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Citizen Sensing




Jean-Paul de Vooght
Markets          Soft-Laws            State/Federal Laws




                           Top-Down

Economic Systems                                         Urban Systems

                          Biodiversity          Transportation
       Major Banks
                             Water                 Health
      Sovereign Debts
                          Soil Erosion             Energy


                         Ecosystemic Services

                           Bottom-Up




                        « Take Ownership »
“The technology
   community has
  set up interactive
   maps to help us
identify needs and
 target resources.”
/
             ast.org
http ://safec




                   http://sparkfun.com/
                                          Tohoku Earthquake
blackcloud.org
●   Multimodal sensor (light, temperature, noise,
    CO2, organic volatile compounds)
●   37 participants over a period of 35 days in
    the Bay Area and Greater Los Angeles
●   Gamified approach to learning about
    pollution




                                                           Other Projects




                                                    http://airqualityegg.wikispaces.com/
                                                                      http://aircasting.org/
Civic Applications
dontflush.me




                            Source : http://teachgreenbk.wordpress.com




                             3
                       NCB-01

http://dontflush.me/               Combined Sewage Overflows
La présentation de Jean-Paul de Vooght à la soirée Citoyens Capteurs de la Cantine du 9 novembre 2012
Taking Ownership in 3 Dimensions



Participative data gathering

Handling of high environmental signal variety

Understanding through systemic thinking
Urban Sensing : out of the woods
Sensors
                              ●   Located at the edge of the « smart » city
                                  architecture
                              ●   Combine soft sensing (using our 5 senses) with
                                  hard sensing (IoT/UbiComp)




                              ●   Complementarity of DIY (discovery) and traditional
                                  manufacturing (replication)
                              ●   Standards for identifiers, formats, semantics and
                                  protocols supporting participatory approaches
                              ●   Additional considerations :
                                  ●   Data ownership and terms of use (open data)
                                  ●   Sensor selection and calibration (trust)
                                  ●   Privacy and anonymity
DIY Counter by Tomorrow Lab
Crowdsourcing
Execution
●   Learn from : citizen science
    ●   Action, conservation, investigation, virtual, education
        (Crowston, Wiggins)
    ●   Protocol design and quality control (task granularity)
    ●   Motivation factors : collective, norm-oriented,
        identification, intrinsic, reward (Nov et al.)




●   Crowdmapping and disaster-relief
    ●   What relief teams want vs what volunteers report
    ●   Data provenance and veracity
    ●   Conciling TOS of popular services with agency
        regulations
    ●   Task coordination under heavy constraints
●
    Micro-tasking platforms (Amazon Mechanical
    Turk, Kaggle, etc.) turn to mechanism design
    to optimize participation, incentives and results
●   Symmetric governance structures with
    progression potential for participants
Complexity in the anthropocene
Simplified
Peak Oil
Example
                                                 Thinking In Systems
                                                                     ●   Put observations into context
                                                                     ●   Use conceptual models and create
                                                                         simulations
                                                                         ●   Recognize interconnections
                                                                         ●   Identify feedback and delays
                                                                         ●   Understand dynamic behavior
                                                                         ●   Differentiate flows and stocks
                                                                     ●   Open and Transdisciplinary
                                                                         approach with multiple roles :
                                                                         ●   Observers and collectors
                                                                         ●   Instrument makers
                                                                         ●   Data scientists
                                                                         ●   Domain and policy experts
                                                                     ●   Leverage modeling environments
                                                                         and visualization kits available (R,
                                                                         NetLogo, Insight Maker, d3, Tangle,
                                                                         OpenStreetMap, etc.)
                                                                     ●   Test alternative policies around a
                                                                         shared model of understanding

Source : de Castro Carranza   http://insightmaker.com/insight/2993
Modeling, Simulation and Discussion
     Hard Sensing                                                                                        Soft Sensing




                                                 Shared Understanding
            Filter    Change ?
                                                                                                       Multi-Scale Visualization

                            Repeatable Accross a Variety of                            Ecosystems




Instrumentation of Model                                                                                     Report Events and
  Variables Over Time            Rent-a-Sensor                                          Smartphone                Context
                                   and DIY                                             Feature Phone
 CO, CO2, O2, CH4, H2, NH3,                                                                                311-type events, ideas,
 C4H10, CH3CH2OH, C6H5H3,                                                                                 best practices addressing
  H2S, NO2, O3, VOC, Air
                                                                                                           elements in the shared
                                                                                                           model of understanding.
  Temperature, Humidity,
   Pressure, PIR, Noise,
    Magnetic Field, Soil                            Citizens Sensing
Temperature, open data, etc..
“Design a way to monitor the natural and industrial systems
  around you and make them knowable to you and your
                       colleagues.
                 Don’t try to do it alone.
                We are all designers now.”

                         John Thackara
                         In The Bubble




                          Jean-Paul de Vooght
                 http://citizensensing.posterous.com/
References
●   HOME, Arthus-Bertrand, https://www.youtube.com/movie?feature=plcp&v=jqxENMKaeCU
●   Urban sensing : out of the woods, Cuff et al., http://dl.acm.org/citation.cfm?id=1325562
●   Workshop at the 10th International Conference on Ubiquitous Computing,
    http://www.urban-atmospheres.net/Ubicomp2008/
●   Technology-Mediated Citizen Science Participation: A Motivational Model, Nov et al.,
    http://www.citeulike.org/user/jhincapie/article/9405389
●   Common Sense, http://www.communitysensing.org/
●   Citizen Science : Enabling Participatory Urbanism, Paulos et al.,
    http://www.igi-global.com/chapter/citizen-science-enabling-participatory-urbanism/21817
●   People-Centric Urban Sensing, Campbell et al., http://dl.acm.org/citation.cfm?id=1234179
●
    Eye On Earth Summit 2011, Working Group White Papers,
    http://www.eyeonearthsummit.org/working-groups/working-group-3
●
    Agent-Based Participatory Simulations: Merging Multi-Agent Systems and Role-Playing Games, Guyot and Honiden,
    http://jasss.soc.surrey.ac.uk/9/4/8.html
●
    Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and
    crisis management: trends, OGC standards and application examples, Kamel Boulos et al.,
    http://www.ij-healthgeographics.com/content/10/1/67
●   The future of citizen science: emerging technologies and shifting paradigms, Newman et al.,
    http://www.monitoringmatters.org/articles/Newman.pdf
●   Crowdsourcing Crisis Information in Disaster-Affected Haiti, Heinzelman et al.,
    http://www.usip.org/publications/crowdsourcing-crisis-information-in-disaster-affected-haiti
●   Ownership in the City, Virtueel Platform, http://virtueelplatform.nl/english/news/ownership-in-the-hybrid-city/
●   Participatory System Dynamics Modeling for Sustainable Environmental Management: Observations from Four
    Cases, Stave et al., http://www.mdpi.com/2071-1050/2/9/2762
●   Citizen Sensor Data Mining, Social Media Analytics and Development Centric Web Applications, Sheth et al.,
    http://videolectures.net/www2011_sheth_velmurugan_csd/

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La présentation de Jean-Paul de Vooght à la soirée Citoyens Capteurs de la Cantine du 9 novembre 2012

  • 2. Markets Soft-Laws State/Federal Laws Top-Down Economic Systems Urban Systems Biodiversity Transportation Major Banks Water Health Sovereign Debts Soil Erosion Energy Ecosystemic Services Bottom-Up « Take Ownership »
  • 3. “The technology community has set up interactive maps to help us identify needs and target resources.”
  • 4. / ast.org http ://safec http://sparkfun.com/ Tohoku Earthquake
  • 5. blackcloud.org ● Multimodal sensor (light, temperature, noise, CO2, organic volatile compounds) ● 37 participants over a period of 35 days in the Bay Area and Greater Los Angeles ● Gamified approach to learning about pollution Other Projects http://airqualityegg.wikispaces.com/ http://aircasting.org/
  • 7. dontflush.me Source : http://teachgreenbk.wordpress.com 3 NCB-01 http://dontflush.me/ Combined Sewage Overflows
  • 9. Taking Ownership in 3 Dimensions Participative data gathering Handling of high environmental signal variety Understanding through systemic thinking
  • 10. Urban Sensing : out of the woods
  • 11. Sensors ● Located at the edge of the « smart » city architecture ● Combine soft sensing (using our 5 senses) with hard sensing (IoT/UbiComp) ● Complementarity of DIY (discovery) and traditional manufacturing (replication) ● Standards for identifiers, formats, semantics and protocols supporting participatory approaches ● Additional considerations : ● Data ownership and terms of use (open data) ● Sensor selection and calibration (trust) ● Privacy and anonymity DIY Counter by Tomorrow Lab
  • 13. Execution ● Learn from : citizen science ● Action, conservation, investigation, virtual, education (Crowston, Wiggins) ● Protocol design and quality control (task granularity) ● Motivation factors : collective, norm-oriented, identification, intrinsic, reward (Nov et al.) ● Crowdmapping and disaster-relief ● What relief teams want vs what volunteers report ● Data provenance and veracity ● Conciling TOS of popular services with agency regulations ● Task coordination under heavy constraints ● Micro-tasking platforms (Amazon Mechanical Turk, Kaggle, etc.) turn to mechanism design to optimize participation, incentives and results ● Symmetric governance structures with progression potential for participants
  • 14. Complexity in the anthropocene
  • 15. Simplified Peak Oil Example Thinking In Systems ● Put observations into context ● Use conceptual models and create simulations ● Recognize interconnections ● Identify feedback and delays ● Understand dynamic behavior ● Differentiate flows and stocks ● Open and Transdisciplinary approach with multiple roles : ● Observers and collectors ● Instrument makers ● Data scientists ● Domain and policy experts ● Leverage modeling environments and visualization kits available (R, NetLogo, Insight Maker, d3, Tangle, OpenStreetMap, etc.) ● Test alternative policies around a shared model of understanding Source : de Castro Carranza http://insightmaker.com/insight/2993
  • 16. Modeling, Simulation and Discussion Hard Sensing Soft Sensing Shared Understanding Filter Change ? Multi-Scale Visualization Repeatable Accross a Variety of Ecosystems Instrumentation of Model Report Events and Variables Over Time Rent-a-Sensor Smartphone Context and DIY Feature Phone CO, CO2, O2, CH4, H2, NH3, 311-type events, ideas, C4H10, CH3CH2OH, C6H5H3, best practices addressing H2S, NO2, O3, VOC, Air elements in the shared model of understanding. Temperature, Humidity, Pressure, PIR, Noise, Magnetic Field, Soil Citizens Sensing Temperature, open data, etc..
  • 17. “Design a way to monitor the natural and industrial systems around you and make them knowable to you and your colleagues. Don’t try to do it alone. We are all designers now.” John Thackara In The Bubble Jean-Paul de Vooght http://citizensensing.posterous.com/
  • 18. References ● HOME, Arthus-Bertrand, https://www.youtube.com/movie?feature=plcp&v=jqxENMKaeCU ● Urban sensing : out of the woods, Cuff et al., http://dl.acm.org/citation.cfm?id=1325562 ● Workshop at the 10th International Conference on Ubiquitous Computing, http://www.urban-atmospheres.net/Ubicomp2008/ ● Technology-Mediated Citizen Science Participation: A Motivational Model, Nov et al., http://www.citeulike.org/user/jhincapie/article/9405389 ● Common Sense, http://www.communitysensing.org/ ● Citizen Science : Enabling Participatory Urbanism, Paulos et al., http://www.igi-global.com/chapter/citizen-science-enabling-participatory-urbanism/21817 ● People-Centric Urban Sensing, Campbell et al., http://dl.acm.org/citation.cfm?id=1234179 ● Eye On Earth Summit 2011, Working Group White Papers, http://www.eyeonearthsummit.org/working-groups/working-group-3 ● Agent-Based Participatory Simulations: Merging Multi-Agent Systems and Role-Playing Games, Guyot and Honiden, http://jasss.soc.surrey.ac.uk/9/4/8.html ● Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and crisis management: trends, OGC standards and application examples, Kamel Boulos et al., http://www.ij-healthgeographics.com/content/10/1/67 ● The future of citizen science: emerging technologies and shifting paradigms, Newman et al., http://www.monitoringmatters.org/articles/Newman.pdf ● Crowdsourcing Crisis Information in Disaster-Affected Haiti, Heinzelman et al., http://www.usip.org/publications/crowdsourcing-crisis-information-in-disaster-affected-haiti ● Ownership in the City, Virtueel Platform, http://virtueelplatform.nl/english/news/ownership-in-the-hybrid-city/ ● Participatory System Dynamics Modeling for Sustainable Environmental Management: Observations from Four Cases, Stave et al., http://www.mdpi.com/2071-1050/2/9/2762 ● Citizen Sensor Data Mining, Social Media Analytics and Development Centric Web Applications, Sheth et al., http://videolectures.net/www2011_sheth_velmurugan_csd/