Presentation that outlines the reasons that researchers should consider data re-use and practical steps that may be taken. Presented by Gareth Knight at the Data Management in Practice workshop on Data Re-use on Nov 14th 2013.

1. Producing research data
for use
in future research
Data Management in Practice
14 November 2013
This work is licensed under a
Creative Commons Attribution 2.0 UK:
England & Wales License

2. Data Use in original context
Research outputs
Develop
Proposal
Complete
project
Start Project
Research papers & reports
Write-up
results
Perform
Research
•Collect/create data
•Process (normalise, harmonise)
•Anonymise
•Analyse
Research Data

3. Data Reuse Scenarios
1. Verify research findings
• 3rd party attempt to reproduce findings
• Data analysed for errors & assumptions. Does the data
confirm conclusions? Have appropriate analysis techniques
been applied?
2. Support new Research
• Analyse in combination with other secondary datasets
• Apply new and alternative analysis techniques
• Piwowar & Vision study (2013) shows increase in no. of
datasets analysed between 2001 - 2010
3. Teaching resource
• Case study in learning & teaching environment
• Students analyse real-world dataset within
research project

4. Data Re-use Incentives
Save time & money
Avoid research duplication
Higher Research Impact
• Greater research credibility
• Papers with associated data receive
higher citation (9%) in comparison to
those that do not, in study of 10,555
gene expression papers (Piwowar &
Vision, 2013)
http://www.clker.com/clipart-256100.html
http://upmic.wordpress.com/2013/06/10/negative-data/

5. Enabling Data Re-Use
1. Ensure appropriate permissions have been provided
• Informed consent from participants
• Clarify ownership rights of project partners
• Record rights information in documentation & assign licence
2. Ensure data can be understood
• Create documentation necessary to understand, evaluate, replicate & build upon
work without author support
• Test documentation with other data users and identify questions
3. Ensure data can be accessed and analysed
• Store data in format supported by wide-range of software
• Ensure data can be analysed and manipulated using different method
4. Ensure infrastructure exists to control access and use
• Investigate options for enabling access and re-use in controlled manner

6. References
•
•
Piwowar H, Vision TJ. (2013) Data reuse and the open data citation advantage. PeerJ PrePrints 1:e1v1
https://peerj.com/articles/175/
Craig, et al, (2007) Do open access articles have greater citation impact? A critical review of the
literature. Journal of Informetrics 1 (3) 239- 3 248 http://dx.doi.org/10.1016/j.joi.2007.04.001
•
UK Data Service: Formatting Data http://ukdataservice.ac.uk/manage-data/format.aspx
•
Information Commissioner Office. Data Sharing Code of Practice
http://www.ico.org.uk/for_organisations/data_protection/topic_guides/data_sharing
•
MANTRA – Data Management training for PhD students
http://datalib.edina.ac.uk/mantra/
•
UK Data Archive – Managing and Sharing Data
http://www.data-archive.ac.uk/media/2894/managingsharing.pdf
•
LSHTM Information Management support material
http://intra.lshtm.ac.uk/infoman/
•
Guidelines on good research practice: Implementing research governance:
http://www.lshtm.ac.uk/research/ethicscommittees/good_research_practice.pdf