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.
Producing research data for use in future research
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