on the experience of two large national projects, while allowing the integration and adoption of future platforms. The TRUSTS platform will act independently and as a platform federator, while investigating the legal and ethical aspects that apply on the entire data verification chain, from data providers to consumers, i.e. it will:
  • Set up a fully operational and GDPR-compliant European Data Marketplace for personal related data and non-personal related data targeting both personal and industrial use by leveraging existing data marketplaces (International Data Space and Data Market Austria) and enriching them with new functionalities and services.
  • Demonstrate and realise the potential of the TRUSTS Platform in 3 use cases targeting the industry sectors of corporate business data, specifically in the financial and telecom operator industries while ensuring it is supported by a viable, compliant and impactful governance, legal and business model.
To create a European Data Market based on secure and trustworthy data exchanges, the TRUSTS consortium brings together technology providers that are already deeply involved in major national data market projects. This integration will be tested in practice by 6 companies, including 2 data providers, addressing 3 different use-cases. The TRUSTS technology and use-cases will be accompanied by business and legal and ethical considerations, which will ensure that the results of the project are sustainable beyond its duration.

In TRUSTS, eBOS will leverage its extensive experience in ICT, data analytics and data visualisation to deliver on the vision of a European data economy based on secure, safe and GDPR-compliant data exchange processes supported by the TRUSTS Platform. eBOS will be mainly involved in the planning, implementation and evaluation of the three business-oriented TRUSTS use cases. eBOS will undertake the role of Work Package leader for the demonstration of the TRUSTS Platform. eBOS will also play a central role in the Anti-Money Laundering (AML) use case, in which it will both act as an open/public data provider and aggregator and leverage its existing bespoke WiseBOS ERP solution for Risk Intelligence, Scoring & Compliance. eBOS will also be involved in:

  • The Requirements elicitation & specifications phase: eBOS will lead the task dedicated to the testing framework and benchmarking;
  • The implementation of the TRUSTS Platform: eBOS will contribute to the elaboration of the Architecture design and technical specifications as well as to the Platform development and its integration;
  • The design, development and integration of new adaptive analytics algorithms and cognitive self-learning models;
  • Dissemination & communication activities.

Consortium

Leibniz Universitaet Hannover / L3S Research Center

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Semantic Web Company GmbH

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Know Center Austria

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Delft University of Technology

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Katholieke Universitet Leuven

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Fraunhofer Gesellschaft für Angewandte Forschung e.V.

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Dell EMC Israel

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Research Studios Austria Forschungsgesellschaft mbH

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Governance One GmbH

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International Data Spaces Association

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Data Intelligence Offensive

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Elliniki Etairia Tilepikoinonion kai Tilematikon Efarmogon AE

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Piraeus Bank

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EBOS TECHNOLOGIES LIMITED

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LSTech Espana LST

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Relational Technology SA- Production Trade and Support of Machinable Products of Software and Informatics

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Foundation for Research and Technology-Hellas

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