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DataCite Summer Meeting 7-8 June 2010, Hannover. Towards Data Publishing Framework for primary biodiversity data. INFORMATION FACILITY. GLOBAL BIODIVERSITY. Dr Vishwas Chavan Senior Programme Officer for DIGIT vchavan@gbif.org. WWW.GBIF.ORG. Building the Biodiversity Informatics Commons.

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global biodiversity

DataCite Summer Meeting

7-8 June 2010, Hannover

Towards Data Publishing Framework for primary biodiversity data

INFORMATIONFACILITY

GLOBALBIODIVERSITY

Dr Vishwas Chavan

Senior Programme Officer for DIGIT

vchavan@gbif.org

WWW.GBIF.ORG

Building the Biodiversity Informatics Commons

gbif an intergovernmental initiative to share biodiversity information
GBIF: an intergovernmental initiative to share biodiversity information

Currently 54 countries; 44 International Organisations…

slide3

GBIF’s 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’

data shared online via gbif
Data shared online via GBIF

Data Publishers: 316

Data Resources: 9900

(>201m biodiversity records mapped to a 1 X 1 degree grid)

gbif global information infrastructure for biodiversity
GBIF, Global Information Infrastructure for Biodiversity
  • Global Infrastructure
  • Tools, Standards, and Processes
  • Strategies and Policy Framework
  • Outreach and Capacity Building
in summary gbif s informatics
In summary…GBIF’s Informatics

Improved access

to Names, Metadata

and Primary Biodiversity

Data

Distributed GBIF

informatics architecture

Faster and easier

publishing of data

slide9

Primary biodiversity data and information effectively available

Reports

Geography

Biological collections

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.

Observations

Scientific publications

Data Bases

Gray literature

slide10

Improving mobilisation and Cultural Changes

  • Broadening Data Types
  • Data Resources Discovery
  • Innovative Approaches to Data Mobilisation
  • Data Mobilisation Strategy Discussions
  • Data Publishing Framework
why should i publish data
Why should I publish data?
  • Recognition
  • Opportunities
  • Investment

What is there for me?

data publishing framework
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
slide13

Components of

Data Publishing FRAMEWORK

Chavan and Ingwersen (2009) ,

BMC Bioinformatics, 10 (Suppl. 14): S2

dpf core technical components
DPF: Core Technical Components

Chavan and Ingwersen (2009) , BMC Bioinformatics, 10 (Suppl. 14): S2

slide15

Data Publication together with scholarly publication: ZooKeys experience

Occurrence Data

KML file

Penev, et.al. (2009). ZooKeys, 11: 1-8.

slide16

Current Biology

PhytoKeys

Indian J. Mar. Sci.

Data Paper:

Recognising

Data Discovery

DoI

Publication

Journal

System

Acceptance

GBRDS

Revision

Peer Review

GBIF Metadata

Repository

Submission

Registry

auto conversion to manuscript

Distributed

Metadata

Catalogues

Persistent

Identifiers

Metadata

Authors

data citation mechanism service
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
data usage index dui why
To demonstrate to data publishers that their biodiversity efforts do have impactData Usage Index (DUI): Why?
  • 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
data usage index dui what is it
GBIF Indicators

As set of indicators operating ondata 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)

Data Usage Index (DUI): What is it?
slide20

Phase III

Local

DUIs

Publishing

Toolkit

Publishing

Toolkit

LDUI

LDUI

LDUI

Aggregator

Aggregator

NDUI

NDUI

UNIVERSAL DUI

Aggregator

Phase II

Natl.,

Regional,

Thematic

DUIs

Aggregator

TDUI

TDUI

RDUI

Data Flow type

Digitisation

Bottom – Top

Top – Bottom

Aggregator

Aggregator

Mirror

Mirror

Publishing

Toolkit

GDUI

GDUI

Phase I

Publishing

Toolkit

Global

DUIs

GDUI

Implementation of DUI

slide21

Improving the relevance of Data Usage Index

Data Life Cycle

Management

Access

Use

Data set citation

LDUL

Indicator Robustness

Time Series Logs

Data Usage Index (DUI)

Local DUI

TDUL, NDUL

Global DUI

GDUL

Phase I

Phase II

Phase III

Data Usage Index (DUI) implementation

dpf challenges
DPF: Challenges
  • Individual Researcher
  • Scientific and Academic Institutions
  • Funding and Donor Agencies
  • Traditional Publishing Industry

Cultural &

Social Acceptance

Policy & Political Uptake

Chavan and Ingwersen (2009) , BMC Bioinformatics, 10 (Suppl. 14): S2

impact of data publishing framework
Impact of Data Publishing Framework

Funding Agencies

encourages

support

Project

Inspires another

results in

Knowledge

Dissemination

Data

Management,

& Archival

leads to

results in

requires

facilitate

facilitate

Incentivisation

through

Data Paper

Metadata

Scholarly

Publishing

Data Creation,

Collection

Data

Discovery

Improves data quality

and fitness

leads to

provide feedback on gaps

and strategies for

Data

Publishing

leads to

Increased

Data Usage

facilitate

results in

leads to

results in

Data Usage Index

Existing cycle

Analysis,

Interpretation

Complementary Expected cycle

Impact Factor

Source: BMC Bioinformatics 2009, 10(Suppl 14):S2, doi:10.1186/1471-2105-10-S14-S2

primary data and scholarly publications
Primary Data and Scholarly Publications
  • Seamless, embedded interconnections between data & paper
  • Unconventional use of data
  • Improving reliability & credibility