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Project Publications

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A catalyst for European cloud services in the era of data spaces, high-performance and edge computing: NOUS

Europe’s position in the current cloud market needs to be improved. This market is currently dominated by non-European players by 75%, shaping the way that Europe is deploying and using cloud services. Although these players are bound to laws and regulations of foreign powers, such as PR China and USA, generating legitimate concerns for the EU, its businesses and citizens. EU’s digital future resides on having installed secure, high-quality data processing capacity. This can only be offered by cloud services both centrally and at the edge. In this context NOUS’s ambition is completely in line with the European Strategy for data as aims to create the foundations for a European Cloud Service which exploits the HPC network and tackles specific-to-the-EU-economy requirements as well as leverages different data spaces (Mobility, Energy, Green Deal and Manufacturing).
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Enhancing Value Creation Through Interoperable Data Spaces

To support the data space transformation, DS2, CEDAR, CyclOps, NOUS, and PLIADES project, have joined forces and created the Data Space Cluster to unlock the full potential of data. In this document, amongst the results of a joint event, the aforementioned projects offer some valuable recommendations.

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Density-Aware Active Learning for Materials Discovery: A Case Study on Functionalized Nanoporous Materials

Machine learning algorithms often rely on large training datasets to achieve high performance. However, in domains like chemistry and materials science, acquiring such data is an expensive and laborious process, involving highly trained human experts and material costs. Therefore, it is crucial to develop strategies that minimize the size of training sets while preserving predictive accuracy. The objective is to select an optimal subset of data points from a larger pool of possible samples, one that is sufficiently informative to train an effective machine learning model.

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