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RESEARCH DATA MANTRA
(MANAGEMENT TRAINING)
ONLINE COURSE LAUNCH
AQMeN event
10 October,2011
Robin Rice
University of Edinburgh
• Robin Rice - Project background
• JonTurner -View from the IAD
• Stuart Macdonald - On creating an Open
Educational Resource
• Cuna Ekmekcioglu – Online demo
Overview
How did we (the data library) get here?
Context of the MANTRA Project
 Data Library &
consultancy
 Edinburgh DataShare
 JISC-funded projects
 DISC-UK DataShare (2007-
2009)
 DataAudit Framework
Implementation (2008)
 Research Data MANTRA
(2010-2011)
Data Library services and projects
4
Data Library service at UoE:
Research data support within IS
 finding…
 accessing …
 using …
 teaching…
 managing
5iStock Photo, ChartsBin and mkandlez on flickr
Data repository service
6
DataShare project findings - e.g.
barriers to deposit
 Lack of clarity about ethics,
rights, ownership
 Fear of errors found by users
 Fear of ‘scooping’
 Poor documentation
 Lack of incentives / reward
7
Donald McLeod on flickr
Findings from 5 Data Audit
Framework case studies in UoE
 Storage provision often
insufficient
 Long retention periods needed
for high value data
 Ad-hoc practices; no formal
data mgmt plans
 Lack of standardised
procedures in creating and
storing data
 Minimal metadata; much effort
expended in finding extant data
on servers
8
European Parliament on flickr
Responses to past project
findings
 Develop online guidance
 Develop training
 Develop university policy
along with services to
support our researchers
9
Web guidance
 Online suite of web
pages for University
academic staff
 http://www.ed.ac.uk/is/
data-management
10
Raising the standards of data management practice by
contributing to long-term culture change.
Creating a new PhD training course to promote data
management skills, supported and delivered by the
Institute for Academic Development, University of
Edinburgh
Training: MANTRA for Change
Research Data MANTRA
(MANagement TRAining)
 Creation of open online learning
materials in RDM for postgrads
and early career researchers
 Grounded in three disciplines,
working with graduate schools
 Video stories from researchers
in variety of settings
 Data handling exercises in four
data analysis environments: R,
SPSS, NVIVO and ArcGIS
12
.ash on flickr (CC-BY-ND)
Online learning materials
 Eight units with activities, scenarios and videos:
 Research data explained
 Data management plans
 Organising data
 File formats & transformation
 Documentation & metadata
 Storage & security
 Data protection, rights and access
 Preservation, sharing and licensing
 Used Xerte OnlineToolkits to create – University of Nottingham
Data handling software
practicals
 SPSS – by Joan Corbett, SCOTCEN, National
Centre for Social Research Methods
 R – by Dr. Duncan Smallman
 NVivo – Dr.Aikaterini Chatsiou (UK Data
Archive)
 ArcGIS – by James Crone, EDINA
Download PDF exercises, work at your own pace
Selling Research Data Mgmt as a
Transferrable Skill
The FRUIT principles:
 Fun
 Relevant
 Useful
 Interactive
 Timely
Green Apple by Image Editor, flickr
CC-BY 2.0
Project evaluation
How will we know if we succeeded?
Stepping back
Critical success factors
1.The commitment of
academic staff to the
project
2. Positive feedback from
user testing
3. Increased advocacy and
awareness of research
data management best
practice across the
University.
4. Evidence that the course
is useful and used in
other contexts outwith
the University of
Edinburgh.
Curlew, Mikebaird on flickr
The policy for management of research data was
approved by the University Court on 16 May, 2011.
Vice-Principal Jeff Haywood was a champion for the
University of Edinburgh to develop the first RDM policy
in the UK
University Research Data
Management Policy
Events influencing the policy
 Recent adoption of the Code of Practice for
Research (UK Research Integrity Office, 2009) by
the university’s research office, obligating the
institution to provide support for retention and
access to data underlying published research.
 ‘Climategate’ email review at East Anglia University
highlighting the reputational risk and legal
accountability associated with staff not being
forthcoming in response to Freedom of Information
(FOI) requests for data from the public. 19
The 10 Policy Principles
1. Research data will be managed to the highest standards throughout the
research data lifecycle as part of the University’s commitment to
research excellence
2. Responsibility for research data management through a sound research
data management plan during any research project or programme lies
primarily with Principal Investigators (PIs).
3. All new research proposals [from date of adoption] must include
research data management plans or protocols that explicitly address
data capture, management, integrity, confidentiality, retention, sharing
and publication.
4. The University will provide training, support, advice and where
appropriate guidelines and templates for the research data management
and research data management plans.
5. The University will provide mechanisms and services for storage,
backup, registration, deposit and retention of research data assets in
support of current and future access, during and after completion of
research projects.
The 10 Policy Principles
6. Any data which is retained elsewhere, for example in an
international data service or domain repository should be registered
with the University.
7. Research data management plans must ensure that research data
are available for access and re-use where appropriate and under
appropriate safeguards.
8. The legitimate interests of the subjects of research data must be
protected.
9. Research data of future historical interest, and all research data that
represent records of the University, including data that substantiate
research findings, will be offered and assessed for deposit and
retention in an appropriate national or international data service or
domain repository, or a University repository.
10. Exclusive rights to reuse or publish research data should not be
handed over to commercial publishers or agents without retaining
the rights to make the data openly available for re-use, unless this is
a condition of funding.
Links
 MANTRA course
http://datalib.edina.ac.uk/mantra
 Xerte OnlineToolkits
http://www.nottingham.ac.uk/xerte/toolkits.htm
 Research data management guidance pages
http://www.ed.ac.uk/is/research-data-management
 University data policy
http://www.ed.ac.uk/is/research-data-policy
 R.Rice at ed.ac.uk

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Research Data Mantra (Management Training) Online Course Launch

  • 1. RESEARCH DATA MANTRA (MANAGEMENT TRAINING) ONLINE COURSE LAUNCH AQMeN event 10 October,2011 Robin Rice University of Edinburgh
  • 2. • Robin Rice - Project background • JonTurner -View from the IAD • Stuart Macdonald - On creating an Open Educational Resource • Cuna Ekmekcioglu – Online demo Overview
  • 3. How did we (the data library) get here? Context of the MANTRA Project
  • 4.  Data Library & consultancy  Edinburgh DataShare  JISC-funded projects  DISC-UK DataShare (2007- 2009)  DataAudit Framework Implementation (2008)  Research Data MANTRA (2010-2011) Data Library services and projects 4
  • 5. Data Library service at UoE: Research data support within IS  finding…  accessing …  using …  teaching…  managing 5iStock Photo, ChartsBin and mkandlez on flickr
  • 7. DataShare project findings - e.g. barriers to deposit  Lack of clarity about ethics, rights, ownership  Fear of errors found by users  Fear of ‘scooping’  Poor documentation  Lack of incentives / reward 7 Donald McLeod on flickr
  • 8. Findings from 5 Data Audit Framework case studies in UoE  Storage provision often insufficient  Long retention periods needed for high value data  Ad-hoc practices; no formal data mgmt plans  Lack of standardised procedures in creating and storing data  Minimal metadata; much effort expended in finding extant data on servers 8 European Parliament on flickr
  • 9. Responses to past project findings  Develop online guidance  Develop training  Develop university policy along with services to support our researchers 9
  • 10. Web guidance  Online suite of web pages for University academic staff  http://www.ed.ac.uk/is/ data-management 10
  • 11. Raising the standards of data management practice by contributing to long-term culture change. Creating a new PhD training course to promote data management skills, supported and delivered by the Institute for Academic Development, University of Edinburgh Training: MANTRA for Change
  • 12. Research Data MANTRA (MANagement TRAining)  Creation of open online learning materials in RDM for postgrads and early career researchers  Grounded in three disciplines, working with graduate schools  Video stories from researchers in variety of settings  Data handling exercises in four data analysis environments: R, SPSS, NVIVO and ArcGIS 12 .ash on flickr (CC-BY-ND)
  • 13. Online learning materials  Eight units with activities, scenarios and videos:  Research data explained  Data management plans  Organising data  File formats & transformation  Documentation & metadata  Storage & security  Data protection, rights and access  Preservation, sharing and licensing  Used Xerte OnlineToolkits to create – University of Nottingham
  • 14. Data handling software practicals  SPSS – by Joan Corbett, SCOTCEN, National Centre for Social Research Methods  R – by Dr. Duncan Smallman  NVivo – Dr.Aikaterini Chatsiou (UK Data Archive)  ArcGIS – by James Crone, EDINA Download PDF exercises, work at your own pace
  • 15. Selling Research Data Mgmt as a Transferrable Skill The FRUIT principles:  Fun  Relevant  Useful  Interactive  Timely Green Apple by Image Editor, flickr CC-BY 2.0
  • 16. Project evaluation How will we know if we succeeded? Stepping back
  • 17. Critical success factors 1.The commitment of academic staff to the project 2. Positive feedback from user testing 3. Increased advocacy and awareness of research data management best practice across the University. 4. Evidence that the course is useful and used in other contexts outwith the University of Edinburgh. Curlew, Mikebaird on flickr
  • 18. The policy for management of research data was approved by the University Court on 16 May, 2011. Vice-Principal Jeff Haywood was a champion for the University of Edinburgh to develop the first RDM policy in the UK University Research Data Management Policy
  • 19. Events influencing the policy  Recent adoption of the Code of Practice for Research (UK Research Integrity Office, 2009) by the university’s research office, obligating the institution to provide support for retention and access to data underlying published research.  ‘Climategate’ email review at East Anglia University highlighting the reputational risk and legal accountability associated with staff not being forthcoming in response to Freedom of Information (FOI) requests for data from the public. 19
  • 20. The 10 Policy Principles 1. Research data will be managed to the highest standards throughout the research data lifecycle as part of the University’s commitment to research excellence 2. Responsibility for research data management through a sound research data management plan during any research project or programme lies primarily with Principal Investigators (PIs). 3. All new research proposals [from date of adoption] must include research data management plans or protocols that explicitly address data capture, management, integrity, confidentiality, retention, sharing and publication. 4. The University will provide training, support, advice and where appropriate guidelines and templates for the research data management and research data management plans. 5. The University will provide mechanisms and services for storage, backup, registration, deposit and retention of research data assets in support of current and future access, during and after completion of research projects.
  • 21. The 10 Policy Principles 6. Any data which is retained elsewhere, for example in an international data service or domain repository should be registered with the University. 7. Research data management plans must ensure that research data are available for access and re-use where appropriate and under appropriate safeguards. 8. The legitimate interests of the subjects of research data must be protected. 9. Research data of future historical interest, and all research data that represent records of the University, including data that substantiate research findings, will be offered and assessed for deposit and retention in an appropriate national or international data service or domain repository, or a University repository. 10. Exclusive rights to reuse or publish research data should not be handed over to commercial publishers or agents without retaining the rights to make the data openly available for re-use, unless this is a condition of funding.
  • 22. Links  MANTRA course http://datalib.edina.ac.uk/mantra  Xerte OnlineToolkits http://www.nottingham.ac.uk/xerte/toolkits.htm  Research data management guidance pages http://www.ed.ac.uk/is/research-data-management  University data policy http://www.ed.ac.uk/is/research-data-policy  R.Rice at ed.ac.uk