1. Data Management Planning and DMPonline
Sarah Jones
DCC, University of Glasgow
Funded by:
VADS4R, Glasgow School of Art, 16th June 2014

2. What is the DCC?
A Jisc-funded service to support universities with research data management
Run training courses
Provide guidance on good practice
Develop tools such as DMPonline
Offer tailored support to universities …

3. Data management is part of
What is research data management?
Plan
Create
Document
Use
Publish
Share
“the active management and appraisal of data over the lifecycle of scholarly and scientific interest”
Data management is part of
good research practice 3

4. What is a data management plan?
A brief plan written at the start of your project to define:
how your data will be created?
how it will be documented?
who will access it?
where it will be stored?
who will back it up?
whether (and how) it will be shared & preserved?
DMPs are often submitted as part of grant applications, but are useful whenever you’re creating data.

5. Why develop a DMP? to help you manage your data
to make informed decisions so you don’t have to figure out things as you go
to anticipate and avoid problems e.g. data loss
to make your life easier!

6. Which UK funders require a DMP?
overview-funders-data-policies

7. DCC Checklist for a DMP 13 questions on what’s asked across the board
Prompts / pointers to help researchers get started
Guidance on how to answer

8. Common themes in DMPs Description of data to be collected / created
(i.e. content, type, format, volume...)
Standards / methodologies for data collection & management
Ethics and Intellectual Property
(highlight any restrictions on data sharing e.g. embargoes, confidentiality)
Plans for data sharing and access
(i.e. how, when, to whom)
Strategy for long-term preservation

9. 1. Describing data to be collected
What type of data will you produce?
What file format(s) will your data be in?
How much data will be produced?
How will you create your data?

10. Some formats are better for the long-term
It’s preferable to opt for formats that are:
Uncompressed
Non-proprietary
Open, documented
Standard representation (ASCII, Unicode)
Data centres may have preferred formats for deposit e.g.
Type
Recommended
Non-preferred
Tabular data
CSV, TSV, SPSS portable
Excel
Text
Plain text, HTML, RTF
PDF/A only if layout matters
Word
Media
Container: MP4, Ogg
Codec: Theora, Dirac, FLAC
Quicktime
H264
Images
TIFF, JPEG2000, PNG
GIF, JPG
Structured data
XML, RDF
RDBMS
Some formats are better for data sharing and long-term preservation than others.
It’s preferable to use formats that are uncompressed (e.g. large, high-quality files like .wav), non-proprietary (i.e. open) standards that are documented and well-understood. This aids preservation and interoperability.
Some data centres have preferred formats for deposit so it’s worthwhile encouraging researchers to consult these to check.
Further examples:

11. Tools for researchers www.dcc.ac.uk/resources/external/tools-services/
managing-active-research-data

12. 2. Standards and methodologies
What metadata and documentation will you record?
What standards are used in your field?
How will your data be organised?
Where will it be stored and backed-up?

13. Documentation and standards
Metadata: basic info e.g. title, author, dates, access rights...
Documentation: methods, code, data dictionary, context...
Use standards wherever possible for interoperability
To make sure their data can be understood by themselves, their community and others, researchers should create metadata and documentation.
Metadata is basic descriptive information to help identify and understand the structure of the data e.g. title, author...
Documentation provides the wider context. It’s useful to share the methodology / workflow, software and any information needed to understand the data e.g. explanation of abbreviations or acronyms
There are lots of standards that can be used. The DCC started a catalogue of disciplinary metadata standards which is now being taken forward as an international initiative via an RDA working group

14. 3. Ethical and IPR implications
Are you seeking consent from participants?
Who owns your data or has rights in it?
Are you re-using other people’s data?

15. Seek consent for data sharing & preservation
If you don’t ask, data centres won’t be able to accept your data – regardless of any conditions on the original grant or your desire for it to be shared.

16. 4. Data sharing and reuse Are you allowed to share your data?
Who will you share with and how?
Do you need to impose conditions on reuse?
How will you license the data for clarity?

17. License your data for reuse
Outlines pros and cons of each approach and gives practical advice on how to implement your licence
CREATIVE COMMONS LIMITATIONS
NC Non-Commercial
What counts as commercial?
SA Share Alike
Reduces interoperability
ND No Derivatives
Severely restricts use
Guidance from the DCC can also help researchers to understand data licensing. This guide outlines the pros and cons of each approach e.g. the limitations of some CC options
Under Horizon 2020 it’s recommended that researchers use CC-0 or CC-BY to make data as open as possible.
how-guides/license-research-data

18. 5. Preservation Which data do you need to keep?
Will you deposit your data in a repository?
Do you need to prepare it for deposit?

19. Lists of repositories to choose from
The EC guidelines suggest selecting a suitable repository. The Databib and Re3data lists can be useful for this. They allow you to search and browse by subject. Re3data also allows you to restrict the search by certificates, open access repositories and persistent identifiers.

20. Managing and sharing data: a best practice guide
How to write a DMP
Formatting your data
Documentation
Data sharing
Ethics and consent
Copyright …

21. Tips for writing DMPs Seek advice - consult and collaborate
Consider good practice for your field
Base plans on available skills & support
Make sure implementation is feasible

22. A useful framework to get you started
Think about why the questions are being asked – why is it useful to consider that topic?
Look at examples to help you understand what to write
I recommend this ICPSR resource
It explains the importance of different questions as a pointer to how to answer
Examples are given. This is the most frequent request we get at DCC - examples help researchers think of what to write for their context

23. Help from the DCC
A web-based tool to help researchers write data management plans
The DCC has produced a How to guide on writing DMPs and developed a tool to help

24. DMPonline demo

25. Thanks – any questions?
DCC guidance, tools and case studies: Follow us on and #ukdcc