TANGO

31/08/2025

    TANGO will establish a stronger cross-sector data sharing, in a citizen-centric, secure and trustworthy manner, by developing innovative solutions while addressing environmental degradation and climate change challenges.

    The overall outcome is a novel platform exhibiting the following capabilities: user-friendly, secure, trustworthy, compliant, fair, transparent, accountable and environmentally sustainable data management, having at its core technology components for distributed, privacy preserving and environmentally sustainable data collection, processing, analysis, sharing and storage. This platform will promote trustworthy and digitally enabled interactions across society, for people as well as for businesses. TANGO will leverage the power of emerging digital technologies to strengthen the privacy for citizens and private/public organisations, reduce costs and improve productivity. It will unlock the innovation potential of digital technologies for decentralised, privacy-preserving applications, while making accessible and demonstrating this potential within the GAIA-X and EOSC ecosystem. With 37 key partners from 13 countries, TANGO, is uniquely positioned to provide a high impact solution within the transport, e-commerce, finance, public administration, tourism and industrial domains supporting numerous beneficiaries across Europe.


    Through the provision of TANGO technologies, a trustworthy environment will be designed acting as a gatekeeper to information and data flows. Citizens and public/private organisations will be empowered to act and interact providing data both online and offline.

    TANGO will focus its activities on 3 main pillars: 

    • The deployment of trustworthy, accountable and privacy-preserving data-sharing technologies and platforms.
    • The creation of data governance models and frameworks.
    • The improvement of data availability, quality and interoperability – both in domain-specific settings and across sectors.

     

    This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement number 101070052.

     

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