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<h3 class="wp-block-heading">Key Highlights</h3>



The event began with a project overview and roundtable of partner introductions. This was followed by a showcase of&nbsp;scientific and technological validation use cases, demonstrating how RI-SCALE will support cutting-edge research and innovation across domains.



<h4 class="wp-block-heading">Scientific Use Cases</h4>



These use cases are designed to demonstrate how RI-SCALE will accelerate scientific discovery through scalable and interoperable digital infrastructures:



<ul class="wp-block-list">
<li>Climate Risk &amp; Agriculture (ENES/CMCC): High-resolution downscaling of climate scenarios for identifying long-term trends affecting agricultural resilience.</li>



<li>Anomaly Detection in Climate Data (ENES/CMCC): Intelligent systems for identifying irregularities in the usage of climate datasets.</li>



<li>Radar Observations &amp; Experiments (EISCAT): Smart scheduling of atmospheric and ionospheric observations to optimise instrument usage.</li>



<li>Space Debris Monitoring (EISCAT): Detection of space debris and orbital anomalies to support satellite safety and sustainability.</li>



<li>Colorectal Cancer Prediction (MUG): Use of explainable AI to enhance early detection of cancer based on clinical data.</li>



<li>Synthetic Data for Pathology (MUG): Generating synthetic biomedical images to train and validate AI models in computational pathology.</li>



<li>Foundational Models for Bioimaging (EBI): Leveraging foundational AI models to analyse complex, heterogeneous biological imaging data.</li>



<li>AI Assistant for Data Discovery (KTH): A generative AI-powered assistant to support users in navigating and exploiting large-scale research data.</li>
</ul>



<h4 class="wp-block-heading">Technological Use Cases</h4>



These use cases focus on the technical enablers needed to deliver RI-SCALE services effectively at scale:



<ul class="wp-block-list">
<li>EuroHPC Scalability (ECMWF): Testing integration with EuroHPC through Destination Earth workflows for climate modelling.</li>



<li>Image Compression (MUG, COM): Exploring efficient image compression techniques to improve storage and transfer of large scientific datasets.</li>



<li>Green Computing (TUW, FRA, MUG): Evaluating sustainable computing methods to reduce the environmental footprint of research infrastructures.</li>



<li>Credit Management System (EGI, GRNET, TUBITAK, TUW): Designing a federated credit and accounting system to enable fair and transparent access across services.</li>
</ul>



<h3 class="wp-block-heading">Technical Planning and Roadmap</h3>



The second day featured an in-depth&nbsp;Competence Centre workshop, where project partners discussed the architectural and technological building blocks of RI-SCALE’s&nbsp;Data Exploitation Platforms (DEP). Topics included:



<ul class="wp-block-list">
<li>Data lifecycle and storage technologies (CERN, CMCC)</li>



<li>AI workflows and model integration (Juelich, KTH)</li>



<li>Access management and interoperability (GRNET, EGI, INFN)</li>



<li>Technology synergies from EUCAIM, Copernicus, DestinE, and more</li>
</ul>



<h3 class="wp-block-heading">Looking Ahead</h3>



The final sessions focused on&nbsp;maximising project impact&nbsp;through communication and collaboration,&nbsp;aligning with related initiatives, and outlining the&nbsp;milestones and deliverables&nbsp;for the first six months.



The kickoff meeting successfully set the direction and momentum for the RI-SCALE project, fostering a shared understanding and strong collaboration framework among all partners.



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RI-SCALE Project Launched with 3-Day Kick-off in Amsterdam

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