1. Practical Help with Managing Data & Applying for Grants
Dr Richard R. Plant & Dr Andrew Thompson
Data Management Planning & Storage for Psychology project

2. How can you help me? Intro to our new one stop shop website...
What does a RDM Plan even look like?
I’m applying for a grant and need a Research Data Management Plan to apply. What tools can help me?
My research council wants me to add this “metadata” stuff to my data and then share it!
How do I backup over the short term – any ideas?
03/05/2019
© The University of Sheffield

3. Mission statement
The DMSPpsych project will establish a culture of data management planning, archiving, and ongoing reuse of data acquired as a result of psychological research within the Department of Psychology at The University of Sheffield.
We recognise it is often difficult and time consuming for the individual, research group or even department to follow a coordinated approach especially where there are no local or discipline specific exemplars to follow.
By tackling these issues at a grass roots level, on a one-to-one basis, we hope to provide support and foster an atmosphere of collaboration with regard to data management.
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© The University of Sheffield

4. Why?
You will no longer be able to apply for funding unless you have a data management plan, take better care of your data and ultimately share it
Increase your citations by at least 69%
Increase your chances of further funding and collaboration
“Backstop” your research papers – journals are likely to request datasets (Stapel fraud)
You might want to reuse your own data!
Universities need a better organizational memory
Good for science, good for UK PLC
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© The University of Sheffield

5. Cognitive dissonance?
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6. Ahhh, that’s better
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7. That looks bad!
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8. Fail to plan, plan to fail
These pictures were taken by Harvey Rutt
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9. Data loss will happen to you
As surely as death and taxes – when & how
Not just catastrophic events you should worry about:
Dropping your laptop
Hard drive failures
Software updates
Obsolescence/upgrades
Poorly described data (metadata)
Theft of equipment
People move on
Research trends (follow the money consequences)
Overwriting data/versioning
File formats
Media degradation (CDR’s, memory sticks, SSD’s)
03/05/2019
© The University of Sheffield

10. How can you help me? Intro to our new one stop shop website...
What does a RDM Plan even look like?
I’m applying for a grant and need a Research Data Management Plan to apply. What tools can help me?
My research council wants me to add this “metadata” stuff to my data and then share it!
How do I backup over the short term – any ideas?
03/05/2019
© The University of Sheffield

11. Demo
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12. What does a RDM Plan even look like?
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© The University of Sheffield

13. What things do I need to cover? Here’s what Wellcome want...
What data outputs will your research generate and what data will have value to other researchers? What does a RDM Plan even look like?
When will you share the data? My research council wants me to add this “metadata” stuff to my data and then share it?
Where will you make the data available?
How will other researchers be able to access the data?
Are any limits to data sharing required - for example, to either safeguard research participants or to gain appropriate intellectual property protection?
How will you ensure that key datasets are preserved to ensure their long-term value?
What resources will you require to deliver your plan?
03/05/2019
© The University of Sheffield

14. How do you expect me to produce something like that?
That plan looked good.
How do you expect me to produce something like that?
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22. Metadata: data about data
In the course of your working life as a professional Psychologist you will routinely generate data. By now you will have already generated varying types and amounts. Some will be quantitative and some will be qualitative, some might be from traditional experiments, observational studies or clinical work.
The common thread that links the data you generate is that it’s often rendered unusable in a frighteningly short amount of time. This is irrespective of the perceived importance at the time you collected it, did an analysis and wrote it up!
Data can become unusable for a variety of reasons, e.g. data losses through hard drive failure, accidental deletion, computer upgrades, software that can read the data becomes obsolete or file formats change. However the most common reason is that you, as the person who generated the data in the first place, forget what it means! Or rather you forget how the data was coded which means you can no longer make sense of it. This is especially true if you are looking at the data in isolation without the written interpretation or publication that went alongside it.
03/05/2019
© The University of Sheffield

23. Metadata: data about data
By describing your data with metadata you effectively annotate it so that you give it context and meaning. Metadata to all extents and purposes is data about data. Doing this isn’t as complicated as it sounds and it’s better to do it as you go along rather than see it as an additional onerous chore that’s done at the end of a project. It can be the simple things that help...
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© The University of Sheffield

24. Metadata: data about data
Start with something as simple as sensible filenames:
stats and graphs for 4 main conditions.sav to
Burt Reading Test (1974) by 4 schools [8 year old pupils].sav
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© The University of Sheffield

25. Metadata: data about data
Use the tools you have available:
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26. Metadata: data about data
Use the tools you have available:
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© The University of Sheffield

27. Administrative metadata
This is simply the “who, when and how” the data was created
The most common way of writing administrative metadata is to use the “Dublin Core DCMI Administrative Metadata” format. This is simply a set of “elements”, or sections, that you should aim to complete. A full list of the 15 elements is shown below.
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28. Administrative metadata
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29. Backing up over the short-term
Good practice suggests that you should have copies of your important files in three separate locations. Often this means a copy at home on your laptop, a copy at work or on campus and a nowadays a copy in the cloud. By cloud we mean somewhere like Dropbox or other could based file storage accessed via the internet, e.g. LiveDrive, Mozy, SkyDrive and Live Mesh, Box, Carbonite, Jungle Disk, SpiderOak, SugarSync, Syncplicity and Apples iCloud amongst others.
It is not a definitive guide and nor is it intended to provide guidance on long term archiving. Also it is not a guide to confidentiality, the Data Protection Act or anonymising personal data. It is purely about data security and preservation over the short term.
Covers the CiCS approach to the cloud with a simple how to
Covers confidentiality
Introduces Dropbox as an alternative (on either managed desktops or staff machines)
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© The University of Sheffield

30. Backing up over the short-term
Easy to understand terminology with lots of screen grabs
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31. Backing up over the short-term
Doing the same thing in Dropbox
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32. Where can I get advice again?
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© The University of Sheffield

33. We will send the website URL out in an email Survey Monkey exit survey
Data Management Planning & Storage for Psychology project