CC image by ecstaticist courtesy of Flickr – flickr/photos/ecstaticist/1337749333/

1. RIN Disciplinary Case Studies: understanding the information needs of life science researchers Stuart Macdonald Researcher EDINA & Data Library University of Edinburgh stuart.macdonald@ed.ac.uk CC image by ecstaticist courtesy of Flickr – http://www.flickr.com/photos/ecstaticist/1337749333/ IASSIST 2010, Cornell University, 2 June 2010

2. 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/

3. 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 Hurley Gurley courtesy of Flickr – http://www.flickr.com/photos/hurleygurley/5134027/

4. 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 CC images by Elephantik courtesy of Flickr – http://www.flickr.com/photos/joemaguiredesign/2300745142/ • 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. CC image by Ecstaticist courtesy of Flickr – http://www.flickr.com/photos/ecstaticist/321582062/

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. 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 Tuis courtesy of Flickr – http://www.flickr.com/photos/tuis_imaging/515380689/

7. Immaterial to researcher whether they need to use an information portal, commercial website, publisher’s web service or bibliographic database – orientation is primarily pragmatic! • Centralised training not specific enough for kinds of refined utilities being used • The use of Web 2.0 tools for scientific research purposes was far more limited than expected • Researchers however were more ready to share methods and tools than experimental data CC image by Darwin Bell courtesy of Flickr – http://www.flickr.com/photos/darwinbell/300495624/

8. ‘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 CC image by CaptPiper courtesy of Flickr – http://www.flickr.com/photos/piper/22584430/ Our findings proposed a simple two-by-two matrix along two dimensions: • Volume of data being handled • Complexity or heterogeneity of that data

9. 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 • 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 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

10. 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 Myxi courtesy of Flickr – http://www.flickr.com/photos/myxi/4623192231/

11. 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 image by cyberdees courtesy of Flickr – http://www.flickr.com/photos/cyberdees/3760447610/

12. CC images by enggul courtesy of Flickr – http://www.flickr.com/photos/enggul/2361808668/ 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 . Thanking You! Acknowledgements: Dr. Wendy Marsden (ISSTI / Innogen) Ann Bruce (ISSTI / Innogen) All images CC Attribution-NonCommercial 2.0 Generic or Attribution 2.0 Generic