This document provides guidance on research data management for postgraduates. It discusses why research data management is important, including ensuring long-term preservation and discoverability of data, supporting more rigorous research through record keeping, and preventing academic fraud. It also outlines the key elements to include in a research data management plan, such as data type and format, storage and security, ownership and sharing. Developing a data management plan early in the research process is recommended to facilitate data preservation and sharing.

1. Research Data Management for Postgraduates
Lynn Woolfrey
lynn.woolfrey@uct.ac.za
Ulwazi Knowledge Commons, Chancellor Oppenheimer Library
University of Cape Town, 27 March, 2014

2. Research Data Management
Preparing Data
for Re-use
Data Collection
and File
Creation
Depositing
Data for re-use
Data
Analysis
Project
Start-Up
Proposal
Development &
DM Planning
“In the context of research …"Data Management" refers to the
storage, access and preservation of data produced from a given
investigation.”
Texas A&M, Research Data Management Lib Guide http://guides.library.tamu.edu/DataManagement
Graphic from Jake Carlson and Ron Nakao. ICPSR Summer Program Course on “Curating Curating and Managing Research Data for Re-Use
https://www.icpsr.umich.edu/icpsrweb/sumprog/courses/0149

3. Also called Research Data Curation

4. From 2011 research funders began requiring research data
management plans in funding proposals

5. UCT is creating policy and infrastructure for the long-term
preservation of UCT research output and its underlying data

6. WHY SHOULD WE DO IT?
Research Data Management

7. Actually, where
IS my data?
What do they
mean by RDM?
Who are they to tell
me what to do with
my data?
The university is just
dreaming up more
admin for me!
To ensure research data is preserved and
discoverable in the long-term

8. To control the
data deluge
To support
more rigorous
research
To ensure data
preservation
and data
discovery
For new
research by
original
researchers
For new
research by
other
researchers
For data
verification
to prevent
academic
fraud
Why should our research data be
actively managed?

9. RDM supports better research
Keeping accurate records of the research process is
sound research practice

10. RDM can prevent academic fraud
Findings of Professor Diederick Stapel, at
Tilburg University (including that meat
eaters are more aggressive) were found to
be based on faked data.
He published 55 academic papers and
Supervised 19 Ph.D. degrees based on the
data.
“Stapel’s fraud went undetected for so long
because of “a general culture of careless,
selective and uncritical handling of
research and data” at the University
Data Shows Meat Eaters
are more Aggressive

11. RDM enables data re-use
Research funders want to maximise returns on their
investment in research by encouraging data re-use

12. HOW TO WRITE A RESEARCH DATA MANAGEMENT PLAN
Research Data Management

13. Data Management Planning elements
• Data Type
• Data Format (including size of data files)
• Data description (metadata) standards used
• Storage and backup
• Security
• Responsibility
• Ownership and Intellectual Property rights
• Data sharing

14. What type of data will you collect?
Research Data is ….primary input into research and
first order results of that research
• “…Records documenting the research process (e.g. research protocols; applications
for regulatory approvals and approvals granted)
• Records documenting research outcomes or products (e.g. technical reports)
• Records documenting the management of the research process/project(s)(e.g.
applications for funding; contracts; purchase invoices; staff timesheets)
• Research data in both ‘raw’ and ‘analysed’ form (e.g. datasets in Stata; notes;
completed questionnaires; audio/video recordings; images; instrument readings;
samples).

15. What format will your data be in?
Results of a UCT survey on research data management needs, April 2013.

16. How much data will you collect?

17. Who owns the data?
Who will manage the data?

18. What standards will you use to
describe your data?

19. Standards for file naming,
versioning, metadata
http://www.dcc.ac.uk/resources
http://www.icpsr.umich.edu/icpsrweb/content/datamanagement/index.html
http://surveynetwork.org/;www.ddialliance.org
http://www.datafirst.uct.ac.za/catalog

20. How will your data be stored?
• How will data be stored and backed up during the project?
• How will data be selected for longer-term preservation?
• How much space will you need for your data?
• In which repository will the data be held?
• How long will the data be retained?
• How will data security be handled during the project for access by
collaborators and data transfer from the field to storage?
• How will you deal with confidential data during the project?
• How will data authenticity be assured?

21. How will your data be shared?
“*If Intellectual Property rights don’t apply+ the data generated
from this research must become available to other researchers
working in the same field (National Research Foundation:
Acceptance of grant conditions 2010).”

22. Plan for data sharing now
Your research reputation will in future be linked to making
your well-organised research data available to the academic
community once you complete your research. This will be
done through the coupling of data sharing to academic
recognition, and through increased citations from Linked
Open Data.

23. Web-tools for Data Management
Planning
https://dmponline.dcc.ac.uk/
http://www.data-archive.ac.uk/create-manage
https://dmp.cdlib.org/

24. Questions?
Questions?