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GLOBAL BIODIVERSITY INFORMATION FACILITY Dr Vishwas Chavan Senior Programme Officer for DIGIT Towards Data Publishing Framework.

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Presentation on theme: "GLOBAL BIODIVERSITY INFORMATION FACILITY Dr Vishwas Chavan Senior Programme Officer for DIGIT Towards Data Publishing Framework."— Presentation transcript:

1 GLOBAL BIODIVERSITY INFORMATION FACILITY Dr Vishwas Chavan Senior Programme Officer for DIGIT Towards Data Publishing Framework for primary biodiversity data Towards Data Publishing Framework for primary biodiversity data Building the Biodiversity Informatics Commons DataCite Summer Meeting 7-8 June 2010, Hannover

2 GBIF: an intergovernmental initiative to share biodiversity information Currently 54 countries; 44 International Organisations…

3 GBIFs Mandate To facilitate free and open access to biodiversity data worldwide, via the Internet, to underpin scientific research, conservation and sustainable development. GBIF is govt-initiated, and govt. funded, in response to government agency needs in biodiversity information access and management; GBIF is in service to science, as a global public good

4 Data shared online via GBIF (>201 m biodiversity records mapped to a 1 X 1 degree grid) Data Publishers: 316 Data Resources: 9900

5 GBIF facilitates access/exchange of data GBIF-mediated data on the India

6 GBIF, Global Information Infrastructure for Biodiversity l Global Infrastructure l Tools, Standards, and Processes l Strategies and Policy Framework l Outreach and Capacity Building

7 Global Biodiversity Research Infrastructure

8 In summary…GBIFs Informatics Improved access to Names, Metadata and Primary Biodiversity Data Distributed GBIF informatics architecture Faster and easier publishing of data

9 Primary biodiversity data and information effectively available Data and information that have been produced but are not easy to find, access, and use (i.e not effectively available!) - a gigantic task of mobilising billions of data is still needed, as well as integrating new data. Biological collections Scientific publications Observations Reports Gray literature Data Bases Geography

10 Improving mobilisation and Cultural Changes l Broadening Data Types l Data Resources Discovery l Innovative Approaches to Data Mobilisation l Data Mobilisation Strategy Discussions l Data Publishing Framework

11 What is there for me? Recognition Opportunities Investment Why should I publish data?

12 Data Publishing Framework Cultural change towards free and open access to biodiversity data Addresses social, technical, and policy concerns Answer What is there for me? for ALL

13 Infrastructure and Technical Policy and Political Socio- Cultural EconomicLegal Chavan and Ingwersen (2009), BMC Bioinformatics, 10 (Suppl. 14): S2

14 DPF: Core Technical Components Persistent Identifiers Data Usage Index Data Citation Mechanisms Chavan and Ingwersen (2009), BMC Bioinformatics, 10 (Suppl. 14): S2

15 Occurrence Data KML file Data Publication together with scholarly publication: ZooKeys experience Penev, et.al. (2009). ZooKeys, 11: 1-8.

16 Persistent Identifiers Journal System Submission Acceptance Revision Peer Review Publication Registry GBRDS DoI Distributed Metadata Catalogues Metadata Authors auto conversion to manuscript GBIF Metadata Repository Current Biology PhytoKeys Indian J. Mar. Sci. Data Paper: Recognising Data Discovery

17 Data Citation Mechanism & Service Deep data citation mechanism Recognise ALL with their roles Multilayer citation – producer, publisher, aggregator Citations within citations Data Citation Service Resolve citation any time Discover the underlined data Under development

18 Data Usage Index (DUI): Why? l 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

19 GBIF Indicators19 Data Usage Index (DUI): What is it? l As set of indicators operating on data concerned with: l Unique Visits l Loyal Visits (repeated visits by same IP address) l Download of datasets & dataset records l Volume and (rank) distributions of dataset records per visit, visitor, dataset provider (institution, country, region, world, theme) & period l 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

20 Phase I Phase II Phase III Data Flow type Digitisation Bottom – Top Top – Bottom Global DUIs Natl., Regional, Thematic DUIs Local DUIs UNIVERSAL DUI Mirror GDUI Aggregator RDUI TDUI Aggregator NDUI LDUI Publishing Toolkit Publishing Toolkit Publishing Toolkit Publishing Toolkit LDUI Implementation of DUI

21 Data Usage Index (DUI) implementation Time Series Logs Indicator Robustness Data Usage Index (DUI) Phase IPhase IIIPhase II Global DUI Local DUI Data set citation GDUL TDUL, NDUL LDUL AccessUseManagement Data Life Cycle Improving the relevance of Data Usage Index

22 DPF: Challenges Persistent Identifiers Data Usage Index Data Citation Mechanisms Chavan and Ingwersen (2009), BMC Bioinformatics, 10 (Suppl. 14): S2 Policy & Political Uptake Cultural & Social Acceptance Individual Researcher Scientific and Academic Institutions Funding and Donor Agencies Traditional Publishing Industry

23 Funding Agencies Project Data Creation, Collection Analysis, Interpretation Scholarly Publishing Data Management, & Archival Data Publishing Increased Data Usage Knowledge Dissemination support results in Inspires another results in requires provide feedback on gaps and strategies for leads to Metadata facilitate results in Improves data quality and fitness facilitate encourages Existing cycle Complementary Expected cycle Impact Factor Data Usage Index Data Discovery Incentivisation through Data Paper leads to results in Source: BMC Bioinformatics 2009, 10(Suppl 14):S2, doi: / S14-S2 Impact of Data Publishing Framework

24 Primary Data and Scholarly Publications l Seamless, embedded interconnections between data & paper Unconventional use of data Improving reliability & credibility

25 Data Publishing together with Scholarly Publishing!


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