The Citclops project aims to use participatory environmental science to improve optical monitoring of seascapes. Citizens will collect water quality data using their smartphones and cameras. This data will be combined with satellite data through the GEOSS framework to better interpret seascapes. The goals are to redesign current monitoring and reveal new environmental details. By engaging citizens, the project hopes to make monitoring more affordable, widespread, and sustainable compared to traditional scientific methods alone.

1. Participatory environmental science
Luigi Ceccaroni, Barcelona Digital Technology Centre
Laia Subirats, Barcelona Digital Technology Centre
Jaume Piera, CSIC
Dick M.A. Schaap, MARIS

2. Citclops project’s challenges and expected final
outcomes
• Optical monitoring (color, transparency and fluorescence) – but
better
– Challenges:
• Use of optical monitoring to interpret seascapes
• Combination and interpretation of data collected by:
• A distributed group of people (Citclops’s participatory environmental science)
• Publicly available data:
– GEOSS
– Satellites
– Standard maps
• other sources (to be defined)
– Expected final outcomes:
• To re-design current monitoring
• To reveal aspects/details of the environment people can’t normally see

3. How Citclops is engaged with GEO and the
implementation of GEOSS
• Active working-group/task (WA-01) on Integrated Water
Information (incl. Floods and Droughts) within GEO and
GEOSS frameworks
– The WA-01-C4: Global Water Quality Products and Services
component identifies the following needs:
• “Monitoring water quality using remote sensing, in conjunction with
strategic in-situ sampling, is needed to determine the current status of
water quality conditions and to help anticipate, mitigate, and even
avoid future water catastrophes.”
• “Systematic investments in an inland and near-coastal water quality
information system are required.”
– The GEO Inland and Near-Coastal Water Quality Working Group
aims to develop international operational water quality
information systems based on Earth observation.
– It also requires support by dedicated in-situ sampling.

4. How Citclops is engaged with GEO and the
implementation of GEOSS
• Projects like Citclops bridge the gap between the local
sampling experience and satellite information.
• Making the connection between the citizen observatory
and satellite-based information will:
– Commit the users to the water quality field
– Give support to the innovation in space-based research and
services
• Citclops results and experience will be directly linked to
GEO:
– One of the partners (Hans van der Woerd from VU-VUmc
together with Gordon Campbell from ESA) directly involved in
the information component that will make the Earth-
observation products better accessible for the public and the
local managers.

5. Participatory environmental science
• Citizens as environmental data consumers
• Monitoring tackled by scientists or policy makers alone
• Expensive
• Hard to use technology
• Quantity, coverage?
• High quality
• Sustainable?
• Citizens as environmental data creators and consumers
• Monitoring tackled by scientists, policy makers and
citizens
• Low cost
• Easy to use technology
• Quantity, coverage?
• Quality?
• Sustainable

6. The convergence of two trends
• Commonplace objects understanding what we do with
them
–Thanks to the proliferation of cheap, powerful sensors

7. The convergence of two trends
• Our personal identities firmly connected to our profiles on
social networks

8. Interaction made “social”
• How to create peer pressure?
• Recycle and impress your (Facebook) friends, or don't recycle
and risk incurring their wrath
• Share your weight with your Twitter followers; it will help you to
stick to a diet
• Monitor the environment and impress your friends, or don't
monitor the environment and…???
• Like a videogame, with points for doing good?
• Why create peer pressure?
• We are not mere automatons who assist big data in asking
and answering questions. Well, we shouldn’t be…

9. The social-engineering context
• Social engineering disguised as product engineering
• From smart cars to smart sensors, "smart" as the shorthand for
transforming present-day social reality
• Smart technologies becoming more intrusive
• Risk of undermining our autonomy by supporting behaviors that
someone somewhere has deemed desirable:
• Smart forks informing us that we are eating too fast
• Smart toothbrushes urging us to spend more time brushing our teeth
• Smart sensors in our cars telling us we drive too fast
• Smartphones telling us which beach is better for us
• Devices giving us useful feedback
• But also sharing everything they know about our habits with
institutions whose interests may be different from our own

10. Different kinds of “smart”
• “Enhancing“: Devices leaving us in complete control of the
situation and seek to enhance our decision-making by
providing more information:
• An Internet-jacked kettle alerting us when the national power
grid is overloaded
• Not preventing us from boiling yet another cup of tea, but adding an
extra ethical dimension to that choice
• A grocery cart scanning the bar codes of products we put into it,
informing us of their nutritional benefits and country of origin
• Enhancing—rather than impoverishing—our autonomy
• An application to contribute to ocean-color research, coupling
color to the most important life form in the water, the
phytoplankton, and informing about the ocean’s health
• What’s in it for me? Education, pollution, sediments…
• Is it sustainable? Public, private, artists…

11. Different kinds of “smart”
• “Limiting“: Technologies making certain choices and
behaviors impossible; smart gadgets seeking to limit,
not to expand, what we can do:
• Facial recognition technologies confirming we are who we
say we are…
• We must resist attempts to universalize this logic:

12. Different kinds of “smart”
• “Limiting“: Technologies making certain choices and
behaviors impossible; smart gadgets seeking to limit,
not to expand, what we can do:
• Facial recognition technologies confirming we are who we
say we are…
• We must resist attempts to universalize this logic:

13. Different kinds of “smart”
• Is the BinCam “enhancing” or “limiting”?
• Not forced to recycle
• Appealing to our base instincts:
• Must earn gold bars and rewards!
• Must “compete” with others!
• Must win and impress friends!
• Not treating us as autonomous human beings, capable of
weighing the options by ourselves
• Allowing a recommendation system or Facebook or the
government to do our thinking for us
• What about crowdsourcing systems involving people on
holiday (scuba diving, on cruise, on the beach) in data
collection?

14. Applications

15. Applications
• Smartphones, water color and Forel-Ule
(images courtesy of Marcel Wernand, NIOZ)

16. Smart crowdsourcing
•Do application designers know precisely how we should behave, so
the only problem is finding the right incentive?
•A truly smart crowdsourcing system should make us reflect on our
environmental habits and contribute to conscious deliberation:
• Letting us benchmark our usual swimming waters against other
waters in our area, instead of trying to shame us with point
deductions and peer pressure
•The task of technology should not be to liberate us from problem-
solving.
•We need to enroll smart technology in helping us with problem-
solving.
•Maybe… in promoting problem solving with a monitoring twist

17. Smart crowdsourcing

18. Applications, applications
•Improvement of scuba-diving activities
•Ranking the best beaches
•Early-warning systems for HABs and bio-chemical hazards
•Monitoring swell and length of waves
•Water transparency via phone pictures and Secchi disc
•Retrieval of sensor measurements from low-cost moorings

19. From current monitoring to
"participatory environmental science"
•Monitoring and…
• Mobile devices as sensor platforms
• Georeferencing
• Education through citizens’ effective participation
• Community involvement
• Internet-distribution and social platforms to observe and
then share:
• Photos (ocean color, transparency)
• Oil spills
• Algal blooms
• Recommendation
• Decision support

20. Information acquisition

21. Information acquisition
Bull. Korean Chem. Soc. 2012, Vol. 33, No. 2

22. Information delivery

23. Information delivery

24. Information delivery

25. Information processing
•Standardization, interoperability
•GIS and satellite-data processing, integration and
interpretation
•Data-quality validation in real-time
• Taking into account position, orientation and weather
conditions
•Context-awareness
• Data provided in a more or less voluntary, active or conscious
way
• Metadata and context data: time, location, name, instrument
•Personalisation
• Location
• Social environment
• Profile and personal history

26. Acquisition, processing, delivery: a new way

27. Resources
•http://www.citclops.eu/
•http://www.coastwatch.org/
•http://creekwatch.researchlabs.ibm.com/
•http://mwater.co/
•http://www.wasserlebnis.de/
•http://www.ecy.wa.gov/programs/eap/fw_riv/rv_main.html
•http://projectbaseline.org
•http://crowd.cs.umass.edu/
•http://en.wikipedia.org/wiki/Citizen_science
•http://senseable.mit.edu/
•http://research.cens.ucla.edu/aquatic/
•http://www.secchidipin.org/
•http://www.earthobservations.org/geo_me_201211_geo9_ec.shtml
•http://www.nurp.noaa.gov/Spotlight/Observatory.htm
•http://marine.rutgers.edu/mrs/LEO/LEO15.html

28. Participatory environmental science
Luigi Ceccaroni, Barcelona Digital Technology Centre
Laia Subirats, Barcelona Digital Technology Centre
Jaume Piera, CSIC
Dick M.A. Schaap, MARIS