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Common European Data Spaces and Robust AI for Transparent Public Governance

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The world is currently confronting unprecedented challenges, encompassing a global pandemic, ongoing conflicts, and environmental and energy crises. In response to these crises, there has been a significant surge in emergency public spending, accompanied by a relaxation of due diligence checks and oversight.
Consequently, this has given rise to patterns of corruption and fraudulent activities, exerting profound and detrimental impacts on the European economy, society, environment, and politics.

CEDAR sees these challenges as catalysts for research, innovation, and collaboration.

GOAL 1 - IDENTIFY

GOAL 1 - IDENTIFY

Collect, generate, harmonise, synchronise, protect, and share new large-scale, high-quality, high-value datasets.

GOAL 2 - BUILD

GOAL 2 - BUILD

Improve methods and tools for effective data management and machine learning (ML) operations (DataOps, MLOps).

GOAL 3 - DEVELOP

GOAL 3 - DEVELOP

New data analytics and machine learning methods for robust, data-efficient, human-centric, and well-informed decision making.

GOAL 4 - VALIDATE

GOAL 4 - VALIDATE

Promote CEDAR results with relevant public and private stakeholders and generate direct and tangible impacts on the European economy, society, and environment.

Articles

A new post-event Report with the highlights of the panel "Interoperability of Data Spaces for seamless value creation networks" which took place during last EBDVF 2024.
The European Commission has published the first draft of the General-Purpose Artificial Intelligence (AI) Code of Practice.
Join us on December the 4th for a discussion on how to conduct transparent and secure business operations with Ukraine and beyond.
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