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| 1 | +--- |
| 2 | +title: "Seven EU Projects Collaborate Around Shared Mission to Extract Meaningful Insights from Extreme Data" |
| 3 | +date: 2024-06-20 |
| 4 | +layout: update |
| 5 | +tags: |
| 6 | + - press-release |
| 7 | + - construction-kit |
| 8 | + - oneapi |
| 9 | + - codeplay |
| 10 | +--- |
| 11 | + |
| 12 | +As part of the Horizon Europe funding programme, seven pioneering projects have received funding to address the |
| 13 | +challenges posed by extreme data generated by IoT, industrial, business, administration, environmental, scientific and |
| 14 | +societal sources. These projects are pursuing innovative approaches that integrate cutting-edge technologies, including |
| 15 | +Artificial Intelligence (AI), Internet of Things (IoT), High-Performance Computing (HPC) and Edge/Fog/Cloud Computing. |
| 16 | + |
| 17 | +Under the 2022 Horizon Europe call for Digital and Space, topic “World Leading Data and Computing Technologies”, the EU |
| 18 | +recognises the intrinsic value of data for EU’s competitiveness. Projects funded under the |
| 19 | +cluster [HORIZON-CL4-2022-DATA-01-05 – Extreme data mining, aggregation and analytics technologies and solutions](https://cordis.europa.eu/programme/id/HORIZON_HORIZON-CL4-2022-DATA-01-05/en) |
| 20 | +seek to securely extract meaningful insights from raw data, facilitating advanced decision-making strategies. |
| 21 | + |
| 22 | +## Methodology and Novelty |
| 23 | + |
| 24 | +Through unique methodologies and application cases, each of the seven projects contribute to strengthening European |
| 25 | +capacities for agile responses to urgent needs by developing and enabling the uptake of the next generation of computing |
| 26 | +and data technologies and infrastructures. Operating within the framework of European values, the projects emphasise |
| 27 | +human-centred and ethical development of digital and industrial technologies, promoting trustworthy technology that |
| 28 | +empowers end-users. |
| 29 | + |
| 30 | +The projects leverage innovative infrastructures, converging and working seamlessly across the compute continuum. With |
| 31 | +diverse application cases, ranging from crisis management, mobility, to food security, the projects aim to bring their |
| 32 | +innovative work closer to end-users, making it a reality for them. |
| 33 | + |
| 34 | +## The Cluster Objectives |
| 35 | + |
| 36 | +The cluster is dedicated to fostering a vibrant community within the seven projects. By creating a space for exchange, |
| 37 | +knowledge-sharing and network-sharing the cluster aims to create a synergetic ecosystem. This collaborative effort |
| 38 | +maximises the impact of the projects by enhancing communication networks and facilitating exchange, with partners from |
| 39 | +across Europe, showcasing the effectiveness of Horizon Europe and laying the foundation for future collaborations. |
| 40 | + |
| 41 | +## DataNexus in Summary |
| 42 | + |
| 43 | +The seven projects in the DataNexus cluster are: |
| 44 | + |
| 45 | +[Graph-Massivizer:](https://graph-massivizer.eu/) Extreme and Sustainable Graph Processing for Urgent Societal |
| 46 | +Challenges in Europe. |
| 47 | + |
| 48 | +Use Cases: Massive graph representation of extreme data in: |
| 49 | + |
| 50 | +* Data Center Digital Twin for Sustainable Exascale Computing |
| 51 | +* Green AI for Sustainable Automotive Industry |
| 52 | +* Global Foresight for Environment Protection |
| 53 | +* Green and Sustainable Finance |
| 54 | + |
| 55 | +[NEARDATA:](https://neardata.eu/) Extreme Near-Data Processing Platform. |
| 56 | + |
| 57 | +Use Cases: A near-data platform for consumption, mining and processing of data in: |
| 58 | + |
| 59 | +* Genomics |
| 60 | +* Metabolics |
| 61 | +* Surgery |
| 62 | + |
| 63 | +[EXA4MIND:](https://exa4mind.eu/) EX4MIND platform for extreme data enables advanced data analytics on supercomputers |
| 64 | +and automated data |
| 65 | +management with support for integration by design with European data ecosystems. |
| 66 | + |
| 67 | +Use Cases: |
| 68 | + |
| 69 | +* Systematic improvement of molecular simulations and accuracy |
| 70 | +* Massively automated annotation and evaluation of automotive camera recordings |
| 71 | +* Smart farming/viticulture with sensors and satellite imagery |
| 72 | +* Secure data mining in health data |
| 73 | + |
| 74 | +[EXTRACT:](https://extract-project.eu/) A distributed data-mining software platform for extreme data across the compute |
| 75 | +continuum. |
| 76 | + |
| 77 | +Use Cases: |
| 78 | + |
| 79 | +* Personalized evacuation route system (mobile app) |
| 80 | +* Transient astrophysics for analyzing space weather |
| 81 | + |
| 82 | +[SYCLOPS:](https://www.syclops.org/) Scaling extreme analytics with cross-architecture acceleration based on open |
| 83 | +standards, and advancing AI/data |
| 84 | +mining by democratizing its acceleration through open standards. |
| 85 | + |
| 86 | +[EFRA:](https://efraproject.eu/) Extreme Food Risk Analytics. |
| 87 | + |
| 88 | +Use Cases: |
| 89 | + |
| 90 | +* Risk predictions for poultry pathogens |
| 91 | +* Enhanced predictive capabilities for pest alarms |
| 92 | +* Informing regulatory decisions with food risk intelligence |
| 93 | + |
| 94 | +[EMERALDS:](https://emeralds-horizon.eu/) Extreme-scale Urban Mobility Data Analytics as a Service. The MAaaS toolset |
| 95 | +will stand out by moving analytics |
| 96 | +and sensitive data analytics to edge computing, enhancing response times and safeguarding data privacy. |
| 97 | + |
| 98 | +Use Cases: |
| 99 | + |
| 100 | +* Mobility analytics as a service toolset |
| 101 | +* Risk-assessment, prediction and forecasting during events |
| 102 | +* Multi-modal integrated traffic management |
| 103 | +* Trip characteristics inference and traffic flow data analytics |
| 104 | + |
| 105 | +By focusing on enabling technologies and their applications for Europe, the cluster contributes to advancing European |
| 106 | +technology and making extreme data useful for addressing economic, societal and industrial needs. |
| 107 | + |
| 108 | +## Contacts |
| 109 | + |
| 110 | +* GRAPH-MASSIVIZER: Nuria de Lama (IDC): <[email protected]> |
| 111 | +* NEARDATA: Vanesa Ruana (Universitat Rovira i Virgili) – < [email protected]> |
| 112 | +* EXA4MIND: Arantxa Echarte (AUSTRALO) – <[email protected]> |
| 113 | +* EXTRACT: Janine Gehrig (Barcelona Supercomputing Center) – < [email protected]> |
| 114 | +* SYCLOPS: Max Brunton (Codeplay) – < [email protected]> |
| 115 | +* EFRA: Efthymios Gkouthas(RAINNO) – <[email protected]>; Ourania Ntinou (RAINNO) <[email protected]> |
| 116 | +* EMERALDS: Sara Bozzi (Trust-IT Services) – < [email protected]>; Marialetizia Mari (Trust-IT Services) – |
| 117 | + |
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