Data Management Principles Planning

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Data Management Principles - Planning

• UniMelb Cluster - Research Symposium
• Lyle Winton
• 24 Oct 2008

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Who am I?

• Dr Lyle Winton
• Background
• Researcher/Scientist
• experimental high energy physics, distributed
  systems, Grid
• Technical Consultant
• education and research for gov. infrastructure
  projects
• Software Engineer
• industry, higher education (web development,
  information systems, enterprise systems)
• Currently
• eScholarship Research Centre (eSRC) Research
  Computing Services, Information Services
• Senior Research Support Officer (eResearch)
• provide ICT support for research workers, supply
  expertise strategic advice
• develop plans for eResearch infrastructure
• be active in local national eResearch
  co-ordination groups

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Data Management

• What are we doing(eSRC eR myself, Joanne
  Evans, Simon Porter, Gavan McCarthy, Leon
  Sterling)
• Policy
• Planning (focus)
• Tools (focus)
• Services
• Infrastructure
• Training (focus)
• Consultancy (focus)

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Nationally

• ANDS Vision The development of ANDS is intended
  to provide the essential meeting place where the
  Australian path forward for research data
  management can evolve and where a vision can be
  achieved.
• Towards an Australian Data Commons, ANDS Oct
  2007
• institutions will be expected to have and
  support data management plans, and any researcher
  seeking support through a number of government
  funding agencies will be expected to describe how
  the data generated through the project will be
  managed throughout its lifecycle. ANDS Interim
  Business Plan Sept 2008
• Enabling Components Data Storage This
  investment will extend to research organisations
  for the development of institutional nodes of the
  storage grid, on the condition that the storage
  is used exclusively for research data the
  institutes co-invest in the infrastructure each
  institute publishes and adopts a data management
  plan and each institute ensures its researchers
  use and abide by the data management
  plan. Strategic Roadmap for Research
  Infrastructure, NCRIS July 2008.

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Known problems

• A mature data stewardship system, interlinking
  policy and infrastructure could address the needs
  of researchers and improve the quality and
  efficiency of Australian innovation and
  research.
• The survey found that individual researchers and
  research groups do not include data management as
  an element when planning research projects.
• Grants do not fund the creation of datasets as
  an end in itself, nor are funds provided
  explicitly for the management of data.
• The survey found that research groups and
  organisations rarely have formal policies for the
  management of data. They usually have a set of
  practices that may or may not be adhered to at
  the project level.
• Researchers see research data as belonging to
  them. Experienced researchers have been
  managing data all their careers.
• AERES report Oct 2006

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Some UniMelb goals

• Information Futures Commission
• Excerpts from final report
• We will know we're on track if
• Management and dissemination of research data
  and digital collections is painless.
• We propose that we will
• Develop and adopt standards, guidelines and
  processes for the management, access and
  preservation of research data
• Implement a program for targeted curation of
  collections
• Implement a digitisation and profiling strategy
  for works in collections (including 'born
  digital')
• Numerous references to services surround data
• Adequate physical and digital collections
  support research, learning and teaching, and
  knowledge transfer Cataloguing and search tools
  make it easy to discover, cite and manage
  information.

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Where are we heading?

• Formal Research Data Management
  Infrastructure/Plans/Policies are emerging!
• Globally researchers are beginning to adopt this
  as good practice
• University is moving towards this as standard
  practice
• We need to start implementing and/or improving
• Professional Data/Info Management Practice
• ensuring quality research data
• enables (appropriate) access
• enables reuse of data
• Policy, Intellectual Property
  Licensing,Contracts, Legislation, Process
• not just paperwork and hurdles
• ensuring research has integrity, repeatability
• enables (appropriate) access
• enables reuse of data

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Why now?

• Research Data is increasing in size
• Research Collaborations are increasing
• Data is increasingly digital
• Wonderful opportunities for reuse,sharing,
  collaboration, analysis
• However
• while microfilm and non-acidic papercan last for
  100 years
• magnetic media lasts 10 years
• optical media lasts 20 years(with proper
  handling)
• 2-10 of hard drives fail every year
• software hardware can outdate
• And much info is still only hardcopy
• Lab books, notes, primary data, samples

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Parts of the elephant

• Researchers Departments
• are at varying levels of maturity
• are experiencing different pain-points
• Infrastructure Providers
• are focused on specific problems
• are experts in different aspects/solutions
• are getting varying requirements

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Framing the elephant
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Training for post-grads

• UpSkills eResearch Stream Data Management
  Workshop
• run 3 so far
• Influences and References
• The University of Melbourne Policy(Research
  Office, Records Services)
• Australian Code for Responsible Conduct of
  Research(NHMRC, ARC, Universities Australia)
• OAK Law Project, QUT
• Belinda Weaver presentations, UQ
• PILIN Project (ANDS/ARROW)
• A few examples!
• Review of material
• By eScholarship Research Centre
• By local eResearch social network (eCoffee)
• By a small group of department research/IT
  managers
• By School of Graduate Research

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Training for post-grads

• Workshop Covers
• Components of a Data Management Plan
• Recommended reading list
• Information Modelling, Good Practice Guidance
• Technologies
• Feedback has been very positive!!!
• Development of a web site (ongoing)
• Resources, References, Examples, QA
• A Research DMP Template (ongoing)
• Drafting guidelines to support theimplementation
  and compliance (underway)
• Future developments
• Training materials for supervisors?
• Discussing undergraduate data managementtraining
  across Uni
• Possible DMP registry

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Why Manage Research Data

• IT IMPROVES YOUR RESEARCH BOTH NOW AND LATER
• Data is often valuable for a long time!!!
• Results of your research may outlast the project,
  your degree,your position, your career, your
  institution
• historical value, predictable or unforseen
• Maximise usefulness of data to fellow researchers
• Context for the research, how data was collected,
  quality controls, how people canand should use
  it (access and licensing), how you then attribute
  people/projects
• can help lead to subsequent research papers
• Good Practice ? Better Research
• DMPs state the parameters within which you MUST
  do research,then follow them! (being a
  Professional Researcher)
• document for new comers, your group, project,
  externals
• Ensure research integrity (and repeatability)
• through keeping better records
• can trace your outcomes right from data
  collection, through research method, through to
  results
• promotes awareness of responsibilities, policies,
  ethics, legislation

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Why Manage Research Data

• IT MAY SAVE WASTED TIME
• You need to properly
• Collect research data
• Manage research data
• Archive research data
• otherwise there is a risk you cannot use your
  data, wasting years of effort.
• From a study of 500 charges of research
  misconduct 40 could have been avoided by good
  data management practice!
• Student submits her PhD thesis for examination
  then leaves country taking the data with them.
  An examiner questions the integrity of the
  research data. A reanalysis of the data and
  original questionnaire is required.
• Participant in a research project lodges a claim
  for compensation, alleging that he was not
  adequately informed about the effects of the
  study, does not recall giving consent, and the
  raw data he provided has become public. Where are
  the records?
• Ten years after a patent has been granted a
  patent infringement action is lodged. The
  laboratory notebook is required.
• At completion of a research project the data and
  records are boxed and stored in a departmental
  storeroom. Sometime later the researcher needs to
  access the original records to refute a claim of
  falsification. He finds that the storeroom has
  since been converted into a laboratory/coffee-shop
  /learning-hub.

Defending Integrity gtgtgt getting to Data
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Why Manage Research Data

• AND YOU NEED TO PLAN AHEAD
• University of Melbourne Policy
• research methods and results open to scrutiny
• data should be retained in a durable and
  appropriately referenced form
• for at least 5 years from any publication
• minimum of 15 years for clinical trials
• minimum of 7 years for adult psychological files
  (for minors 7 years after reaching 18)
• or longer if external/funding/regulatory/archival
  requirements
• research units departments have
  formallydocumented procedures for retention
• researchers must comply
• ensure research data and records areaccurate,
  complete, authentic and reliable
• data and records formed for verification
  andinclude sufficient detail(authenticity and
  validity of conclusions)

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Whats in a DMP?

• A Possible Template
• Context (Outline, Pre-planning, Decisions)
• Responsibilities (ethics, consent, licensing,
  legislation, funding requirements, reporting)
• Process Policies
• Data Collection and QC Process
• Access Policy
• Appropriate Use and Access Patterns
• Data Maintenance, Persistence and Archival
  Practice
• Decommissioning/Destruction/Sanitisation
• Technical Requirements (policy for system
  developers/implementers/admins)
• Current Infrastructure and Requirements
• Future Infrastructure Requirements
• Interoperability
• Data Security
• Availability, Reliability, Support and Response
• (full template found at http//www.esrc.unimelb.ed
  u.au/dmp )

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Why Plan?

• Making the most of Infrastructure
• ARCS Data Fabric (NCRIS)
• University Infrastructure
• National Compute Infrastructure (VLSCI, ANUSF,
  VPAC)
• Advanced Technology (imaging, sequencing,
  synchrotron)

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Why Plan?

• Making the most of Research Networks
• ANDS Data Commons
• BioGrid Australia
• Protein Data Bank
• Increasingly you need to ensure
• Research integrity, traceability
• Data and Result quality
• Data reusability
• Data security (misuse/damage, unintended/intended
  )

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Communication

• 2-way Communication is important
• Administration/ICT and Research Community
• Good Practice will emerge from both Research and
  ICT expertise
• National Infrastructure
• Opportunities and Trade-offs
• 3 -way communication ?
• Vision a local community of practice
• to provide and review guidelines and policies
• to share data management plans
• to drive development of shared infrastructure
• advocate for and steer national infrastructure

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What you can do

• http//www.esrc.unimelb.edu.au/dmp
• Provide general feedback
• Ask questions, well seek answers
• Work with us on guidance good practice
• Encourage students to attend future UpSkills
• Talk with your students/group/department about
  formally documenting a DMP
• Feed back you DMP