This document summarizes a presentation about managing data throughout the research lifecycle. It discusses the stages of the research lifecycle, including planning, data creation, documentation, storage, sharing, and preservation. It provides examples of research lifecycle models and addresses key questions to consider at each stage, such as what formats to use, how to document data, where to store it, and how to share and preserve it. The presentation emphasizes making informed decisions about data management and talking to colleagues for support and advice.

1. Managing data throughout
the research lifecycle
considerations and pointers to support
University of Northampton, 20th February 2013
Marieke Guy
DCC, University of Bath
m.guy@ukoln.ac.uk
Funded by:
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2. Today’s Talk…
Managing data throughout the
research lifecycle
• What is the research lifecycle?
• How do you manage data?
• What questions does managing data raise?

3. What is the research lifecycle?
• Research activity often takes place in stages
which form a ‘lifecycle’
• Data is created at points during this lifecycle
• The data created has its own lifespan
“Data often have a longer lifespan than the research
project that creates them. Researchers may continue to
work on data after funding has ceased, follow-up
projects may analyse or add to the data, and data may
be re-used by other researchers.” UKDA

4. Example 1: DCC lifecycle model
A model to show the activities PLAN
and people involved in CREATE DATA
managing data. ADD DOCUMENTATION
RESEARCHERS
IT
DATA CENTRE

5. Example 2: Research360 lifecycle
Research
Process

6. Example 3: UK Data Archive

7. Example 4: UK Data Archive

8. Key ideas from the research lifecycle
• Different research lifecycles suit different researchers
• Research is a circular process
• Certain stages are likely to be familiar to many
researchers – conceptualisation/planning, creation,
active use/documentation, publication etc…
• Certain stages are likely to be familiar to less researchers
– sharing, re-use etc…
• Data may be created at many stages during the process
(intervention points)
• Data is likely to need management at many stages
during the process

9. Key Qs from the research lifecycle
1. What data will you produce?
5.
1.
Preservation
Create 2. How will you organise the data?
& Re-Use
3. Can you/others understand the
data
4.
2.
4. What data will be deposited and
Publication
& Deposit
Active Use where?
5. Who will be interested in re-using
3. the data?
Documentation

10. What is data curation?
“the active management and
Manage
appraisal of data over the
lifecycle of scholarly and
scientific interest”
Data management is part of
Share good research practice

11. Good data management is about
making informed decisions

12. •http://xkcd.com/949

13. How do you manage data?
Key questions to consider when:
- Creating data
- Documenting data
- Storing data
- Sharing data
- Preserving data
- Planning data management
Examples and pointers to support

14. Creating data: questions
What formats will you use?
- determined by the instruments / software you have to use
- common, widespread formats to enable reuse
How will you create your data?
- What methodologies and standards will you use?
- How will you address ethical concerns and protect participants?
- Will you control variations to provide quality assurance?
- What external data sets will you use?
(See the BL Social Science Collection guide to Management and
Business studies datasets)

15. Creating data: advice
Different formats are good for different things
- open, lossless formats are more sustainable e.g. rtf, xml, tif, wav
- proprietary and/or compressed formats are less preservable but
are often in widespread use e.g. doc, jpg, mp3
May choose one format for analysis then convert
to a standard format for preservation / sharing
Excellent guidance on creating data & managing ethics in:
www.data-archive.ac.uk/media/2894/managingsharing.pdf

16. File formats for long-term access
• Unencrypted
• Uncompressed
• Non-proprietary/patent-encumbered
• Open, documented standard
• Standard representation (ASCII, Unicode)
Type Recommended Avoid for data sharing
Tabular data CSV, TSV, SPSS portable Excel
Text Plain text, HTML, RTF Word
PDF/A only if layout matters
Media Container: MP4, Ogg Quicktime
Codec: Theora, Dirac, FLAC H264
Images TIFF, JPEG2000, PNG GIF, JPG
Structured data XML, RDF RDBMS
Further examples: http://www.data-archive.ac.uk/create-manage/format/formats-table

17. Documenting data: questions
What information do users need to understand the data?
- descriptions of all variables / fields and their values
- code labels, classification schema, abbreviations list
- information about the project and data creators
- tips on usage e.g. exceptions, quirks, questionable results
How will you capture this?
Are there standards you can use?

18. Dublin Core metadata example
Creator:Donald Cooper
Role=Photographer
Subject: Shakespeare, William, 1564-1616,
Antony and Cleopatra [LC]
Description:Vanessa Redgrave as Cleopatra
Date: 1973-08-09
Type:Image
Format:JPEG
Identifier:4150 [catalogue no]
Source: negative no 235
Relation: Antony and Cleopatra: Thompson/73-8
IsPartOf
Coverage:Bankside Globe
Role=Spatial
Rights:Donald Cooper
•http://www.ahds.ac.uk/performingarts

20. Storing data: questions
What is available to you?
What facilities do you need?
- remote access
- file sharing with colleagues
- high-levels of security
How will the data be backed up?

21. Storing data: advice
Speak to the Northampton IT Team for advice – TUNDRA2
Remember that all storage is fallible – need to back-up
- keep 2+ copies on different types of media in different locations
- manage back-ups (migrate media, test integrity)
Choose appropriate methods to transfer / share data
- email, dropbox, ftp, encrypted media, filestore, VREs...

22. Sharing data: questions
Does your funder expect you to share data?
Which data can be shared?
How will you share your data?
What do you get from sharing?
- citations, recognition...

23. Sharing data: advice
Where possible, make your data
available via repositories, data centres
and structured databases
•Northampton Electronic Collection of Theses and Research (NECTAR)
http://nectar.northampton.ac.uk/
•http://datacite.org/repolist •http://databib.org/

24. Preserving data: questions
Are you required to preserve (or destroy) your data?
How will you select what to keep?
Is there somewhere you can archive your data?
How can you support the reuse of your data?

25. Preserving data: advice
How to select and appraise research data:
www.dcc.ac.uk/resources/how-guides/appraise-select-research-
data
How to licence research data
www.dcc.ac.uk/resources/how-guides/license-research-data
How to cite datasets and link to publications
www.dcc.ac.uk/resources/how-guides/cite-datasets

26. Planning data management
What do you (and others) want to do with the data?
 your decisions should bear this in mind and make it feasible
Remember:
Data management is about making informed decisions
Talk to colleagues and support staff to see which option works best

27. Data Management and Sharing Plans
Funders typically want a short statement covering:
- What data will be created (format, types) and how?
- How will the data be documented and described?
- How will you manage ethics and Intellectual Property?
- What are the plans for data sharing and access?
- What is the strategy for long-term preservation?
DMP tool: https://dmponline.dcc.ac.uk/
How to write a DMP:
www.dcc.ac.uk/resources/how-guides/develop-data-plan

28. Thanks - any questions?
Acknowledgements:
Thanks to DCC staff, UK Data Archive and Research360 for slides