International Activities of Data Centric Science

Kimmo Koski, CSC
February 24th, 2015
ROIS International Workshop, TokyoAgenda
Short presentation of CSC
Motivation for collaboration in data centricscience
European landscape in Research
Infrastructures
From 7th Frame Program to Horizon2020:
DCS related activities in EU
European data infrastructures: EUDAT
Global initiative: Research Data Alliance
Building trust: need for global collaboration

CSC at a Glance
Founded in 1971 as a technical support
unit for Univac 1108
Connected Finland to the Internet in1988
Reorganized as a company, CSC –Scientific Computing Ltd. in 1993
All shares to the Ministry of Educationand Culture of Finland in 1997
Operates on a non-profit principle
Facilities in Espoo, close to Otaniemi
campus (of 15,000 students and 16,000
technology professionals) and Kajaani
Staff over 260
Volume in 2014 about 35 MEUR
(without investments)

CSC’s Services
Funet Services
Computing Services
Application Services
Data Services for
Science and Culture
Information
Management Services

Universities
Polytechnics
Ministries
Public sector
Research centers
Companies

International (EC) and national projects

euclidCSC: One-stop shopping for e-infrastructure

More informationwww.csc.fi@CSCfiwww.facebook.com/CSCfi
www.youtube.com/channel/UCFv76jNZlBFp6O9umdnyDA
www.linkedin.com/company/csc---itcenter-for-science
www.slideshare.net/CSCfi

Research Infrastructure
the term Research Infrastructure refers tofacilities, resources and related services
that are used by the scientific community
to conduct top-level research in theirrespective fields.

8e-Infrastructure
The term e-Infrastructure refers to a newresearch environment in which all
researchers - whether working in thecontext of their home institutions or innational or multinational scientificinitiatives - have shared access to uniqueor distributed scientific facilities (includingdata, instruments, computing andcommunications), regardless of their typeand location in the world.
9

Exponential growth

Things get more complex…
Zettabytes
Exabytes
Petabytes
Terabytes
Gigabytes
Increasing complexity and variety• Where to store it?
• How to find it?
• How to make the most of it?

10

Research Infrastructures
Research Infrastructure trends:
 Internationalization
 Diversification

European Ris:
 Around 300
 € 100 billion investment
middle age

19th century

20th century

21st century

11

Looking for synergy
The worst case scenario: Every Research
Infrastructure builds an incompatible selfmade ICT system of their own
What can we do to promote collaboration
and re-use of e-infrastructure?

12

If we do not collaborate, we will…
… make a lot of overlapping work by reinventing solutions in multiple places… do things inefficiently… loose money by unnecessary
investments in hardware, software andservices… run out of competent and experienced
data specialists

e-infrastructure priorities

Back in 2013, when planningfor Horizon2020

Data-centric science and engineering
Infrastructure for open access, management of extremely large research datasets,
persistence and trust, as well as community-driven data infrastructures, and global
coordination for research data

Computational infrastructure
Support to setting up of HPC Centres of Excellence, deployment of HPC Tier-0services, support to open computing platforms and services

GÉANT
Continued development and operation of the GÉANT infrastructure, support tointernational links and opening and strengthening innovation activities

VRCs and virtual research environments
Supporting VRE's as an open call (bottom-up)

Policy development and international cooperation
Global reach and connectivity; governance; sustainability; coordination with MS

Data as infrastructure: Europe is Riding the Wave
The High Level Expert Group on Scientific Data
presented Riding the Wave in October 2010
Vision: "data e-infrastructure that supports
seamless access, use, re-use, and trust of data.
In a sense, the physical and technicalinfrastructure becomes invisible and the data
themselves become the infrastructure avaluable asset on which science, technology, theeconomy and society can advance".

Collaborative Data Infrastructure-A framework for the future? -Trust

Data Curation

Data
Generators

Users

User functionalities, data capture& transfer, virtual research
environments

Community Support Services

Data discovery & navigation,
workflow generation, annotation,interpretability

Common Data Services

Persistent storage, identification,authenticity, workflow execution,miningThree priorities towards H2020
We need to build trust between researchersand e-infrastructure providers– Synergy, efficiency, proper workload division

What we do in European level need to linktightly to national and global activities– Most of the funding for e-infrastructure is national– Researchers don’t want to have too many layers

The services need to be user driven– What to do by user communities, how to implementby technology providers– Co-design: user communities as partners in ICTprojects, not only as customers
18

Science is global, as also the need for
e-infrastructure and related services
Research collaborations
are global
E-Infrastructures mustreact to the requirements• Examples from the networks

Sustaining Global Forums– RDA, CODATAWhat will happen in Horizon2020?
The work with Research Infrastructures and einfrastructures will continue– Continuation of successful projects from FP7– New initiatives– Update of ESFRI Research Infrastructure list
http://ec.europa.eu/research/infrastructures/index_en.cfm?pg=esfri
ESFRI = European Strategy Forum for Research Infrastructures

Targets include:– Excellent science– Industrial leadership– Addressing societal challenges– http://ec.europa.eu/programmes/horizon2020/h2020-sections

Some flagship projects in H2020
EUDAT2020 (www.eudat.eu)– European data infrastructure

RDA-Europe (europe.rd-alliance.org)– Research Data Alliance

PRACE (www.prace-ri.eu)– Supercomputing

GEANT (www.geant.net)– Research network

Other, including Research Infrastructures,clusters of Ris and e-infrastructure projects

E-Infrastructures with data
EGI, www.egi.eu– European grid initiative

Helix-Nebula, http://www.helix-nebula.eu/– Cloud services

OpenAIRE, https://www.openaire.eu/– Publications, open access

Number of new initiatives starting with firstH2020 callsPrevious EU projects
2 data infrastructure calls– About 15 disciplinary projects

ESFRI cluster projects– Bringing Research Infrastructures from same area
closed together– BioMedBridges for biomedical– DASISH for humanities– ENVRI for environmental sciences– CRISP for (physics) experiments– Continuation for part of these expected in H2020

ESFRI Research Infrastructures
Newest roadmap update from 2010, projects on-going:
http://ec.europa.eu/research/infrastructures/pdf/esfristrategy_report_and_roadmap.pdf#view=fit&pagemod
e=noneSix areas: social sciences and humanities, biologicaland medical sciences, environmental sciences,materials and analytical facilities, energy, physicalsciences & engineering
38 projects, major investment in each
– Not all funded, planning and prioritization on-going

All 38 projects require data management: how to
enable synergy and collaboration?

Example: EISCAT3D
The next generation European incoherent
scatter radar system
Construction 2014-16, operation 2016-46Construction 60-250 MEUR, Operation 410 MEUR/year
Sweden, Norway, Finland, UK, Germany,Japan, China
https://www.eiscat3d.se/EUDAT2020
Data Services, Tools &Knowledge

A pan-European e-Infrastructure solution for pan-European
RI data Challenges• All Research Infrastructures are facing data challenges– Where to store the growing amount of data?
– How to find it?
– How to make the most of it?

• Many communities are developing own solutions– This is good…
– … but we also need to make sure that the solutions
remain interoperable• EUDAT mission is to fill this gap– Providing a set of services to help RIs managing theirgrowing amount of data
– Providing these services across communities to ensure
minimum level of interoperability– EUDAT also help to bring data and computing together(HPC centers core partners)

27

Data Centers and Communities

28

User Forums + 30 communities

1st User Forum
7-8 March 2012, Barcelona

29

Services & Resources

Covering both access anddeposit, from informal
data sharing to long-termarchiving, and addressing
identification,
discoverability andcomputability of both
long-tail and big data,
EUDAT’s services willaddress the full lifecycleof research data30

User-Driven
EUDAT H2020 (32)

Factor 6
Integrating

Pilots/testing

Start EUDAT (5)Interacting31

Bridging National and European solutions• Making national resources more availableand visible– Making visible valuable national collections through EUDAT– Access to European resources through national catalogues• Enhancing cross-national collaborations– EUDAT provides a European extension to nationalsolutions• Research and infrastructures are stilllargely funded at national levels– Better coordination between funding schemes androadmaps is neededResearch Data Alliance (RDA)
rd-alliance.org

33

RDA

34

The goal of RDA is to accelerate international data-driven innovation anddiscovery by facilitating research data sharing and exchange. This isachieved through the development, adoption, and deployment of
infrastructure, policy, practice, standards, and other deliverables.

 RDA Vision
Researchers and innovators openly share data acrosstechnologies, disciplines, and countries to address the grandchallenges of society.
 RDA Mission
RDA builds the social and technical bridges that enable open
sharing of data.

Ways to participate in RDA
 Joining as a member Participation in working groups, interest groups or BoFgroups
 RDA conferences twice a year March 9-11th 2015 San Diego, US September 2015 Paris, France Number of other events
 https://rd-alliance.org/news-and-events.html

35

The Data Harvest: How sharing researchdata can yield knowledge, jobs and growth

https://europe.rdalliance.org/sites/default/files/report/TheDataHarvestReport_%20Final.pdf

36Building trust and collaboration
Bringing research and ICT closer together– Tools, methodology, data analysis– Optimizing workload, benefits from synergy

New requirements for education system– Producing data scientists with multidisciplinary
approach

Planning National – Regional – Global– Collaboration in all levels

Sharing best practices and exchanging
knowledge

Thank You!
Kimmo.Koski@csc.fi

9.3.2015