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RIN Disciplinary Case Studies: understanding the information needs of life science researchers
RIN Disciplinary Case Studies: understanding the information needs of life science researchers
RIN Disciplinary Case Studies: understanding the information needs of life science researchers
RIN Disciplinary Case Studies: understanding the information needs of life science researchers
RIN Disciplinary Case Studies: understanding the information needs of life science researchers
RIN Disciplinary Case Studies: understanding the information needs of life science researchers
RIN Disciplinary Case Studies: understanding the information needs of life science researchers
RIN Disciplinary Case Studies: understanding the information needs of life science researchers
RIN Disciplinary Case Studies: understanding the information needs of life science researchers
RIN Disciplinary Case Studies: understanding the information needs of life science researchers
RIN Disciplinary Case Studies: understanding the information needs of life science researchers
RIN Disciplinary Case Studies: understanding the information needs of life science researchers
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RIN Disciplinary Case Studies: understanding the information needs of life science researchers

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Presentation given by Stuart Macdonald at the IASSIST 2010 Conference, Cornell University, Ithaca, New York. 1 - 4 June 2010.

Presentation given by Stuart Macdonald at the IASSIST 2010 Conference, Cornell University, Ithaca, New York. 1 - 4 June 2010.

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  • 1. CC image by ecstaticist courtesy of Flickr – http://www.flickr.com/photos/ecstaticist/1337749333/ RIN Disciplinary Case Studies: understanding the information needs of life science researchers Stuart Macdonald Researcher EDINA & Data Library University of Edinburgh [email_address] IASSIST 2010, Cornell University, 2 June 2010
  • 2. <ul><li>Advances in new ICT technologies, </li></ul><ul><li>the data deluge, funding body </li></ul><ul><li>requirements have brought major </li></ul><ul><li>changes for life science researchers </li></ul><ul><li>The eight-month RIN-funded project </li></ul><ul><li>was carried out by a team of social </li></ul><ul><li>scientists and information service </li></ul><ul><li>specialists from ISSTI, DCC, and IS </li></ul><ul><li>at the University of Edinburgh. </li></ul><ul><li>Principal Investigators: </li></ul><ul><li>Professor Robin Williams </li></ul><ul><li>(ISSTI) and Graham Pryor (DCC). </li></ul><ul><li>The aim was to identify ‘how </li></ul><ul><li>information-related policy, strategy </li></ul><ul><li>and practice might be improved to </li></ul><ul><li>meet the needs of researchers’. </li></ul>CC image by Sean McGrath courtesy of Flickr – http://www.flickr.com/photos/mcgraths/3597037843/
  • 3. CC image by Hurley Gurley courtesy of Flickr – http://www.flickr.com/photos/hurleygurley/5134027/ Seven case studies were conducted across a diverse range of laboratories and research groups from botany to clinical neuroscience. Deployed a range of quantitative methods and tools designed to ‘enhance understanding of how researchers locate, evaluate, organise, manage, transform and communicate information sources as an integrated part of the research process’. 5-day information diaries (x55) F-2-F interviews, (x24) Cognitive mapping (1 per case) Focus groups (1 per case)
  • 4. CC image by Ecstaticist courtesy of Flickr – http://www.flickr.com/photos/ecstaticist/321582062/ CC images by Elephantik courtesy of Flickr – http://www.flickr.com/photos/joemaguiredesign/2300745142/ <ul><li>Diversity of Cases: </li></ul><ul><li>Enormous range of information use and exchange (formal/informal, internal/external) across the research groups </li></ul><ul><li>Activities of individual members of research groups strongly influenced by their role, expertise and responsibility </li></ul><ul><li>There is much talk of ‘big science’, and our initial research design presumed that we would be studying large-scale formal collaborations. </li></ul><ul><li>We found most research groups in the life sciences operate on a relatively small scale. </li></ul>
  • 5. Cognitive Maps Adapted from a lifecycle model developed by C. Humphrey (2006) different colours represent different types of activity within an information cycle. CC image by philippeleroyer courtesy of Flickr – http://www.flickr.com/photos/philippeleroyer/3944665610/
  • 6. CC image by Tuis courtesy of Flickr – http://www.flickr.com/photos/tuis_imaging/515380689/ <ul><li>Information patterns and behaviour: </li></ul><ul><li>Researchers discover and gain access to information mainly via direct access to web-based resources – little use of centralised services (e.g. library) </li></ul><ul><li>Google – the ultimate enabler often delivering serendipitous contextual information </li></ul><ul><li>Limited awareness of available services and resources but loyalty to those they like or trust </li></ul><ul><li>Researchers used informal and trusted sources of advice from colleagues, rather than institutional services to help them identify information sources & resources </li></ul>
  • 7. CC image by Darwin Bell courtesy of Flickr – http://www.flickr.com/photos/darwinbell/300495624/ <ul><li>Researchers however were more ready to share methods and tools than experimental data </li></ul><ul><li>Immaterial to researcher whether they need to use an information portal, commercial website, publisher’s web service or bibliographic database – orientation is primarily pragmatic! </li></ul><ul><li>The use of Web 2.0 tools for scientific research purposes was far more limited than expected </li></ul><ul><li>Centralised training not specific enough for kinds of refined utilities being used </li></ul>
  • 8. CC image by CaptPiper courtesy of Flickr – http://www.flickr.com/photos/piper/22584430/ ‘ Impressionistic’ taxonomy of case study research data Some form of taxonomic ordering is needed to facilitate a comparative analysis of the diversity of our cases Our findings proposed a simple two-by-two matrix along two dimensions: • Volume of data being handled • Complexity or heterogeneity of that data
  • 9. CC images courtesy of Flickr – http://www.flickr.com/photos/11304375@N07/2326596014/ Credit: M. M. Alvarez, T. Shinbrot, F. J. Muzzio, Rutgers University, Center for Structured Organic Composites   <ul><li>Researchers have concerns about misuse of research data, ethical restraints and IPR </li></ul><ul><li>Some disciplines lend themselves more than others to ‘openly sharing’ </li></ul><ul><li>Researchers retain a keen sense of ownership towards data which represents their ‘competitive </li></ul><ul><li>advantage’ and ‘intellectual capital’ </li></ul><ul><li>Researchers felt that only they had the subject knowledge to curate their own data </li></ul>Research data sharing: sharing of complex data is more problematic than sharing of research results via publications which remains the primary vehicle for dissemination and reward
  • 10. CC image by Myxi courtesy of Flickr – http://www.flickr.com/photos/myxi/4623192231/ <ul><li>Researchers’ perceptions of future challenges and needs: </li></ul><ul><li>Bioinformatics support (centralised, preferably local & easily accessible) </li></ul><ul><li>Standardisation (data can be highly variable, different forms and formats, specificity of software) </li></ul><ul><li>Data deluge and technical barriers (fear that there will be too much data to handle, process, even look at) </li></ul><ul><li>Support for development of data curation should not be at the expense of funding for research </li></ul><ul><li>Short term nature of funding may frustrate attempts to build & sustain data repositories </li></ul>
  • 11. CC image by cyberdees courtesy of Flickr – http://www.flickr.com/photos/cyberdees/3760447610/ <ul><li>Challenges and conclusions: </li></ul><ul><li>Institutional information services need to develop services that are seen as beneficial to researchers and can add value to the research process (tools, advice, subject-specific documentation and training, infrastructure) </li></ul><ul><li>Development of research data curation skills and training to cater for diversity of research output and practice as viable career option </li></ul><ul><li>Institutional information service need to develop intuitive tool-based support for practitioners to assist in the curation of their own data </li></ul><ul><li>Research and funding councils, information service providers and institutions need to understand the practices of the research communities if policies and strategies are to be effective - A single approach to the future of life sciences or a one-size-fits-all information policy will not be productive or effective </li></ul>
  • 12. CC images by enggul courtesy of Flickr – http://www.flickr.com/photos/enggul/2361808668 / Thanking You! Acknowledgements: Dr. Wendy Marsden (ISSTI / Innogen) Ann Bruce (ISSTI / Innogen) The full report ‘Patterns of information use and exchange: case studies of researchers in the life sciences’ is available at: http://www.rin.ac.uk/case-studies . All images CC Attribution-NonCommercial 2.0 Generic or Attribution 2.0 Generic

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