EXA4MIND | EXtreme Analytics for MINing Data spaces

Original description

EXA4MIND will build an Extreme Data platform that brings together large scale data storage systems and powerful computing infrastructures by implementing novel automated data management and effective data staging. This will enable integration with extreme data sources and support complex and advanced data analysis pipelines for knowledge extraction. Involving three large universities and a research centre, small and medium-sized enterprises (SMEs), and the industrial sector, EXA4MIND uses interdisciplinary top-level expertise to create a modular Extreme Data Database (EDD) analytics environment. Driven by four representative Extreme Data Application Cases from the fields of molecular dynamics, autonomous driving, smart agri-/viticulture and health/social Big Data, EXA4MIND will support data ingestion and versatile preprocessing, develop an “Advanced Query and Indexing System” with convenient interfaces, and leverage high-performance storage and computing infrastructure. We will make Big Data from heterogeneous storage systems and database management systems available in a uniform way for processing on European pre-Exascale Supercomputers, cloud and AI-processing systems. Further to providing automatised staging, caching or direct access to these systems, the results and relevant data from our project will be made available to the European FAIR Data Ecosystem (including European Data Spaces, EUDAT, and the EOSC). Therefore, standardised modules and automated procedures will be implemented in our EDD. The project will constitute a leap forward towards common European Big and Extreme Data techniques in science, industry, and SMEs. Offering advanced data workflow orchestration, the EDD will be validated, proven, and sustained in collaboration with application partners, generating internationally recognised results. EXA4MIND will thus lay the technological foundations for future European data analytics and computation taking into account the whole Digital Continuum.

Status

SIGNED

Url

https://cordis.europa.eu/project/id/101092944

Call topic

HORIZON-CL4-2022-DATA-01-05

Update Date

09-02-2023