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AI-Enabled Data Lifecycles Optimization and Data Spaces Integration for Increased Efficiency and Interoperability

Project description

Building smarter, greener data ecosystems

Robotics and AI depend on high-quality data, but today’s data spaces are often fragmented, inefficient, or difficult to link. In this context, the EU-funded PLIADES project aims to advance the data-space architectures to enable smoother data use across sectors. Specifically, it will develop AI-driven tools that integrate every stage of the data lifecycle. This includes methods for compressing and filtering data, improved protocols that safeguard privacy and sovereignty, and brokers and connectors that use richer metadata to support seamless exchange. PLIADES will also introduce data-discovery services to connect separate data spaces. Its technologies will be tested in six use cases (mobility, healthcare, industry, energy, and the green transition), showing how smarter data ecosystems can support safer transport, better human–robot interaction, and lower-carbon services across Europe.

Objective

PLIADES advances the SoA dataspaces reference architectures, towards a step change on the use of data as key enabler of technological advances in AI and Robotics. To this end, PLIADES researches into novel, AI-enabled tools to advance full data life cycles integration, both within and between data spaces. Sustainable data creation methods through data compression, filtering and normalization will be developed, to allow efficient and greener storage in a data-oriented future. Data privacy and sovereignty will be further ensured, through standards and decentralized protocols to protect data-producing organizations and citizens. Alongside, data sharing will be revolutionized through novel AI-based brokers and connectors using extended metadata, shaped through the project’s best practices and domain expert’s knowledge. On top of these, active data discovery services through cross domain AI connectors will allow creating linked data spaces, enabling interoperability between previously disconnected entities, while data quality assessment services will facilitate real time data evaluation. Extended synergies with EU initiatives will be established in order to contribute models, strategies and technologies for a Common European Data Space. Our outcomes will be evaluated in six use cases focusing on direct advancements in key AI and Robotics technologies for everyday use, oriented around multiple data spaces; mobility, healthcare, industrial, energy and green deal. Our use cases provide a challenging validation suite involving vast heterogeneous data creation, management and sharing while addressing full data lifecycles in multiple major domains. Through the developed ecosystem, CCAM and ADAS/AD car technologies will be enhanced, HRI for robot operators and healthcare patients will be reshaped, while further advanced, integrated data spaces will be deployed in the healthcare, manufacturing and green deal sectors aiming to reduce carbon footprints and shape a greener future.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

(opens in new window) HORIZON-CL4-2023-DATA-01

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Coordinator

ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS
Net EU contribution
€ 1 286 250,00
Address
CHARILAOU THERMI ROAD 6 KM
570 01 THERMI THESSALONIKI
Greece
Region
Βόρεια Ελλάδα Κεντρική Μακεδονία Θεσσαλονίκη
Activity type
Research Organisations
Links
Total cost
€ 1 475 000,00

Participants (26)

Partners (2)