Virtual Research Environments supporting biodiversity research: Needs & priorities for Horizon 2020

Virtual Research Environments supporting biodiversity research

Needs & priorities for Horizon 2020

Vince SmithViBRANT Coordinator

Natural History Museum, [email protected]

ViBRANTVirtual Biodiversity

6-7th March 201310th e-Concertation Meeting, BrusselsTrack 4: Digital environments for collaboration

Virtual Biodiversity ResearchViBRANT

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

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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

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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”

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A modular, flexible VRE ArchitectureA 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

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A modular, flexible VRE ArchitectureA 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

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Data workflowsServices into and out of the VRE

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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)

PD

FH

TM

LX

ML

Citation, usage statistics, data aggregation and data/paper publishing

doi:10.3897/zookeys.50.539

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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

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2014-2020: Biodiversity data capture needs…

Contact: Vince Smith ([email protected])

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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

Virtual Research Environments supporting biodiversity research: Needs & priorities for Horizon 2020

Technology

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