Data management experiences in the European projects context:

which lessons for us? which lessons for us?

Claudio Cacciari, c.cacciari@cineca.it (Cineca)

FAIR data management

RDA National Event in Italy

Florence, Italy, 14-15 November 2016

This work is licensed under the Creative Commons Attribution 4.0 International License.

Cineca consortium

• Cineca is a not for profit Consortium of Universities. Founded in 1969, today is made up of 70 Universities, six national Reseach Institutions, and the Italian Ministry of Education, Universities and Research (MIUR).

• It is the most powerful supercomputing center in Italy • It is the most powerful supercomputing center in Italy devoted to scientific and industrial research, and one of the most important worldwide. Cineca supports the international community of scientific research with HPC and Big Data analysis, it develops information systems for universities administation offices, for the MIUR, and for companies, health care, and public administration.

http://www.cineca.it

Cineca’s users

http://www.hpc.cineca.it/content/statistics-cineca-hardware-utilization-september-2016

Cineca’s storage resourcesMay 2015

Online storage will reach 20 Pbytes in 2017

Cineca’s scenario

European projects

Projects

FAIR principles

Italian projects

Services & resourcesCloud

HPC

Big Data analytics

Long termarchiving

Tapelibrary

High performance data transfer

Cloud

HPCplain fs

Long term

archive

Lowering the barrier

• In many cases the tools that support FAIR principles are too complex for the scientificresearchers

• The Cloud infrastructure allows to lower the • The Cloud infrastructure allows to lower the barrier deploying more user-friendly toolsclose to the data and sharing the effort oftheir implementation/maintaining.

EUHIT Portal

EuHIT

EuHIT is a consortium that aims at integrating cutting-edge European facilities for turbulence research across national boundaries.

Data repository

EUDATA truly pan-European Infrastructure

EUDAT offers common data services, supporting multiple research communities as well as individuals, through a geographically distributed, resilient network of 35 European organisations

Our vision is to enable European researchers and practitioners researchers and practitioners from any research discipline to preserve, find, access, and process data in a trusted environment, as part of a Collaborative Data Infrastructure

EUDAT Service Suite

http://www.eudat.eu/services

Conclusions 1

• There is an immense heterogeneity about data and metadata specifications among the differentdisciplines and often within each discipline too.

• If the communities of a scientific domain are not• If the communities of a scientific domain are notable to, at least partially, converge towardscommon standards, the data centers offeringData and Computing services/resources cannotfill the gap on their behalf.

Conclusions 2

• The data centers should offer services and enforce policies which support FAIR principlesin a flexible way.

• Some scientific communities can/want to• Some scientific communities can/want tocomply with some reccomendations, but notothers. The data services should allow the community to improve its compliancyprogressively.

Conclusions 3

• We see interest in making the data accessibleand findable.

• Not much to make them interoperable and re-usable.usable.

Thanks !Thanks !