Producing research data for use in future research

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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.

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Producing research data for use in future research

  1. 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. 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. 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. 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. 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. 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

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