A distributed data-mining
software platform for
EXTReme dAta Across the
Compute conTinuum

Delivering a data-driven open-source platform integrating cloud, edge and HPC technologies for trustworthy, accurate, fair and green data mining workflows for high-quality actionable knowledge

Objectives

Enable the development of complex and secure data mining workflows

Develop novel data-driven orchestration mechanisms to efficiently deploy and execute data mining workflows

Deliver the EXTRACT software platform and demonstrate its benefits in two use cases

Fully exploit the performance capabilities of the compute continuum to effectively address extreme data characteristics (high volume, variety, velocity, veracity)  holistically

Foster the adoption of EXTRACT technology by industrial and academic communitie

Use cases

Personalized Evacuation Routing (PER) System

A Personalized Evacuation Routing (PER) System will serve to guide citizens in an urban environment (the city of Venice) through a safe route in real time.

The EXTRACT platform will be used to develop, deploy and execute a data-mining workflow to generate personalized evacuation routes for each citizen, displayed in a mobile phone app, by processing and analysing extreme data composed of Copernicus and Galileo satellite data, IoT sensors installed across the city, 5G mobile signal, and a semantic data lake fusing all this information.

Transient Astrophysics with a Square Kilometer Array Pathfinder  (TASKA)

The Transient Astrophysics with a Square Kilometer Array Pathfinder (TASKA) case will use EXTRACT technology to develop data mining workflows that effectively reduce the huge amount of raw data produced by NenuFAR radio-telescopes by a factor of 100. This will allow the populating of high-quality datasets that will be openly accessible to the astronomy community (through the EOSC portal) to be leveraged for multiple research activities.

DataNexus JOINS EBDVF ´25

DataNexus JOINS EBDVF ´25

This session brings together three years of collective experience from the DataNexus cluster working on extreme data challenges. Four flagship...