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Phidias HPC puts at the core of its activity the development of fully-fledged services to discover, manage and process spatial and environmental data to support researchers involved in domains as earth surface, atmosphere and ocean.

Creating access services
to increase HPC and Data capacities

The Project


PHIDIAS - Prototype of HPC/Data Infrastructure for On-demand Services is an H2020 project co-financed by the Innovation and Networks Executive Agency (INEA) under the European Union's Connecting Europe Facility (CEF). The project addresses the development and concrete realisation of a set of High-Performance Computing (HPC) based interdisciplinary services and tools to exploit large satellite datasets of public European interest provided by:

  • Satellite observation of Earth
  • FAIR access to processed datasets
  • Value-added services through large data storage capability and high-bandwidth network across Europe

 

PHIDIAS offers a catalogue allowing users to discover and access data, but also relevant open source software, public application programming interfaces (APIs) and interactive processing services. The project also implements an end-user web common interactive processing service based on notebook and datacube technologies.

 

PHIDIAS aims at creating access services to increase the HPC and data capacities of the European Data Infrastructure in the context of the Connecting European Framework (CEF) on open data. In particular, in collaboration with all the consortium members, the project will pursue the following objectives:

  • Build a prototype for earth’s scientific data and high-performance computing services.
  • Optimise and industrialise treatment workflows for extensive reusability.
  • Ensure open access to standardised HPC services.
  • Improve FAIRisation processes and open access.
  • Develop new data-processing models coupled with HPC capabilities.
  • Deploy data-processing methods as a service for the scientific community

 

The PHIDIAS Consortium brings together a committed, competent and complementary Consortium of 13 Partners from 5 European countries led by CINES - The French National Computing Centre for Higher Education.

 

KEY IMPACTS

PHIDIAS

Expected outcomes

Create sustainable HPC data-powered services for the earth, atmospheric and marine data towards researchers, industry and public sectors;
Leverage networking infrastructures such as GEANT (GN4-2 Research and Education Networking), RENATER (Réseau National de Télécommunications pour la Technologie, l'Enseignement et la Recherche), FUNET (Finnish University and Research Network) to ensure end-to-end scientific workflows;
Federate infrastructure to infrastructure services, including authentication, access to resources (pre- and post-processing, management and preservation of large volumes of digital information over time);
Define and create a FAIR portal for the scientific community and data providers.

GOALS

PHIDIAS

01

Building a prototype

Develop a catalogue that will allow users to discover and access data, open-source software, public Application Programming Interfaces (APIs) and interactive processing services. This catalogue will implement interoperable services for the discovery, access and processing of the data, and be connected to other major data repositories such as the European Data Portal, the Global Earth Observation System of Systems Portal (GEOSS), the Next Global Earth Observation System of Systems Portal (NextGEOSS), and the European Open Science Cloud (EOSC).

02

Optimising and industrialising

Optimise and industrialise workflows to allow the largest degree of reusability of data as possible, in compliance with the INSPIRE directives and ensuring interoperability with the EUDAT (European Data), EOSC, and IS-ENES (Infrastructure for the European Network for Earth System Modelling) portals and generic services.

03

open access

Implement an end-user web common interactive processing service based on notebook and data cube technologies allowing new users to easily have access to HPC capacities and develop new algorithms.

04

FAIRisation

Improve the FAIRisation of satellite and environmental datasets and preserve FAIR (Findable Accessible Interoperable Reusable) datasets into a Remote Data Access (RDA) certified repository.

05

Data pre-processing

Develop new data pre-processing models coupled with HPC capabilities, by building a new and innovative on-the-fly computing service for smart processing of data, addressing the problem of efficient filtering and on-the-fly first diagnostics on incoming in-situ data.

06

Data post-processing

Deploy data post-processing methods as a service for several end-users, including scientific communities, public authorities, private entities and citizen scientists.

PHIDIAS is looking forward
to hearing from you

The 30-months project NGIatlantic.eu will push the Next Generation Internet a step further by providing cascade funding to EU-based researchers and innovators in carrying out Next Generation Internet related experiments in collaboration with US research teams.




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