Presented at the 10th e-Concertation Meeting in Track 4 (Digital environments for collaboration), Brussels, Belgium 6-7 March 2013.

1. Virtual Research Environments
supporting biodiversity research
Needs & priorities for Horizon 2020
Vince Smith
ViBRANT Coordinator
Natural History Museum, London
vince@vsmith.info
ViBRANT
Virtual Biodiversity
6-7th March 2013
10th e-Concertation Meeting, Brussels
Track 4: Digital environments for collaboration

2. Virtual Biodiversity Research
ViBRANT
The problem
Science is global
• It needs global standards
• Global workflows
• Cooperation of global players
Science is carried out “locally”
• By local scientists
• Being part of local infrastructures
• Having local funders
2 of 10

3. Virtual Biodiversity Research
ViBRANT
The problem applied to biodiversity science
• Inventory the Earth’s species
• Document their relationships
• “Publish” & apply these data
Goal…
• 1.8 M described spp. (10M names)
• 300M pages (over last 250 years)
• 1.5-3B specimens
Data set…
People…
• 4-6,000 scientists
• 30-40,000 “pro-amateurs”
• Many more citizen scientists?
Linking grand challenges to local research activities
3 of 10

4. Virtual Biodiversity Research
ViBRANT
Linking “local” to “global” problems
537 Scratchpads Communities
by 7,291 active registered users
covering 18,790 taxa
in 511,192 pages
• Hosted VRE (Scratchpads) for biodiversity
• Ecosystem of user communities
• Communities self-assemble
• We CANNOT predict their research questions
• We CAN predict their data & service needs
• Support data management & workflows
User engagement though a VRE
“Success defined
through engagement”
4 of 10

5. Virtual Biodiversity Research
ViBRANT
A modular, flexible VRE Architecture
A cloud of niche services plugged into a core VRE
Service based Virtual
Research Environment
Core/Pluggable servicesExternal service
External service External service
External service
External service
5 of 10

6. Virtual Biodiversity Research
ViBRANT
A modular, flexible VRE Architecture
A cloud of niche services plugged into a core VRE
Service based Virtual
Research Environment
Data
publishing
Data
modelling
Phylogenetic
analysis
Citizen
science
Species
Identification
Research Support
• Data management
• Visualisation
• Workflows
Management Support
• Communication
• Task assignment
• Planning
6 of 10

7. Virtual Biodiversity Research
ViBRANT
Data workflows
Services into and out of the VRE
7 of 10

8. Virtual Biodiversity Research
ViBRANT
Incentives to encourage uptake & use
Data paper assembled from
Scratchpad database
XML submission, peer review &
marked-up publication by Pensoft
5-step workflow for selecting data,
adding metadata & previewing
New Biodiversity Data Journal
(worldwide coverage)
PDFHTMLXML
Citation, usage statistics, data aggregation and data/paper publishing
doi:10.3897/zookeys.50.539
8 of 10

9. Virtual Biodiversity Research
ViBRANT
Challenges to VRE activities in H2020…
Generic VRE issues to address:
• Sustaining & enhancing VRE core
activities
• Trusting external services
• Persistence of data & services
• Effective embedding and training of
user community
• Agile development to meet
changing user needs
• Delivering immediate user benefits
• Success defined through usage
(not always cutting edge, must be
useful, simple & easy to use)
• Interoperability, not just about data
standards
• Global use and benefits (not just
within the EU)
Data management themes:
• Integration with long term data
repositories
• Persistent identification & data citation
• Open access, data publishing & Open
Science
• Data and metadata standards,
controlled vocabularies
• Automated data extraction from text
and other resources
• Automated processing to link related
data (including Linked Open Data)
• Crowd-sourcing expertise
• Mobile technologies to enable early
data capture
• Capacity building to expand data
capture
9 of 10

10. Virtual Biodiversity Research
ViBRANT
2014-2020: Biodiversity data capture needs…
Contact: Vince Smith (vince@vsmith.info)
10 of 10
Aspect of biodiversity Type of data Capabilities
Landscape/ecosystem Imagery Satellites, Drones, LIDAR
Species distribution
(including community
composition)
Point observation Specimens, Survey/monitoring, Citizen science, Camera
traps, Acoustic monitoring, Ecogenomics, Satellite/drone
imagery, Literature, Traditional Knowledge, Regional
species lists, Image recognition
Species abundance Shape files Expert judgement, Niche modelling, Models including
interactions
Measurement Survey/monitoring, Citizen science, Ecogenomics,
Satellite/drone imagery, Literature, Traditional Knowledge
Species Traits and
functions
Specimens, Literature, Genomics, Traditional Knowledge,
Crowd- sourced data
Identification Specimens, Literature, Barcode sequences, Diagnostic
keys, Crowd- sourced expertise
Interactions Specimens, Text-mined Literature, Genomics, Traditional
Knowledge, Crowd-sourced data, Isotopes
Phenology Specimens, Literature, Genomics, Diagnostic keys,
Traditional Knowledge, Crowd-sourced data
Threat status Red list, Statutory authorities, Automated change
detection