Federated decentralized trusted dAta Marketplace for Embedded finance
▶Summary
FAME is a joint effort of world-class experts in data management, data technologies, the data economy, and digital finance to develop, deploy and launch to the global market a unique, trustworthy, energy-efficient, and secure federated data marketplace for Embedded Finance (EmFi). The FAME marketplace will alleviate the proclaimed limitations of centralized cloud marketplaces towards demonstrating the full potential of the data economy. In this direction, the project will enhance a state of the art data marketplace infrastructure (i.e., H2020 i3-Market marketplace) with novel functionalities in three complementary directions namely: •Secure, interoperable, and regulatory compliant data exchange across multiple federated cloud-based data providers in-line with emerging European initiatives like GAIA-X.•Decentralized, programmable, data assets trading and pricing leveraging blockchain tokenization techniques (including support for accruing data assets value in NFTs).•Integration of trusted and Energy Efficient (EE) analytics based on novel technologies such as Quantitative Explainable AI, Situation Aware Explainability (SAX), incremental EE analytics, and edge analytics.FAME will become operational in a federated cloud environment with multiple providers of EmFi data assets, including datasets, AI/ML models, and more. It will become interconnected with more than 12 data marketplaces that are operated by the project partners, as well as with other data infrastructures that will support the implementation of 7 pilots. Through this process, the catalog of the FAME marketplace will be populated with a critical mass of 1000+ data assets. Furthermore, FAME will establish a Learning Center (LC) for tech and non-tech users, as this is a key prerequisite for unlocking the potential of the data economy. FAME will build a vibrant community of EmFi stakeholders around the FAME platform, which will serve as a catalyst for the sustainability of the project’s results.