germany and its open science cloud - plan-e – platform ... · 4/27/2017 · generic research...
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Arndt Bode Member of the Board of Directors, Leibniz Supercomputing Centre of the Bavarian Academy of Sciences
and Humanities and Technical University Munich
Germany and its Open Science Cloud
PLAN-E Meeting, April 27th, 2017, Poznan Supercomputing and Networking Centre, Poznan
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German Wording: „Informationsinfrastrukturen“
2011 „Kommission Zukunft der Informationsinfrastruktur“
Definition of a concept for an Information-Infrastructure in Germany
Submitted to GWK („Gemeinsame Wissenschaftskonferenz“)
2014 „Rat für Informationsinfrastrukturen“ (RfII)
2016 RfII publishes position paper „Leistung aus Vielfalt“
Recommendation for Research Data Management (RDM): structures, processes,
financials for RDM in Germany
Recommendation to establish „Nationale Forschungsdaten Infrastruktur“ (NFDI):
Governing Board to coordinate activities regarding research data. [ To be decided
by GWK in April 2017 ]
5/22/2017 PLAN-E Meeting, Poznan 2
Germany and the Open Science Cloud (1)
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Many activities regarding RDM by the „Laender“ (provinces)
Baden Württemberg: eScience Initiative (coordinated project of BW universities)
Hessen: HeFIS „Hessische Forschungsdaten Infra-Struktur“
Hamburg & Schleswig-Holstein: Cooperation in „Digital Science“ (April 6, 2017)
Activities by Research Organizations
Helmholtz: Helmholtz-Data-Federation
Fraunhofer: Development of a private cloud FORDATIS
Leibniz: FDM project: Leibniz Data
Cooperation NL-D: position paper „FAIR use of Research Data“
Participation in EOSC since 2015 „High level export group“: Klaus Tochtermann
Governing Board (to be established summer 2017) would correspond to NFDI
Preparation of the G7-Member States for a Recommendation: Action plan to be signed in September 2017
5/22/2017 PLAN-E Meeting, Poznan 3
Germany and the Open Science Cloud (2)
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Open Science Cloud defined as a seamless scalable and federated infrastructure for HPC,
HTC, data analytics, RDM is „work in progress“ : GCS, GA, …….
GeRDI: a federated approach, mainly for RDM
5/22/2017 PLAN-E Meeting, Poznan 4
Germany and the Open Science Cloud (3)
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Open Science needs Federated Infrastructure
Structure. Keypoints of the Talk
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The Point of View of an Infrastructure Provider (LRZ)
The Open Data Challenge
Towards a Generic Research Data Infrastructure (GeRDI)
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Vision
Create an infrastructure to support open and interdisciplinary research.
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Datafindable
accessible
interoperable
Reusable
Open
Trusted
Environment
Image: www.digitalbevaring.dk
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The Leibniz Supercomputing Centre
What is the LRZ? IT-Service Provider / Research Institution / HPC Centre
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IT Services (amongst others)
• Mail & Web
• Internet Service Provider (MWN)
• Storage Cloud
• Compute Cloud
• gitlab
• Licences
• Backup and Archiving Centre
• HPC (SuperMUC)
incl. application support
Computer Centre for all Munich Universities
• 160 employees and 43 extra staff
• More than 100,000 students
• 30,000 professors, scientific and other staff
Services also for big customers, eg. BSB/BVB (Bavarian
libraries) or Hochschulstart
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Munich Scientific Network (MWN)
Science needs Connectivity. Internet and Network for Scientists
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Image: www.digitalbevaring.dk
Operation figures
• 16 Routers
• 1,500 Switches
• 2,900 Access points
• 76 leased dark fibres
• 40+ private dark fibres
• > 150,000 systems connected
• 50 Locations with more than 540 groups of buildings
Connecting Munich‘s universities to the internet
• with 10 Gbit/s
• 1,200/800 Terabyte per month incoming/outgoing
• 22 Petabyte per month via backbone
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Code Hosting @ LRZ
Science needs Collaboration. Enable to share and improve scientific applications
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The LRZ hosts a gitlab instance as an open platform for code sharing
• 4600+ users
• 6500+ code projects
• 420+ GB of source code
• 1800+ Merge Requests
• 1000+ Forks
• supports invitation of scientists outside of the LRZ Identity Management (gitinvited.lrz.de)
gitlab.lrz.de was introduced early 2016 and is now widely used in both research and teaching.
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The LRZ: a Supercomputing Centre
Science needs Computing. Creating and Analyzing Big Data
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SuperMUC• Phase 1:
• 3 PF, > 300 TB Memory, > 156,000 cores
• Phase 2:
• 3 PF, 200 TB Memory, > 86,000 cores
Linux Clusters• Heterogenous, Several flavours
• Continuously expanded
• 327 TF, 33 TB, 16.180 cores
• Housing for LCG and others
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Backup and Archiving Systems at LRZ
Science needs a Digital Memory. Long Term Archival and Backup Solutions
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Occupancy
• 48 Petabytes data
• 21 billions files
• 117 Terabytes data incoming per day
• 9,654 registered systems
Configuration
• 5 tape libraries
• 154 tape drives
• 46,000 tape cartridges
• approx. 3 Petabytes disk cache
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Open Data Challenge 1
Diversity. Several research data repositories across Germany · Europe · World.
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Open Data Challenge 2
Openness and Interdisciplinarity. How can data be made FAIR?
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Data should be
• Findable
• Accessible
• Inter-operable
• Reproducible
Interdisciplinary data exchange adds even more complexity
(e.g. what metadata standards should be used?)
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Open Data Challenge 3
Sceptical scientists. Why should I make My Data open?
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Image: Brian Hole, ubiquitiy Press. http://www.slideshare.net/brianhole/ubiquity-press-eifl130830
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How can these challenges be met?
The GeRDI-Approach. Open Science needs Federated Infrastructures
• A single service provider cannot hope to succeed
Federation of IT-service providers
• FAIRly shared data need standards
Interdisciplinarity and Openness reconciled in one infrastructure
• The right incentives for sharing data must be derived considering the whole data life cycle
both from a specific and a global perspective
Community Management to foster open science
(Listen to communities and make them talk to each other)
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Project Consortium
5 Partners · CAU · DFN · LRZ · ZBW · ZIH
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• Leibniz Supercomputing Center of the Bavarian Academy of Sciences and Humanities
• Verein zur Förderung eines Deutschen Forschungsnetzes e. V.
• Software Engineering Group, Christian-Albrechts-University of Kiel
• Centre for Information Services and High Performance Computing,
Technische Universität Dresden
• German National Library for Economics – Leibniz Information Centre for Economics
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Support the Data life cycle
What search abilities are needed by the communities?
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Process
Analyse
Store
Find
SEARCH ENGINE
Index System
Node 1 Node 2
Public Search Mask
Chair of Hydrology and
River Basin Management
Environmental, Resource and
Ecological Economics
Image: www.digitalbevaring.dk
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Support the Data life cycle
What kind of (re)assembling procedures are needed?
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SEARCH ENGINE
Index System
Node 1 Node 2
Public Search Mask
Process
Analyse
Store
Find
INTERIMSS
TORAGE
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Chair of Hydrology and
River Basin Management
Environmental, Resource and
Ecological Economics
Image: www.digitalbevaring.dk
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Support the Data life cycle
How to interface (High Performance) Computing services?
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SEARCH ENGINE
Index System
Node 1 Node 2
Public Search Mask
INTERIMSS
TORAGE
Process
Analyse
Store
Find
HPC
Chair of Hydrology and
River Basin Management
Environmental, Resource and
Ecological Economics
Image
: w
ww
.dig
italb
evari
ng.d
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Support the Data life cycle
Where to store derived data?
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SEARCH ENGINE
Index System
Node 1 Node 2
Public Search Mask
INTERIMSS
TORAGE
Process
Analyse
Store
Find
HPC
Chair of Hydrology and
River Basin Management
Environmental, Resource and
Ecological Economics
Image
: w
ww
.dig
italb
evari
ng.d
k
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Involved Research Communities
We focus on their data and workflows to identify requirements.
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• Environmental, Resource and Ecological Economics (EREE), CAU Kiel
• Paleoceanography, Ocean Circulation and Climate Dynamics,
GEOMAR Helmholtz Centre for Ocean Research Kiel
• German Socio-Economic Panel (SOEP),
German Institute for Economic Research (DIW)
• Hydrology and River Basin Management: ZEUS (Bavarian Flashflood Map)
• …
Chair of Hydrology and
River Basin ManagementEnvironmental, Resource and
Ecological Economics
Image: www.digitalbevaring.dk
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Example Community: AlpEnDAC
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Title:
Virtuelles Alpen
Observatorium II: Alpine
Environmental Data Analysis
Centre (AlpEnDAC)
Partner:
• Prof. Michael Bittner
• Uni Augsburg / DLR
• UFS
• bifa
Duration:
2014 – 2017
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Outlook
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GeRDI ProjectConcept & Evaluation of a virtual
RD Infrastructure
BMBF/DFG
Setup, Operation, Organization of a
national RD-Infrastructure
Phase I
2016 – 2018
Storage Management, Services, Pilots, Operation Model
Expert discussionsaboutRD-Management
Phase II2019 – 2021
Transfer of Phase I: Put GeRDI intoOperation, Roll-Out, New Communities
Tendering of a national RDI, Roll-Out, SustainableOrganization
Phase IIIstarting 2021
Self-sustained andself-organized
• Operation
• Maintenance
• Development
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Generic Research Data Infrastructure · www.gerdi-project.eu
Questions or Comments?
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Importance for Research Data
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Rat für Informationsinfrastrukturen (RFII)Data management requires information infrastructures to support the digital transition in science.
There are many aspects: e.g. management of increasing digital research data, development of tools
and services
High Level Expert Group „European Open Science Cloud“
There is increasing agreement among Member States and […] e-infrastructure stakeholders that
an integrated approach to research data infrastructures is needed, going beyond layers
(computing, data storage, use) and national and disciplinary silos.
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European Open Science Cloud
Vision. Bringing together current and future data infrastructures.
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What does bringing together
mean?
GeRDI
A model for a future (German)
Research Data Infrastructure
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Generic Research Data Infrastructure
Link existing and future research data repositories with each other.
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Image: www.digitalbevaring.dk
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Across Disciplines
FAIR Data. Findable · Accessible · Interoperable · Re-usable
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Research Dataapplication of standards and
development of new
technologies to link existing
and future research data
centers
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Reference Implementation
Longterm Accessible · Sustainable · Interoperable Infrastructure
Connection of
• Existing Systems
• Software Components
• Standards
• Resources
• Technical Infrastructure
• Policies
• Protocols …
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Infrastructure for interdisciplinary research
Support the professional management of research data.
Enable all scientists in Germany
•Search
•Process
•Analyze
•Store
•Share
•Manage
•Re-use
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Research Data
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Project Idea
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(6) Communities
(5) Disciplinary Services
(4) Middleware Components
(3) Interfaces
(2) Generic Services
(1) Storage
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Challenges
A long-living expandable infrastructure.
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• architectural decisions
• identification and evaluation of existing software
systems for re-use in GeRDI
• community management and domain-specific
requirements
• heterogeneous research data and corresponding metadata
• sustainability and operation model
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Work Packages
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Project Environment
Our aim is to setup a pilot center connecting different repositories.
Arndt Bode, Leibniz Supercomputing Centre Berlin, March 21st 2017 34
Research CommunitiesInfrastructures Connections
Chair of Hydrology and
River Basin Management
Environmental,
Resource and
Ecological Economics
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Broader Project Environment
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Connect repositories
Allow interdisciplinary research
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Vision
Create an infrastructure to support open and interdisciplinary research.
37
Datafindable
accessible
interoperable
Reusable
Open
Trusted
Environment
Image: www.digitalbevaring.dk
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Situation in Germany
Open science needs a federated research data infrastructure.
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Communication networks High performance
computing capacities
Integrated national infrastructure
for research data