Research projects Archive - Page 2 of 2

Filtering by: Advanced Digital Innovation Center - ADIC Center

SCALA-MEDI – Improving sustainability and quality of Sheep and Chicken production by leveraging the Adaptation potential of LocAl breeds in the MEDIterranean area

The SCALA-MEDI project will optimise the sustainable use and conservation of local genetic resources from the Mediterranean region, focusing on adaptation to climatic conditions and consumer preferences. The expertise and data from previous EU projects will be extended to the genetic and epigenetic characterisation of local resources and their adaptation to different production environments in three North African countries, Tunisia, Algeria and Morocco. Tools and strategies will be developed to improve local breeds for sustainable production. Application of these tools will be demonstrated to farmers in diverse Mediterranean production systems.

SDGs-EYES – Sustainable Development Goals – Enhanced monitoring through the family of copErnicus Services

The UN 2030 Agenda for Sustainable Development is a data driven agenda, and the use of Earth Observation (EO) can make the SDG indicators’ monitoring and reporting technically and financially viable, and comparable across countries. SDGs-EYES aims to boost the European capacity for monitoring the SDGs based on Copernicus, building a portfolio of decision-making tools to monitor those SDG indicators related to the environment from an inter-sectoral perspective, aligning with the EU Green Deal priorities and challenges. SDGs-EYES will establish an integrated scientific, technological and user engagement framework overcoming the knowledge and technical barriers that prevent the exploitation, combination and cross-feeding of data and tools from the Copernicus’s six core Services, its space-based and in-situ components, and other platforms and portals. SDGs-EYES considers three interconnected SDGs, on climate (SDG13), ocean (SDG14) and land (SDG15), to demonstrate through four Pilots the Copernicus potential for monitoring six indicators making part of the EU and national assessments: GHG emissions, temperature deviation, ocean acidification, marine eutrophication, forest cover change and soil erosion. Although focusing on the biosphere, these indicators are linked to other SDGs on socio-economic and (geo)political factors (e.g., human health, resources security, poverty, conflicts, displacements). Thus, an additional cross-goals indicator and Pilot will focus on vulnerable communities under cumulative climate extreme hazards. SDGs-EYES seeks to combine the science-informed (top-down) approach with a stakeholder-driven (bottom-up) approach to transfer scientific outcomes into easy-to-understand and easy-to-use actionable information in the context of SDG indicators’ assessment. Decision-making tools delivered by Pilots will be co-designed with users,

SILVANUS – Integrated Technological and Information Platform for wildfire Management

SILVANUS envisages to deliver an environmentally sustainable and climate resilient forest management platform through innovative capabilities to prevent and combat against the ignition and spread of forest fires. The platform will cater to the demands of efficient resource utilisation and provide protection against threats of wildfires encountered globally. The project will establish synergies between (i) environmental; (ii) technology and (iii) social science experts for enhancing the ability of regional and national authorities to monitor forest resources, evaluate biodiversity, generate more accurate fire risk indicators and promote safety regulations among citizens through awareness campaigns. The novelty of SILVANUS lies in the development and integration of advanced semantic technologies to systematically formalise the knowledge of forest administration and resource utilisation. Additionally, the platform will integrate a big-data processing framework capable of analysing heterogeneous data sources including earth observation resources, climate models and weather data, continuous on-board computation of multi-spectral video streams. Also, the project integrates a series of sensor and actuator technologies using innovative wireless communication infrastructure through the coordination of aerial vehicles and ground robots. The technological platform will be complemented with the integration of resilience models, and the results of environmental and ecological studies carried out for the assessment of fire risk indicators based on continuous surveys of forest regions. The surveys are designed to take into consideration the expertise and experience of frontline fire fighter organisations who collectively provide support for 47,504×104 sq. meters of forest area within Europe and across international communities. The project innovation will be validated

SIM: Sistema Avanzato ed Integrato di Monitoraggio e Previsione

The project, part of Italy’s National Recovery and Resilience Plan (PNRR), aims to build an advanced and integrated monitoring and forecasting system to enhance predictive capabilities regarding the effects of climate change and protect the Italian territory and water resources from natural and anthropogenic risks. The SIM (Sistema Avanzato ed Integrato di Monitoraggio e Previsione) is a long-term surveillance system designed to enable the implementation of preventive measures, such as scheduled maintenance of the territory and infrastructures, marine and coastal pollution monitoring and optimized resource and emergency management. By integrating real-time data collection and predictive modeling, the system enhances the ability to detect environmental threats in advance, mitigate pollution risks in marine, coastal and land areas and support sustainable management strategies for land and water resources. The project involves six vertical applications, including Marine and Coastal Pollution Monitoring (Vertical 3), which focuses on surveillance of marine and coastal water quality to prevent and mitigate environmental pollution. Each Vertical is split in different Case Uses (CU) or applications. CMCC is involved in CU 3.2, 3.3 and 3.5 of Vertical 3.

Skills4EOSC | Skills for the European Open Science Commons: Creating a Training Ecosystem for Open and FAIR Science

Skills4EOSC brings together leading experiences of national, regional, institutional, and thematic Open Science (OS) and Data Competence Centres from 18 European countries with the goal of unifying the current training landscape into a common and trusted pan-European ecosystem, in order to accelerate the upskilling of European researchers and data professionals in the field of FAIR and Open Data, intensive-data science and Scientific Data Management. Competence Centres (CC) are seen as centres of gravity of OS and EOSC activities in their countries. These entities can either be established national initiatives (as is the case of ICDI in Italy) or initiatives under establishment (e.g., Austria, Greece, and the Nordic countries) or organizations which have the leading or mandated contribution to the OS activities nationally. CCs pool the expertise available within research institutions, universities, and thematic and cross-discipline research infrastructures. They offer training and support, empowerment, lifelong learning, professionalization, and resources to a variety of stakeholders, including not only researchers and data stewards, but also funders, decision makers, civil servants, and industry. Thanks to their position at the heart of the above-described multi-stakeholder landscape, the CCs represented by the Skills4EOSC partners play a pivotal role in national plans for Open Science and in the interaction with scientific communities. They also have close access to policy makers and the related funding streams. The Skills4EOSC project will leverage this reference role to establish a pan-European network of CCs on OS and data, coordinating the work done at the national level to upskill professionals in this

Space It Up!

SPACE IT UP is a program aiming at enhancing the space technology of Italy to be used for space exploration and exploitation for the benefit of planet Earth and the entire humankind. An extended project partnership will foster synergies between academy, industry, and research centres to have a strong impact on the Italian space sector and to pursuit the following main objectives: -Promote innovative and extend fundamental knowledge; -Fostering a sustainable future; -Ensure long-term human permanence in extraterrestrial space; -Strengthening the “Ecosystem” space in Italy.

WeatherGenerator

The project will build the WeatherGenerator – the world’s best generative Foundation Model of the Earth system – that will serve as a new Digital Twin for Destination Earth. The WeatherGenerator will be based on representation learning and create a general and versatile tool that models the dynamics of the Earth system based on a large variety of Earth system data. The WeatherGenerator will be task-independent and will improve results for a wide range of machine learning applications when compared to task specific machine learning tools. It will also be more resilient for climate applications when the underlying data distributions are changing, and it will lead to a significant reduction in computational costs and faster turnaround times. To achieve this, the project will: (1) Collect and use the most important datasets of Earth system science including data from Digital Twins of Destination Earth, selected observations, analysis and reanalysis datasets, and output of conventional Earth system models. (2) Build the WeatherGenerator as a novel representation learning- based machine learning tool that exploits the full potential of Europe’s largest supercomputers. (3) Engage with the wider community via services and apply the WeatherGenerator for 22 selected applications that can be integrated into the Destination Earth framework. The applications include global and local predictions, local downscaling, data assimilation, model post-processing, and impact applications in the domains of renewable energy, water, health and food. The project consortium that will build the WeatherGenerator consists of experts in machine learning, supercomputing and Earth system sciences, and includes