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The DYDAS project involves the creation of a platform capable of handling large volumes of dynamic data, enabling the public sector and industry to benefit from large-scale data analysis.

Information today is based on the ability to collect and process vast amounts of data, millions of times more than in the last 10 years. This revolution is taking place in terms of quantity and variety. It is happening thanks to the rapid development of IoT devices, sensors, intelligent automation systems, and all-new M2M data communications. In this context, the ability to handle large amounts of data is related to the need for adequate infrastructure HPC (High-Performance Computing) and related implementation techniques. It is in this context that the DYDAS project was born, and funded by the CEF TELECOM 2018. In line with the objective of the CEF 2018 work program and the CEF-T-5 call, the project will contribute to the European data infrastructure by improving the sharing and re-use of public and private data. By enabling the use of dynamic data sets such as Earth observation satellite and vehicle data, promoting HPC-based R&D through an integrated research laboratory and scientific knowledge and collaboration system, offering easy-to-use HPC-based services and tools, through specialized interfaces, and designing to provide different user experiences to a wide range of users.

In addition, DYDAS promotes the sharing and re-use of public and private data in a secure environment and through innovative monetization mechanisms.

This collaborative platform will act as an e-marketplace for data access, but as added value, it will be equipped with HPC-enabled services based on Big Data technologies, machine learning, AI, and advanced services.

The project will test the data analysis capabilities of the platform through the integration and operation of three use cases (maritime, energy and mobility).

A key and differentiating element of the project will be the implementation of a Geospatial Data architecture. Architecture that, through the adoption of a geospatial data model and interoperability rules, allow seamless integration and processing capabilities of large data sets for innovative use modes.

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DYDAS Project CKAN Catalog statistiche