- Citizen science involves collecting data about biodiversity and the environment through contributions from the public.
- The Competence Center aims to provide solutions by linking citizen science data with scientific models to improve predictions and inform decisions.
- Current initiatives include Natusfera, a citizen science platform for biodiversity observations in Spain, and CINDA, a framework and mobile app for collecting multiple types of citizen science data.
- Future areas of focus are linking citizen science platforms with automated species identification and integrating biodiversity and environmental observations to build better predictive models.
2. Summary
• The conceptual framework
– the question
– the data
– the role of citizen science
– CC as solution provider
• Current strategy and
developments
– Natusfera
– Caffe
– Cinda
• Future action lines
4. The question
Cimate change and biodiversity crisis
"Countries can not make decisions about
the major environmental problems that
affect us, both those related to climate as
the natural capital itself without the
essential support of the best scientific
knowledge available“
Ana Luisa Guzmán,
Ejecutive Secretary, CONABIO, México
Fires, erosion, coccolithophores and CO2
6. The best data for the best answers
• Biodiversity data suitable for analysis
offers a tremendous increase
in data available!
7. Citizen Science is not new
A directory of nature oriented associations in the region of Madrid (Spain)
http://www.madrid.org/cs/Satellite?cid=1142330062399&pagename=PortalJoven/Page/JUVE_contenidoFinal
…
12. Why branching out from iNaturalist?
(lessons learnt or to be learnt)
• Localisation: different languages
• “Projects of projects”, greater flexibility and
control for users (thinking of communities
rather than individuals)
• Customized data publication avenues for users
(instead of a monolithic approach)
• iNaturalist subscription model was
problematic to accept and to maintain
13. Data publication, data integration
http://www.gbif.org/dataset/50c9509d-
22c7-4a22-a47d-8c48425ef4a7
16. The challenges
• “if we build it, they will come” <-NO
– usable, useful, used
• How to get faster innovation that spreads
beyond people doing the innovation
• Integration
– open data
– connecting repositories
– standardization (OGC, TDWG)
– Metadata
17. Future action lines
– Linking CS Biodiversity observation platform(s)
and species identification based on automatic
image analysts
– Linking biodiversity and environmental
observations and information
18. Linking CS Biodiversity observation platform(s) and
species identification based on automatic image analysis
Observer/SC gets species ID
Instant satisfaction
Species distribution DB gets ID
DB quality
19. Linking biodiversity and environmental
observations and information
• shared infrastructure
• shared standards
• open data
• linked data
• species
occurence data
• environmental data
• Simultaneous recording of
biodiversity and environmental
conditions
• Improved models > improved
predictions > improved decisions
• Autonomous data
acquisition Integration
• Unified access
20. As a way of conclusion
• Integration has to go beyond ICT:
– ICT- Biology
– Science – Society
– …
• Tension projects vs infrastructures
• ·”So much to do so little time”
• Appreciate the opportunity: ICT is changing the
way biodiversity is studied, conserved and
managed…
… still struggling to get the right incentives in
place (cultural change)