Toward a Canadian National Collaborative Data Infrastructure

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Toward a Canadian National Collaborative Data
Infrastructure

• Name
• Contributions by
• Lynn Copeland, Kathleen Shearer, Chuck Humphrey,
  Mike Ridley
• date

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Introduction CNCDI

• Collaborative initiative
• Enable Canada to be a research innovation leader
• Form locus for entrepreneurial innovation
• Seeking CFI funding

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Scope

• Focus on research data
• factual records
• primary sources for research
• validate research findings
• Will
• Be widely available across sectors
• Facilitate cross-fertilization, solutions,
  products, understanding
• Ensure all necessary privacy rules are enforced

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Data infrastructure

• Flexible, reliable
• Secure, privacy, open
• Local, global
• Affordable, high performance
• Ensure protection of privacy

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Why is data stewardship important?Needs
addressed

• Enables replication and verification of research
  results.
• Avoids duplication of research.
• Increases the visibility and impact of research.
• Encourages collaboration
• Accelerates scientific progress.

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Anticipated result

• Research data
• widely available to academy, industry, citizenry
• Facilitate x-fertilization of ideas, domains
• Producing novel solutions
• Support new product development
• Promote greater understanding of complex problems

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Proposed Canadian data stewardship principles

• All research data are recognized to be valuable
  assets for the Canadian and global research
  community. As assets, the proper treatment of
  research data includes full lifecyle management,
  asset assessment, risk management and
  preservation.
• Emerging information technologies are to be
  monitored, evaluated and applied to improve
  methods of producing, providing open access to
  and preserving research data.
• Sustainable solutions to data stewardship are to
  be achieved through institutional commitments and
  collaboration with communities of practice.
• Data stewardship skills and norms, including
  roles and responsibilities, are to be established
  from within research communities of practice
  through policy support, training and curriculum
  development.
• Research Data Strategies Working Group

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Context international

• We are on the verge of a great new leap in
  scientific capability, fuelled by data.
• (HLEG on Scientific Data, EU)
• Scientific data are not homogenous in any
  manner. The disciplines generating data have
  widely varying practices with respect to the
  reporting of experimental, observational and
  calculation conditions and the resulting
  metadata. Archiving practices, in terms of direct
  deposition into community databases, inclusion in
  peer-reviewed papers, etc. differ greatly. Yet
  because almost all data are generated and managed
  electronically, the dream exists of making
  everything available.
• John Rumble, Jr.

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Context Canada

• Sci/Tech strategy
• 10B on RD with associated data
• Granting councils data stewardship policies
  (SSHRC, selective CIHR)
• Previous consultations
• NDAC (SSHRC, NAC)
• NCASRD (NRC, CIHR, NSERC, CFI)
• CDIS (LAC)
• Open data initiatives municipal (Edmonton,
  Ottawa, Vancouver), federal
• A large, complex issue!

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Long overdue
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Libraries unique contributions

• the digital equivalent of libraries
• preserve and provide access to other types of
  content
• strong links with the disciplinary communities
• organized collections required
• In partnership with researchers and technology
  experts

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Libraries contributions

• provide metadata management, access and support
  for data sets
• support and host similar managed content
  (Institutional Repositories, Digital Content)
• play an advocacy role

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Data stewardship examples

• Bioinformatics e-Fungi, ATLAS, GIMS, Columbia,
  BioMART, BioWarehouse
• International Social Science CESSDA, ICPSR,
  GESIS
• Canada
• Data Liberation Initiative
• RDC
• TREC
• ltodesigt
• Islandora
• ABACUS
• IPY ltodesigt, UA data sharing (iRODS) initiative
  (w. CANARIE)
• TAPoR
• VENUS, Neptune
• CANARIE Community Cloud
• Many University data centres
• has significant library leadership/involvement

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Campus library leadership/involvement

• Most CARL libraries provide metadata management,
  access and support for data sets such as
  Statistics Canada data, ICPSR social science
  data, other local sets (police records, etc.)
• Most CARL Libraries play an advocacy role in
  continuing the Data Liberation Initiative,
  creating municipal, provincial and federal Open
  Access policies etc.
• Most CARL libraries support and host similar
  managed content (Institutional Repositories,
  Digital Content)

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Related Initiatives CARL Data Management
Working Group

• Survey of data initiatives across Canada
• Data Management Awareness Toolkit, Research
  Data Unseen Opportunities
• Addressing the Research Data Gap A Review of
  Novel Services for Libraries document
• Research Data Management Seminars
• Plan to encourage Library and Information
  Schools to introduce a research data stewardship
  stream

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Related Initiatives Research Data Strategy
Working Group

• A collaborative effort to address the challenges
  and issues surrounding the access and
  preservation of data arising from Canadian
  research
• Task Group 1 Policies, Funding, and Rewards and
  Recognition
• Task Group 2 Infrastructure and Services
• Produced Principles of Data Stewardship and Gap
  Analysis
• Organizing a Data Summit September 2011 to
  raise awareness of the issue with high level
  policy makers

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CNCDI activities fall 2010-spring 2011

• Touching base
• CFI, SSHRC, CIHR, NSERC
• CISTI (RDSWG), CNC-CODATA, CRKN
• Canarie, CUCCIO, Compute Canada
• Steering Committee Vision
• Data Model WG DM, costs, plan
• Researcher consultation- March 10/11, 2011
• Proposal (ultimately)

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Vision

• The Canadian National Collaborative Data
  Infrastructure
• (CNCDI) project will build a national
  infrastructure to support
• the innovative re-use of data created through
  publicly-funded
• research. The project will build on and enhance
  the existing
• patchwork of data management services and
  infrastructures in
• Canada to create a comprehensive, integrated
  network of data
• repositories capable of supporting Canadian
  research across
• all disciplines far into the future.

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Vision (2)

• The data infrastructure will exist within an
  ecosystem comprised of several layers
• 1. A national collaborative network of digital
  data repositories with trusted status and
  institutional permanence (ingest and access
  services)
• 2. Preservation storage repositories (long term
  management)
• 3. Tools and applications for data re-use and
  analysis
• 4. Skills, training, and support services

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Canadian data landscape
Preservation Function Individual Centric Domain Centric Institutional Centric
Long-term preservation Domain archives Institutional repositories
Short to mid-term preservation Data centres Staging repositories
No preservation responsibilities Website FTP site Research web portals Data libraries
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Questions - Topics

• 1 Needs?

1.     
1.  Should/could there be more collaboration
among IT services, library, library IT and data
centres? 2.   Should/could/is there
project/enterprise/funding support for managing
digital research data? 4.   Will this help a
research data management enterprise solution?
5.   What should be the relationship between
this research data management project and campus
HPC? 6.   What are possible governance
models? 7.   Who should CARL collaborate with on
a campus/national level 8.   How can the CIO and
campus research infrastructure help advance this
project?
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Questions/comments?

• name
• email

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