ROLES AND RESPONSIBILITIES FOR DATA MANAGEMENT AN AUSTRALIAN PERSPECTIVE

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ROLES AND RESPONSIBILITIES FOR DATA MANAGEMENT
AN AUSTRALIAN PERSPECTIVE

• Andrew Treloar
• Deputy Director, ANDS

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Outline

• Reservations
• Relativities
• Reprise
• Roles and Responsibilities
• Reflections

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Reservations
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Existing work in this area

• Lyon, L. (2007). Dealing with Data Roles,
  Rights, Responsibilities and Relationships -
  Consultancy Report
• Key Perspectives (2008). The Skills, Role And
  Career Structure Of Data Scientists And Curators
  An Assessment Of Current Practice And Future
  Needs
• Plus aspects of the entire JISC work programme!

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Relativities
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Similarities and differences

• Similarities
• Government funding of universities and research
• Strong tradition of university-led research
• Strong focus on e-Research
• Differences
• Only two funding councils (ARC, NHMRC)
• Only one discipline data centre (ASSDA, ? UKDA)
• Smaller sector (40 universities)

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National Collaborative Research Infrastructure
Strategy
Note scaled to EU or US economies this is
analogous to 1B USD per annum
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Platforms for Collaboration Major Investments
2007-2011
Capability Computing Advanced models NCI - 26M
The Data Commons Data Federations ANDS - 24M
Collaboration services Research workflows ARCS -
20M
Research connectivity Seamless reach AAFAREN -
6M
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Australian Strategic Roadmap Review

• Data Storage (p.21)
• National data-fabric, based on institutional
  nodes
• Shared Data (p. 22)
• More ANDS
• Coordination Component (p. 23)
• Integration of eResearch activities
• JISC-lite?
• Inclusion of data itself as collaborative
  research infrastructure (p. 9)
• Expertise as an enabling infrastructure (p. 23)
• Addition of humanities and social sciences
• http//www.innovation.gov.au/ScienceAndResearch/Do
  cuments/Strategic20Roadmap20Aug202008.pdf
• Not yet funded

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Reprise
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The ANDS Blueprint

• Towards the Australian Data Commons (TADC)
• Developed during 2007 by ANDS Technical Working
  Group
• Mapped out coherent vision of what needs to be
  done in the data space
• Available at http//www.pfc.org.au/bin/view/Main/D
  ata

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TADC Why Data? Why Now?

• We are in an era of increasing data-intensive
  research
• Almost all data is now born digital
• Increasing amount of data generated(semi-)automat
  ically
• Consequently, increasing effort and therefore
  funding will necessarily be diverted to data and
  data management over time (Towards the
  Australian Data Commons (TADC), p. 4)

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TADC Need for standardisation

• Software and hardware keep getting cheaper,
  wetware keeps getting more expensive
• Fixing data management problems is enormously
  labour intensive and costly
• Consequently, standardisation within forms of
  data and simplification in the frameworks around
  retention, storage, access and use of data, and
  the elimination of differences whose resolution
  requires labour, must be made, if the on-going
  keeping and reuse of data is to remain
  affordable (TADC, p. 5)

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TADC Role of data federations

• With more data online, more can be done
• Possible now to answer questions unrelated to
  reasons why data was collected originally
• Increasing focus on cross-disciplinary science
• Consequently greater clarity is needed over
  control and access to community-funded data, and
  the means of aggregating, federating and
  accessing such data are increasingly important
  (TADC, p. 5)

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The ANDS Vision

• As a vision, ANDS sets out to transform the
  disparate collections of research data around
  Australia into a cohesive corpus of research
  resources. This transformation would assist the
  connection of Australian and international data
  centres, repositories and online collections to
  enable serendipitous discovery,
  cross-disciplinary research, and cross-repository
  workflows. (TADC, p. 5)

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ANDS Assumptions

• ANDS doesnt have enough money to fund storage
• Thus is predicated on institutionally-supported
  solutions
• ANDS aims to leverage existing activity, and
  coordinate/fund new activity
• ANDS will only start to build the Australian
  Research Data Commons
• http//ands.org.au/andsinterimbusinessplan-final.p
  df

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Realising the Vision
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ANDS Delivery Structure

• ANDS has been structured as four inter-related
  and co-ordinated service delivery programs
• Developing Frameworks
• Providing Utilities
• Seeding the Commons
• Building Capabilities
• Plus candidate service development activities
  funded through National eResearch Architecture
  Taskforce projects

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Developing Frameworks

• Influencing relevant national policies
• Building common understanding of data management
  issues and solutions across government, research
  funding agencies, and research intensive
  organizations
• Encouraging moves in favour of discipline-acceptab
  le default sharing practices

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Providing Utilities

• Building and delivering national technical
  services to support the data commons
• Examples
• Discovery services
• Persistent identifier minting and management
• Collections registry to underpin discovery
• Providing capability within ANDS for integration
  of existing systems into Australian Data Commons

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Seeding the Commons

• In targeted areas (because not enough resource to
  do everything), working to improve
• fabric for data management
• amount of content
• data capture and management practice
• Plus, opportunistic content recruitment in year 1
• Selection process to identify targets
• Placement of ANDS-funded staff, together with
  co-investment

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Building Capabilities

• Improving level of capability for research data
  management and research access to data
• train-the-trainer model
• targeting both early career researchers and
  research IT support
• Building community around data management concerns

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Roles and Responsibilities
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Two UK lists

• Dealing with data
• Scientist
• Institution
• Data centre
• User
• Funder
• Publisher

• Swan report
• Data creator
• Data scientist
• Data manager
• Data librarian

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Australian perspective

• Researcher
• Institution
• National data fabric
• Research re-user
• Funder
• Publisher
• Public

• This is an ecosystem, just like (in fact an
  extension of!) scholarly communication (Kaufer
  and Carley 1993)
• Players are mutually defining, coadaptive, and
  coevolving components of a single ecology (KC,
  p. 95)

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Implications for ANDS

• Funders cant demand what cant yet be supported
• Researchers need to get rewarded for the desired
  behaviour
• Cant just try to influence a single component of
  ecosystem
• cf slow progress on OA publishing

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Australian Code for the Responsible Conduct of
Research

• Describes the responsibilities of institutions
  and researchers, including in management of
  research data primary materials
• Joint initiative of Universities Australia, ARC,
  NHMRC

• Institutions are to
• retain research data and primary materials
• provide secure research data storage and
  record-keeping facilities
• identify ownership of research data and primary
  materials
• ensure security and confidentiality of research
  data and primary materials

• Researchers are to
• retain research data and primary materials
• manage storage of research data and
  record-keeping facilities
• maintain confidentiality of research data and
  primary materials

http//www.nhmrc.gov.au/publications/synopses/_fil
es/r39.pdf
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Reflections
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Some closing thoughts

• Need career path for third profession
• Disciplines are international gt need
  co-ordinated response
• UK and AU can usefully continue to play leapfrog
• All the players in the data management ecosystem
  interlock, and so we need co-ordinated responses
  at each point

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What do we want?

• More researchers re-using more data more often
• So we need to
• lower the costs and raise the benefits
• have data be seen as a first class research
  output
• drive culture change in all the roles
• build partnerships between those with
  responsibilities

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Questions?

• andrew.treloar_at_ands.org.au ross.wilkinson_at_ands.org
  .au
• http//andrew.treloar.net/ http//ands.org.au/