The document discusses several newly-funded H2020 initiatives that focus on computing infrastructure for extremely large datasets and open identifiers. These include EUXDAT for extreme data analytics in areas like agriculture, environmental protection and biodiversity. DARE aims to improve big data methods and solutions for projects like EPOS and ENES. DEEP-HybridDataCloud provides intensive processing services for deep learning, analysis of data streams, and specialized hardware. XDC focuses on scalable technologies for distributed storage and data management. FREYA develops a persistent identifier service as a core component for research resource discovery. It also suggests informing EUDAT users and providers about techniques for exascale data resources and computing with large datasets.

1. Engage the newly-funded H2020 initiatives which focus on Computing e-
infrastructure dealing with extremely large datasets as well as open
identifiers
EUXDAT - Extreme Data Analytics, focus on Agri, env. protection,
biodiversity
DARE – Unified agile approach to big data methods development &
improving existing solutions, focus on EPOS&ENES
DEEP-HybridDataCloud - Intensive processing services (deep learning,
post processing and on-line analysis of data streams), specialized
hardware
XDC- eXtreme DataCloud - scalable technologies for federating storage
resources & managing data in highly distributed envs.
FREYA - Connected Open Identifiers for Discovery, Access and Use of
Research Resources – developing PID service as core global
component
Inform EUDAT service providers and users on suggested
techniques/services for handling exascale data resources
Computing with large datasets