Citizen science involves non-professional scientists volunteering to participate in scientific research projects, including data collection, analysis, and dissemination. The document discusses Extreme Citizen Science (ExCiteS), which aims to allow any community, regardless of literacy, to conduct bottom-up citizen science by collecting and analyzing data to address local issues. Examples are provided of ExCiteS projects involving air quality monitoring, community mapping, and enabling indigenous communities to report issues like poaching. Challenges addressed include ensuring data quality with low literacy, addressing cultural and ethical issues, and facilitating mutual learning between researchers and communities.

1. @UCL_ExCiteS
excites@ucl.ac.uk

2. Citizen Science
Volunteer rainfall observer Rick
Grocke checks the rain gauge at
Tanami Downs cattle station in the
Northern Territory of Australia
Audubon Cal.
Scientific activities in which non-
professional scientists volunteer
to participate in data collection,
analysis and dissemination of a
scientific project.
WMO–No. 919

3. Nursary
Community Centre
School
Scrap yard

4. Noise mapping
Mapping for Change

6. Dust Sampling

8. Public Laboratory for Open Technology and Science
Problem Classification Visualisation &
Data collection Action
definition & basic analysis analysis

9. PhD
Postgraduate
University/College
High School
Basic School

11. We need science and engineering
solutions to complex interrelated
issues
Increased demand
50% by 2030 (IEA)
Energy
Climate
Change
Food Water
Increased demand Increased demand
50% by 2030 30% by 2030
(FAO) (IFPRI)
Professor John Beddington
Chief Scientific Adviser to HM Government ,2009

14. ‘Extreme’ Citizen Science
‘Normal’ Citizen ‘Extreme’ Citizen
Science Science
Users Educated, usually with Everyone, regardless of
some domain level of literacy
knowledge
Locations Wealthy, populated and Everywhere
popular
Role Data collection and Problem definition,
entry analysis, use outcomes
Mode of work Crowdsourcing Collaborative and
participatory science

15. Participation in Citizen Science
• Collaborative Science – problem
Level 4 ‘Extreme’
definition, data collection and analysis
Level 3 ‘Participatory • Participation in problem definition
science’ and data collection
Level 2 ‘Distributed
• Citizens as basic interpreters
Intelligence’
Level 1
• Citizens as sensors
‘Crowdsourcing’

16. Extreme Citizen Science group
• Focus on ‘Extreme’ Citizen Science (ExCiteS) –
the theory, methodologies, techniques and
tools that will allow any community, regardless
of their literacy, to start bottom-up citizen
science activity, collect the data, analyse the
results and act on the outcomes .
• In addition, develop the ‘science of citizen
science’ – understanding data quality,
participation, engagement and contribution

17. Building an Air Quality Egg
Sensors in the Egg:
• MQ-7 for Carbon Monoxide
• DHT temperature
• humidity sensor
• Nitrous Dioxide sensor
inserted/welded onto an Arduino ProtoShield –
connected via LAN to feed data to COSM
Cindy Regalado, ExCiteS
Cindy Regalado, ExCiteS Cindy Regalado, ExCiteS

18. Science has no borders
Together with the Mildmay
Community Centre community
researchers from all over London
will be initiating Extreme Citizen
Science initiatives based on the
principles of Civic Science
(questioning the state of things) Cindy Regalado, ExCiteS
and taking a DIY approach
facilitated by the Public
Laboratory for Open Technology
& Science

19. Mapping for Change

21. June 2012

22. July 2012

23. August 2012

24. Forest monitoring
Jerome Lewis, ExCiteS

26. ExCiteS data collection platfrom
• Equip non-literate Pygmy hunter-gatherers with
portable data collection devices, to allow:
– collect information on illegal poaching
– capture points of resources or abuses
– capture audio stories or photos
– inform ecosystem managers
• Challenges: Literacy, GPS signal, Electricity,
Network coverage

27. Michalis Vitos, ExCiteS

28. Jerome Lewis, ExCiteS

29. Jerome Lewis, ExCiteS

31. Jerome Lewis, ExCiteS

32. Extreme Citizen Science
• Mutual learning – learning about the issues
together with the community
• How to ensure data quality, coverage?
• What kind of research can be done when
(functional) literacy is an issue?
• Ethical issues – informed consent, reuse of
data etc.
• Cultural issues – initiatory cycles, societal roles

33. Credits
Support for the research kindly provided by:
UCL Graduate School Research Fund,
ESRC ‘Conserving Biodiversity That Matters: The Value of Brownfield Sites’ project
RGS/IBG Small Research Grant
UrbanBuzz: Building Sustainable Communities (HEFCE)
London Sustainability Exchange (LSx)
London 21 Sustainability Network
EPSRC Challenging Engineering Award ‘Extreme Citizen Science’, ‘Challenging RISK’
EPSRC Adaptable Suburbs project
EU FP7 EveryAware, Citizen Cyberlab project
Google Research Awards
Amazon Web Services Education Grants
Special thanks to the participants and the communities that work with us
And our partners: Royal Geographical Society, ESRI, Helveta and U-Blox

34. • Follow us:
– http://www.ucl.ac.uk/excites
– Twitter: @UCL_ExCiteS
– Blog: http://uclexcites.wordpress.com