2. Overview
1. Background – biodiversity data diversity
• An introduction to me (lice to data infrastructures)
• The problem (integrating biodiversity research)
2. Example tools to manage biodiversity data
• Scratchpads (a platform to manage data)
• Biodiversity Data Journal (incentives to work digitally)
• eMonocot (aggregating data across communities)
3. Big community challenges – three examples
• Social issues (openness)
• Data issues (mobilizing existing data)
• Synthetic issues (modeling data)
4. Next steps
• Toward an integrated view for H2020 (strategy)
4. Lice to data infrastructures (1997-2004)
Systematics (circa 1998)
- No high level keys
- Poor high level taxonomy
- Just one phylogeny
- Few living experts!
Circa 5,000 spp.
Mammals & birds
12,000 associations
15,000 potential hosts
6. The problem – integrating biodiversity research (2004>)
How to we join up these activities? How do we use this as a tool?
Species conservation & protected areas
Impacts of human development
Biodiversity & human health
Impacts of climate change
Food, farming & biofuels
Invasive alien species
What infrastructures do we need?
(technologies, tools, standards…)
What processes do we need?
(Modelling, workflows…)
What data do we need?
(Genes, localities…)
8. Scratchpads – a space for your data
• Hosted websites for
biodiversity data
• Virtual research
environments
• Completely open access
& open source
• Modular & flexible
• Running since 2007
• Making taxonomy
digital, open & linked
http://scratchpads.eu
9. Scratchpads– a space for your data
Taxa Projects Regions Societies
544Scratchpad Communities
by 6,644active registered users
covering 91,631taxa
in 535,317 pages.
81 paper citations in 2012
In total more than
1,300,000 visitors
http://scratchpads.eu
10. Biodiversity Data Journal – incentivising data publishing
• New, Open Access data journal
• Linked to Scratchpads via Publication
Module
• Supports the life cycle of a manuscript
• Writing, submission, review, publication
& dissemination, all in one place
• Structured, reusable, standardised data
• Launched in Sept 2013 with 24 articles
http://biodiversitydatajournal.com
11. Biodiversity Data Journal – easy manuscript assembly
Structured data
Review, Publish
, cite &
disseminate
EOL
Dryad
GBIF
Wiki Species-Id
PubMed
Plazi
Select, describ
e & annotate
data
Publication module
http://biodiversitydatajournal.com
12. eMonocot – aggregating data across communities
• Online resource for monocot
plants
• Collaboration between
Kew, Oxford University and
NHM
• Data to be open and usable
by other scientists
http://e-monocot.org
13. eMonocot – aggregating data across communities
• Linking monocot
communities
• Identification, checklist
& taxonomic data for:
- 275,000 taxa
- 8,300 images
- 15 identification keys
- 3 phylogenies
• A sustainable digital
portal
• A source of data for
analysis
http://e-monocot.org
14. 3. Example challenges
- Social issues (openness)
- Data issues (mobalising existing data)
- Synthetic issues (modelling)
15. Social challenges: openness
E. Archambault et. al., Proportion of Open Access Peer-Reviewed Papers at the
European and World Levels--2004-2011, June 2013, Science-Metrix Inc.
“One-half of all papers are now freely available
within a year or two of publication”
“A piece of data or content is open if anyone is free to use, reuse, and redistribute it -
subject, at most, to the requirement to attribute and/or share-alike.” http://opendefinition.org/
Many kinds of openness:
• Open Access
• Open Data
• Open Science
• Open Source
• Sharing data is a foundation
for our activities
• Normal practice in some
communities (molecular)
• Mandated by some funders
& governments
Need to continue to incentivise openness
16. Data challenges: mobilising existing data
Collections
• 1.5-3B specimens in collections worldwide
• Fragments efforts / need coordination
Biodiversity literature
• >300M pages, BHL scanned 41M to date
• Copyright post-1923 & article metadata
Informatics challenges
• Automation & annotation
• Storage & persistence
• Business models to sustain activity
Collections, literature & metadata
How can we quickly, efficiently and cost
effectively mobilise biological data at scale?
Bibliography of Life
(RefFinder & RefBank)
BHL
literature
NHM
Digitisation
17. Synthetic challenges: Modeling the biosphere
Conceptually has many potential uses
• Identifying trends
• Explaining patterns
• Making predictions
• Real time alerts
- when data contradicts current knowledge
• The ultimate policy tool
Major informatics challenges
• Technical very difficult (many years off)
• Needs effective prototypes & platforms
• Some first steps e.g. Local Ecological Footprint Tool
Nature 2013, doi:10.1038/493295a
Reasoning across large, linked biodiversity datasets
A clear, singular, long-term vision, which
biodiversity data can contribute too