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Dryad UK discussion meeting Mark Patterson, Director of Publishing April 27, 2010

Committed to making the world’s scientific and medical literature a public resource. Dryad UK discussion meeting Mark Patterson, Director of Publishing April 27, 2010. Why share data?. Complete picture of the work Reliability of the conclusions/recommendations

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Dryad UK discussion meeting Mark Patterson, Director of Publishing April 27, 2010

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  1. Committed to making the world’s scientific and medical literature a public resource Dryad UK discussion meeting Mark Patterson, Director of Publishing April 27, 2010

  2. Why share data? • Complete picture of the work • Reliability of the conclusions/recommendations • Developing alternative interpretations • Reusing the data for new analyses • Data may be unique/precious • Human participants deserve it • Whilst preserving confidentiality

  3. Consequences of not sharing data • Misunderstanding • Uncorrected errors • Misrepresentation • Duplication of effort • Limits research impact

  4. ..at least 70 structures demonstrated to be falsified… …the current problems could not have been easily discovered without the availability of the structure-factor files

  5. …the full data must be accessible for scrutiny by the scientific community.

  6. Barriers to (effective) data sharing • Technical barriers • Lack of infrastructure (database) • Lack of standards (formats) • Too much data • Administrative and legal barriers • Lack of clarity of reuse terms • Lots of files to organize and process • Publishers don’t make it easy enough • Cultural barriers • Sharing is not the norm • Insufficient incentives • Maximizing credit via publication encourages hoarding of data

  7. The role of publishers • Policy requiring data sharing as a condition of publication • Quality control of data • Providing incentives to share data

  8. Challenges to policy development • Discipline-specific differences • Data sharing tradition/behaviour • Availability of an established database • Enforcing the right standards at the right time • Privacy/confidentiality issues • Technical issues • Quantity of data • CC Zero Waiver • Policing the policy • Making sure restrictions are clear before publication • Appropriate action after publication

  9. Quality control - image manipulation • Images screened for inappropriate manipulation • Most frequent problem is that original files cannot be found • Should all raw data be submitted?

  10. Incentives • Provide a forum for ‘data papers’ • Indicators for the impact of datasets • Make sure that datasets are properly cited

  11. PLoS Currents: Influenza Workflow Google Knol: Author(s) assemble content and control access and editing. Authors submit content to PLoS Currents. PLoS Currents: Moderators control posting of content, commenting and version control. PubMed Central: Immediate transfer from PLoS Currents site; stable identifier and permanent archiving.

  12. PLoS Currents Influenza • Very fast • Very cheap • Moderated by experts • Citable • Version control • Archived at PubMed Central • Indexed in PubMed

  13. http://www.plosone.org/enhanced/pone.0006975/

  14. http://www.plosone.org/enhanced/pone.0006975/

  15. (http://tiny.cc/ALM1)

  16. “Article-level metrics” could be applied to datasets in Dryad

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