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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

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

    • 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
      • Advances in new ICT technologies,
      • the data deluge, funding body
      • requirements have brought major
      • changes for life science researchers
      • The eight-month RIN-funded project
      • was carried out by a team of social
      • scientists and information service
      • specialists from ISSTI, DCC, and IS
      • at the University of Edinburgh.
      • Principal Investigators:
      • Professor Robin Williams
      • (ISSTI) and Graham Pryor (DCC).
      • The aim was to identify ‘how
      • information-related policy, strategy
      • and practice might be improved to
      • meet the needs of researchers’.
      CC image by Sean McGrath courtesy of Flickr – http://www.flickr.com/photos/mcgraths/3597037843/
    • 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)
    • 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/
      • Diversity of Cases:
      • Enormous range of information use and exchange (formal/informal, internal/external) across the research groups
      • Activities of individual members of research groups strongly influenced by their role, expertise and responsibility
      • There is much talk of ‘big science’, and our initial research design presumed that we would be studying large-scale formal collaborations.
      • We found most research groups in the life sciences operate on a relatively small scale.
    • 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/
    • CC image by Tuis courtesy of Flickr – http://www.flickr.com/photos/tuis_imaging/515380689/
      • Information patterns and behaviour:
      • Researchers discover and gain access to information mainly via direct access to web-based resources – little use of centralised services (e.g. library)
      • Google – the ultimate enabler often delivering serendipitous contextual information
      • Limited awareness of available services and resources but loyalty to those they like or trust
      • Researchers used informal and trusted sources of advice from colleagues, rather than institutional services to help them identify information sources & resources
    • CC image by Darwin Bell courtesy of Flickr – http://www.flickr.com/photos/darwinbell/300495624/
      • Researchers however were more ready to share methods and tools than experimental data
      • Immaterial to researcher whether they need to use an information portal, commercial website, publisher’s web service or bibliographic database – orientation is primarily pragmatic!
      • The use of Web 2.0 tools for scientific research purposes was far more limited than expected
      • Centralised training not specific enough for kinds of refined utilities being used
    • 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
    • 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  
      • Researchers have concerns about misuse of research data, ethical restraints and IPR
      • Some disciplines lend themselves more than others to ‘openly sharing’
      • Researchers retain a keen sense of ownership towards data which represents their ‘competitive
      • advantage’ and ‘intellectual capital’
      • Researchers felt that only they had the subject knowledge to curate their own data
      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
    • CC image by Myxi courtesy of Flickr – http://www.flickr.com/photos/myxi/4623192231/
      • Researchers’ perceptions of future challenges and needs:
      • Bioinformatics support (centralised, preferably local & easily accessible)
      • Standardisation (data can be highly variable, different forms and formats, specificity of software)
      • Data deluge and technical barriers (fear that there will be too much data to handle, process, even look at)
      • Support for development of data curation should not be at the expense of funding for research
      • Short term nature of funding may frustrate attempts to build & sustain data repositories
    • CC image by cyberdees courtesy of Flickr – http://www.flickr.com/photos/cyberdees/3760447610/
      • Challenges and conclusions:
      • 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)
      • Development of research data curation skills and training to cater for diversity of research output and practice as viable career option
      • Institutional information service need to develop intuitive tool-based support for practitioners to assist in the curation of their own data
      • 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
    • 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