At a Glance
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- At a Glance
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 dataoriented 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 Aibased 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.
Expected Impacts
Improved European leadership in the global data economy
PLIADES delivers a novel data integration framework that builds on existing state of the art architectures, such as IDSA, in order to extend them through a suite of novel tools and standards that aim to solve critical and complex problems on data creation, storage, ownership and discovery as well as their disposal in diverse data spaces. The framework will have advanced capabilities such as proposing suitable dataspaces to the users based on their needs while being able to understand request contexts, saving them valuable resources of time and money. Through its training and support approach, PLIADES project will help individuals and organizations to adopt the new standards and architectures, easing their transition to the new data landscape while its capability to efficiently combine data from several sources in a secure and trustworthy manner, dealing with the problems that organizations are currently having with data sharing because of business, technical, and legal limitations, will foster innovation providing new insights that will boost EU economic development. In this way, with easier, more efficient and secure access to data of multiple dataspaces that are suitably matched to each user’s needs while being of high-quality, PLIADES will provide the means towards improved European leadership in the global data economy.
Maximised social and economic benefits from the wider and more effective use of data
PLIADES project targets at increased and efficient data sharing that will lead to the wider and more effective use of data, particularly focusing on boosting the potential of full data cycles management data as a key enabler for technological developments in AI and Robotics-oriented fields. Covering the ML/DL needs for vast amounts of high quality data, enhanced or even new technological solutions and services are expected to appear in the market leading to substantial benefits for the economy as well as the society that will enjoy services and products of advanced quality, ameliorating various aspects of everyday life, spanning from efficient and trustworthy smart and autonomous vehicles to personalized healthcare solutions. Moreover, the more effective use of data by means of data compression, filtering and multi-dimensional human factors compensation will reduce the carbon footprint associated with the management and maintenance of large amounts of data leading to more environment-friendly solutions while data sharing and reuse will facilitate industries to have easy and trustworthy access to valuable data that can leverage their business.
