research data management: obstacles faced by the novice data manager

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CSIR Research Data Management: the way forward Louise Patterton CSIRIS September 2013

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Page 1: Research Data Management: obstacles faced by the novice data manager

CSIR Research Data Management: the way forward

Louise PattertonCSIRISSeptember 2013

Page 2: Research Data Management: obstacles faced by the novice data manager

The future of research data in the CSIR

• Definition• Global trends• Current situation• Problems• Solving the problems• Plan of action• Policy• Summary……………..

Page 3: Research Data Management: obstacles faced by the novice data manager

Not so fast…..

Page 4: Research Data Management: obstacles faced by the novice data manager

OBSTACLE The concept of Research Data Management (RDM) new!

OBSTACLE CSIR Research Data status quo UNKNOWN!

OBSTACLECSIR Research Data policy NON-EXISTENT!

OBSTACLEGlobal trends WE ARE FALLING BEHIND!

Page 5: Research Data Management: obstacles faced by the novice data manager

Excuse me sir......do you have a minute to talk about…. carrots?

Page 6: Research Data Management: obstacles faced by the novice data manager

Dear Colleague,

We will be repeating the NeDICC workshop for rookie data managers in Pretoria on 28 August. This very successful workshop was launched at the 5th African Conference for Digital Scholarship and Curation during June and due to demand we have decided to make it available in Gauteng as well. Space is limited so unfortunately we can accommodate no more than 50 attendees.

Venue: CSIR Knowledge CommonsDate: 28 August 2013Time: 09:00 - 14:00Price: R399 VAT included

A light lunch will be served at 13:00.

The workshop will provide those who are starting out on the data management journey the opportunity to hear how other rookie data managers are coping with the new challenges, where they find their information and who they talk to. Delegates will also have the opportunity gain advice from those who have already engaged with researchers and those who are providing their research clients with appropriate training. They will also have the opportunity to hear from one institution where data management has become part of the way in which things get done.

OBSTACLE #1: Unfamiliarity with ‘Research Data Management” concept.........

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Page 8: Research Data Management: obstacles faced by the novice data manager

Welcome to the Carrot Cake Factory!

Page 9: Research Data Management: obstacles faced by the novice data manager

Welcome to the CSIR Carrot Cake Factory!

Page 10: Research Data Management: obstacles faced by the novice data manager

WE PRESENT (PROUDLY) :

Carrot cake Carrot salad

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However, clients/competitors now require:

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Carrots required! Carrot audit required!

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Excuse me sir......do you have a minute to talk about…. carrots?

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carrot origin, carrot harvesting, carrot organisation.......

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carrot quality

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carrot growth, carrot phases, carrot versions

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carrot processing

Page 18: Research Data Management: obstacles faced by the novice data manager

carrot storage

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carrot storage

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carrot quality

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retrieval, grouping, ordening

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documentation, calibration, logbooks

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accessibility, security, sharing

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Sharing: how?

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Establishing risks of data sharing

• misuse• misinterpretation

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Establishing disposal policies, disposal methods

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???CSIR librarian

OBSTACLE #2 : What research data do we have in the CSIR? (and that’s just the start……)

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Carrot audit required!

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OBSTACLE #3: Many scientists, no research data management policy…limited grasp of RDM benefits

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BENEFITS OF RDM PLANNING:

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Benefits with regards to data access:

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Benefits with regards to sharing

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Benefits with regards to research integrity

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Benefits with regards to research efficiency

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Obstacle #4: Global trends............way ahead

• Training tools: (courses, degrees) * DMTpsych (psychology) * Mantra (wide coverage) * Cairo (creative arts) * DATUM for Health (health studies) * DataTrain (archaeology)

• Data Archives/Data Repositories/Data banks

* UK Data Archive (soc science in UK) * National Space Science Data Center (space)

• Funder requirements * DMP is essential

Page 36: Research Data Management: obstacles faced by the novice data manager

 • UK: Legal requirements…all Research Councils now have

research data management policies, based on a set of common principles formulated by Research Councils UK

• USA: National Institutes of Health: Data Sharing Policy: Supports the sharing of research data and expects researchers funded at $500,000 or more to include a data sharing plan in their grant proposals

• USA: National Science Foundation (NSF): Dissemination and Sharing of Research Results: Beginning January 18, 2011, NSF will require grant proposals to include a supplementary data management plan of no more than 2 pages. This requirement is a new implementation of the long-standing NSF Data Sharing Policy

• Australia: Monash University Policy Bank: The purpose of this policy is to ensure that research data is stored, retained, made accessible for use and reuse, and/or disposed of, according to legal, statutory, ethical and funding bodies’ requirements.

Global Research Data Management Policy trends

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Research Funders % elements

National Science Foundation (NSF) 53%NSF Basic Research to Enable Agricultural Development (BREAD)

59%

NSF Division of Earth Sciences (EAR) 65%NSF Division of Ocean Sciences 59%NSF Integrated Ocean Drilling Program 47%NSF Ocean Acidification Research 59%DOE Atmospheric Radiation Measurement Program (ARM)

76%

National Aeronautics and Space Administration (NASA) - Earth Sciences

65%

NIH - National Human Genome Research Institute

88%

NIH - Genome-Wide Association Studies (GWAS)

76%

American Heart Association 0%

Issues in Science and Technology Librarianship: Percent of total data elements addressed by policy (Dietrich et al, 2012)

Page 38: Research Data Management: obstacles faced by the novice data manager

Research Funders

Outputs Data

Time limits

Data plan

Access/sharing

Longterm curation

Monitoring

Guidance

Repository

Data centre

Costs

AHRC - -BBSRC

CRUK - -

EPSRC - -

ESRC

MRC - -

NERC

STFC

WellcomeTrust

UK Funder requirements for data management and sharing (DCC)

Source: http://www.dcc.ac.uk/resources/policy-and-legal/overview-funders-data-policies

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• “Homeless” data quickly become no data at all: curation NB

• There is no economic “magic bullet” that does not require someone, somewhere, to pay: funding required

• What happens to valuable data when project funding ends: long term planning required

• Additionally:

* infrastructure * policy/guidelines/training * team

• Data management planning does not happen in a vacuum

• :

Some final points to ponder on….

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So, in a nutshell..........

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THE WAY FORWARD:

Step 1:

• survey/audit/inventory• aim: Research Data Management Practices• questionnaire edited, refined• ethics clearance• target sample chosen: Research Group Leaders• audio recording…transcribed• all units, all Research Group Leaders• confidentiality• benchmark against similar studies

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THE WAY FORWARD:

Step 2: Analysis………………………………………………………………………………………………………………………………………………..…..……………………………..

Step 3:Recommendations: • personnel• infrastructure• cost

Step 99:• CSIR Research Data Policy• Training/Guidelines• Data Repository• Sharing

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Excuse me sir......do you have a minute to talk about…. carrots?

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Thanks for listening!