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Ebiosphere09 Vc Final


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This presentation was made at eBiosphere 09 conference in London during June 1-3, 2009.

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Ebiosphere09 Vc Final

  1. 1. Data Publishing = Scholarly Publishing ? Vishwas Chavan Global Biodiversity Information Facility Secretariat, Copenhagen, DENMARK
  2. 2. Significance of Biodiversity Data Policy development and decision making (at local, national, regional, and global levels) Biodiversity Data Monitoring of status Conservation and trends of and sustainable biodiversity use of (sound science) biodiversity Chavan, June 2009
  3. 3. It is all about…… Data Data Data Data Data Data Data Data Content Data Content Content Data Data Content Data Data Content Content Content Data Content Data Content Content Data Data Content Content Data Data Data Data Data Data Data Data Content Data Data Content Data Data Data Chavan, June 2009
  4. 4. What is needed? • Data Digitisation, Management and Archiving • Data exchange / sharing • Digital Data Publishing • Free and Open Access • Data without barriers Chavan, June 2009
  5. 5. Why should I publish data? rm e? e re fo t is th Wha Chavan, June 2009
  6. 6. Why should I publish data? • Recognition rm e? re fo s• t he i Opportunities W h at • Investment Chavan, June 2009 Data Publishing Framework 6
  7. 7. Data Publishing Framework • Bring in cultural change towards ‘free and open access' to biodiversity data • Addresses social, technical, and policy concerns • Answer ‘What is there for me?’ needs of ALL Chavan, June 2009 Data Publishing Framework 7
  8. 8. Data Publication together with scholarly publication: ZooKeys experience Occurrence Data KML file Chavan, June 2009
  9. 9. DPF: Core Technical Components Chavan, June 2009
  10. 10. Data Usage Index (DUI): Why? • To demonstrate to data publishers that their biodiversity efforts do have impact • To encourage … – Increase of high quality data discovery and mobilisation – Further usage of biodiversity data and information in scientific work – Formal citation behavior in research papers of dataset – Standardisation of dataset information Chavan, June 2009
  11. 11. Data Usage Index (DUI): What is it? • As set of indicators operating on data concerned with: – Unique Visits – Loyal Visits (repeated visits by same IP address) – Download of datasets & dataset records – Volume and (rank) distributions of dataset records per visit, visitor, dataset provider (institution, country, region, world, theme) & period • Indicators to be normalised (by records or MB), relative (to world, theme) and weighted (according to provider profile of species/taxa/themes) Chavan, June 2009
  12. 12. Data Flow type Digitisation Bottom – Top Top – Bottom Publishing Publishing Publishing Publishing Toolkit Local Toolkit Toolkit LDUI DUIs Toolkit LDUI LDUI Aggregator Aggregator Aggregator UNIVERSAL DUI NDUI NDUI Natl., Regional, Aggregator Aggregator Thematic Aggregator DUIs TDUI TDUI RDUI GDUI GDUI Mirror Mirror Global GDUI DUIs Chavan, June 2009 Implementation of DUI
  13. 13. Improving the relevance of Data Usage Index Data Life Cycle Management Access Use DUI) e x( I nd e ag Us ta Da Phase I Phase II Phase III Data Usage Index (DUI) implementation Chavan, June 2009
  14. 14. DPF: Challenges Policy and Political Uptake • Individual Researchers • Scientific and Academic Institutions • Funding and Donor Agencies • Traditional Publishing Industry Chavan, June 2009 GBIF Indicators
  15. 15. DPF: Challenges Cultural and Social Acceptance Policy and Political Uptake Chavan, June 2009
  16. 16. Impact of Data Publishing Framework Funding Agencies es ag support ur co en Project res u Inspires another lts in Knowledge Dissemination fac Data ilit • Impact Factor for Scholarly Publishingires ate requ Management, e at te lit ita ci & Archival cil Data fa fa Publishing it y Scholarly Data Creation, al qu ss ata Publishing Collection • Data Usage Index for Digital Data Publishing ne d fit es fa gaps d ov ci n lit ck o an p r edba or at Im e ide f e sf prov trategie Increased and s Data Usage results in re su to l ts in s ad le Data Usage Index Existing cycle Analysis, Complementary Expected cycle Impact Factor Interpretation Chavan, June 2009 GBIF Indicators 16
  17. 17. Data Publishing = Scholarly Publishing ? Email: