DaFab - AI Factory for Copernicus Data at Scale
Background & Objectives
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 decisionmakers 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.