Global Open Research Commons IG

Global Open Research Commons IG

• 1.
  Global Open ResearchCommons IG https://www.rd-alliance.org/groups/coordinating-global-open-research-commons-ig Omo Oaiya WACREN Nigeria Sarah Jones DCC Scotland Devika Madalli ISI India Vivien Bonazzi Deloitte USA Andrew Treloar ARDC Australia Corina Pascu EC Belgium Kazu Yamaji NII Japan
• 2.
  Session agenda • Introductorygrounding (15 mins) Sarah / Corina - The remit of the new Interest Group - Defining a typology for Open Science Commons - Report from the CODATA conference session in Beijing • Developing the WG proposal (60 mins) - Andrew / Mark - Proposals for initial pilot cases  input from floor - How to coordinate / synchronise topics - shared workplan / timeline or thematic - Volunteers to contribute to pilots and lead WG • Shaping the OSC agenda & global collaboration (15 mins) Juan www.rd-alliance.org/open-science-commons-interest-group-working-group-0 Please add to the collaborative session notes! http://tiny.cc/GOSC-IG
• 3.
  Research Data AllianceBoFs Several previous sessions before IG: • Towards a Global Open Science Commons, March 2018, Berlin • Delivering a Global Open Science Commons, November 2018, Gaborone • Coordinating Global Open Science Commons initiatives, March 2019, Philadelphia
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  • To examinepotential for further coordination and interoperability • New case studies (Asia/Pacific region and international) • Platforms/clouds: • CSTCloud federation cloud for open science in China • National Data platform datagov.in in India • African Open Science Cloud • Inter-Regional modular solution for federation of inter-regional Open Science clouds (e.g. EU-China, EU-Africa or Africa-China) • Services: • Sharing mesh of storage, data and applications: H2020 CS3mesh4EOSC (starting 01/2020, Coordinator: CERN, AARNet partner) • National/international policies • G7, ISC, International Science Council, NDSAP ( National Data Sharing and Accessibility Policy) and Open Science initiatives in India, progress in Japan https://conference.codata.org/CODATA_2019/sessions/155 CODATA session
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  • Initiatives areemerging globally, including in less economically developed countries – how to enable inter-regional cooperation? • Multilateral and cross disciplinary cooperation is needed • The Beijing Declaration (under review) on core principles to encourage global cooperation especially for public research data • Many pieces in the “puzzle” required to make this vision a reality which include policy and technical spheres but also governance, cultural change Some take-aways
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  GOSC Interest &Working groups Global Open Science Commons IG …WG …. WG … WG https://rd-alliance.org
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  Remit of newInterest Group • Provide a neutral place where people have conversations about Open Science Commons • Reach a shared understanding of what a “Commons” is in the research data space • Proactively look outside the RDA community to connect with parallel initiatives • Own the overall remit of coordinating the delivery of a Global Open Science Commons and monitor progress made within related RDA Working Groups and other initiatives
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  Plan for first12-18 months • Reach consensus on the description/vision of a Commons. • Agree a typology of Open Science Commons to provide a framework for activity • Develop a roadmap for global alignment between Global Open Science Commons. • Create one or more initial Working Groups to conduct focused activity.
• 9.
  What is anOpen Research Commons? “A shared virtual space or platform that provides a marketplace for data and services” Could be country, continent, discipline, sector based e.g. • European Open Science Cloud • Australian Research Data Commons • African Open Science Platform • Data Commons for Food Security • CSIROs Managed Data Ecosystem • …..
• 10.
  Science Commons typologies… EOSCsix layers
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  1. FAIR objectecosystem (FAIR DOs, PIDs/GUPRIs, Types) 2. Community Services/Core Resources A. Semantic resources, metadata schema B. Repositories/data resources, data stewardship services, analytical tools 3. Communities Agreements (data sharing/visiting agreements) Typology of areas for consensus building in global commons initiatives 4. Data Policies 5. Infrastructure (network, compute, storage) 6. Skills and Training 7. Business Models and Sustainability 8. Governance and Rules of Engagement
• 12.
  NIH technical layersplus… Technical AND human dimensions Governance Sustainability Stakeholderengagement Technical layer cake courtesy of Vivien Bonazzi, NIH Flows……. Don’t build silos! Open APIs and open data where possible Avoid vendor lock-in. Infrastructure should be “forkable” to move elsewhere if desired
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  Image Reuben Juarezhttps://unsplash.com/photos/C4sxVxcXEQg
• 14.
  Thanks for listening! Questions? [email protected] Twitter:@sjDCC