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What does Open Science, Open Scholarship look like?

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What does Open Science, Open Scholarship look like?

  1. 1. Open@ed [Research] What does Open Science, Open Scholarship look like? Robin Rice, Data Librarian EDINA and Data Library, IS Edinburgh: 9 March 2015
  2. 2. Open Science, Open Scholarship • Open Access & Data Sharing  • Code Sharing & Reproducible Research  • Networking & Citizen Science
  3. 3. Open Access & Data Sharing Data sharing policies Publicly Funded Research Should Be Made Publicly Available. - OECD declaration, 2007 - Followed by research funders - Then by institutions
  4. 4. Open Access & Data Sharing Open Access publications becoming norm • Monographs still the exception – (Pressure on Humanities?) • Institutional support for Green and Gold OA • Preprints & embargoes help speed up dissemination • Publishing not yet “Beyond the PDF”
  5. 5. Open Access & Data Sharing What’s different about data (sharing) ? • A researcher’s working capital • ‘Ownership’, rights problematic • Curation required for re-use • Citation non-standard • Career rewards uncertain
  6. 6. Open Access & Data Sharing Benefits of data sharing • More eyeballs (scrutiny) on your work • Publish for posterity • Deposit for safekeeping • Sharing goes both ways
  7. 7. Codesharing and Reproducible Research 3 R’s of sharing • Re-use • Replication (independent verification of findings) • Reproducibility (analysis can be repeated using same code & data)
  8. 8. Networking and Citizen Science Benefits of citizen science • Public engagement • Crowdfunding • Data gathering, cleaning • Citizen scientists (informed citizenry)
  9. 9. Science 2.0 = Open Science • EC consultation on ‘Science 2.0’- Sep ‘14 • Social media for scientists & scholars • Working transparently: “This is what I’m working on,” getting early feedback • eg MyExperiment, Seek4Science Networking & Citizen Science
  10. 10. Why do Open Science? Alice Williamson - Chemistry Department, University of Sydney (statement for the OpenAIRE Conference 2012) https://vimeo.com/53506533

Editor's Notes

  • “Publicly funded research data are a public good, produced in the public interest, which should be made openly available with as few restrictions as possible in a timely and responsible manner that does not harm intellectual property.”
    RCUK Common Principles on Data Policy
    http://www.rcuk.ac.uk/research/datapolicy/
  • “Reproducibility is particularly important in large computational studies where the data analysis can often play an outsized role in supporting the ultimate conclusions.”
    Quote by Roger Peng, blog post Simply Stats, 6 June 2014, http://simplystatistics.org/2014/06/06/the-real-reason-reproducible-research-is-important/
     
  • EC: ‘Science 2.0’ describes the on-going evolution in the modus operandi of doing research and organising science. These changes in the dynamics of science and research are enabled by digital technologies and driven by the globalisation of the scientific community, as well as the need to address the Grand Challenges of our times. They have an impact on the entire research cycle, from the inception of research to its publication, as well as on the way in which this cycle is organised.

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