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AI Factory for Copernicus Data at Scale

Project description

Unlocking Copernicus data to accelerate EU Earth observation market

Despite Copernicus data's success, the European Earth observation market remains only a third the size of North America’s. However, projections suggest it will double in the next decade, driven by sectors like insurance and precision agriculture. Yet, three primary challenges hinder its growth: timely data analysis, data identification, and sustainability. The EU-funded DaFab project targets these challenges to Copernicus data utilisation. Firstly, it focuses on timely analysis via AI and federated computing. Secondly, it tackles data volume and accessibility issues with semantic web techniques and metadata catalogues. Lastly, it ensures sustainability of analysis by-products through cloud computing. By addressing these challenges, DaFab aims to unlock Copernicus-derived data’s full potential.

Objective

Despite the success of Copernicus data, the European Earth Observation (EO) data market is only one-third of the size of the North American market. However, the market is expected to double over the next decade. Various sectors, such as insurance, food safety, environmental monitoring, and precision agriculture, are anticipated to capture most of the growth. In this context, DaFab has identified three primary challenges that must be addressed to leverage the full potential of Copernicus' information. Firstly, the timely analysis of EO data is critical for decision-makers to make informed decisions. To address this challenge, DaFab invests in novel hardware techniques dedicated to AI and federated computing techniques, which are capable of handling large high-resolution datasets and can enable real-time applications. Secondly, the massive amounts of Copernicus data make it challenging to identify the most relevant datasets for specific purposes, and the siloed nature of EO data further compounds this problem. To address this challenge, DaFab invests in semantic web techniques and public metadata catalogs to enable searching Copernicus images by features and relationships. Finally, the sustainability of analysis by-products is critical for efficient data management. To address this challenge, DaFab invests in cloud-computing techniques and public metadata catalogs, providing a unified solution for searching both raw Copernicus and by-products by features and relationships. By addressing these challenges, DaFab aims to unlock the full potential of Copernicus data and drive growth in the European EO data market.

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HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-EUSPA-2022-SPACE

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Coordinator

DATADIRECT NETWORKS FRANCE
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 360 000,00
Address
10-12 RUE ANDRAS BECK
92360 Meudon La Foret
France

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Region
Ile-de-France Ile-de-France Yvelines
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 360 000,00

Participants (7)

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