Sense-making with a citizen-sensor-network in the city of Nijmegen

Transcriptie

1 Slide optie 1A Sense-making with a citizen-sensor-network in the city of Nijmegen City government, university, entrepreneurs and citizens monitoring urban dynamics in Smart Emission project. Linda Carton, Michel Grothe, Hester Volten, Henk Nijhuis, and other project members, citizens and students involved in the Smart Emission consortium. Consortium pilot: RU, gem. Nijmegen, Geonovum, Intemo, CityGIS, RIVM

2 Background: Developments in society - Cities and urban health: Emissions and air pollution - ICT development and the wikification of GIS Mobile app Chinese cities Online real-time air pollution index

3 Illness load or ziektelast by air pollution (source: Volksgezondheid Toekomst Verkenning, RIVM 2014) Unhealthy environment counts for almost 6% in estimation of the causes of bad health and illness load, of which air quality accounts for circa 5% and noise for circa 1% Exposure to fine dust in the Netherlands leads to an average life shortening of circa 12 months. 3

4 Spatial context and history: New bridge and ringway S100 planned and implemented near city-harbor and large inner-city industrial area, Nijmegen-West. => Citizens in Nijmegen are concerned about increasing emissions Governmental ambitions, City government (College B&W): Keep working on improvement of environment quality in the city, also on local scale Look beyond existing norms, do more than legally required, from idea that less emissions will lead to increased health (own city policy, not mandatory by EU/national rules, because of citizen concerns) Better monitoring, more fine-grained, innovation. Strive for participation and transparency, substantive dialogue preferred above legal procedures (Raad van State). Measures for air quality indicators (soot) and for traffic as major source.

5 Core idea Smart Emission co-creation, experimenting with constructing a citizen-sensor-network in the city, use the city as urban laboratory. Illustratie: Anke Nobel Consortium Smart Emission ( ): Radboud University, Municipality Nijmegen, Intemo, CityGIS, Geonovum, RIVM, and 34 citizen-sensor-holders in the city of Nijmegen. 7

6 Research questions Smart Emission 1. Do low-cost sensors add to the fine-grained picture of air quality indicators? 2. Does the concept work? 3. Does sense-making with citizens work? 4. Does this open up opportunities for environmentally-informed city governance? 5. Reflective: (How) do roles of government and citizen change?

7 Approach and underlying philosophy 1. Inclusive Citizen Sensing: Transparency and democracy of pollution monitoring Citizen-sensor-networks for fine-grained measurements Assess fine-grained measurements & large-scale models in mutual relation Cost-effective environmental monitoring, Open Data 2. Towards Sustainable Cities: Value human health in the city Support change of daily behavior (real-time feedback), And on longer term, shift car traffic to bicycle and electric transport (awareness raising, shifting policy discourse from norms towards health) 3. Smart Governance: Tracing urban dynamics, visualize urban environmental footprint Information cycles, from small to large, bottom-up: Connect small cycles (feedback data) and large cycles (info piping through models) 9

8 Participatietraject, Roadmap Smart Emission pilot 2016 (test of proof of concept, with planned participatory meetings during pilot) 1 e citizen participation meeting, after request in local newspaper to sign up (jan. 2016) 2 e citizen participation meeting, install sensors (voorjaar, incl. klimaatkamertest RIVM) 3 e citizen participation meeting, preliminary results of 1 e data output (via viewers ) Meanwhile: Calibration, use case analyses, (fietsronde, evaluatie in september) 4 e en 5 e citizen meeting: Two evening lectures, to do collective learning and sensemaking of Noise and Air Quality as phenomena, and selective sensor data use cases Discussing results so far (16 en 24 november 2016) End of pilot, wrap up results in scientific and societal circles (dec 2016) 2017: Continuation: Maintenance of sensor network + innovation: extend network with 12 sensoren and 6 indoor sensors at schools (a fine dust sensing device included), apply for follow-up research, (calibration by data science approach, active citizen participation and partial self-organization, data use). Towards forming a working group of sensor holders. 10

9 Theory: role of citizens in combination with sensor data In planning literature, much about participatory planning Literature on sensors and citizen s expertise is emerging Source: Boulos et al. (2011) 9

10 Levels of participation and citizen science Haklay (2013) Citizen science and Volunteered Geographic Information (VGI). Levels of participation and engagement in citizen science projects

11 A networked gradient in measurement systems from high level and expensive (scarce in spatial spread), to consumer products and Do-It-Yourself equipment Weinig Veel 1. RIVM LML Gassen en fijnstof meters 2. Locale boxen Gemeente Nijmegen 3. Small sensors Smart Emission project 4. Makers community, DIY beweging Hoog geavanceerd Middel geavanceerd Best beschikbare in consumenten pr. Laagste kosten consumenten pr. Accuracy conditions Cost-accuracy assessment Relative accuracy with low cost Lowest cost, smallest accuracy. Professional specialization Professional specialization Relatively simple to operate Self-made rocket science standard hospital equipment light-weight camera, for trained user Dustduino (source: L. Carton)

12 1 e citizen workshop, January

13 1 st sensors 12

14 2 nd citizen meeting: citizens explain their local case, request forum 13

15 Cycling route along sensors (sept) 14

16 Sensordata: interns and masterstudents present analyses during evening lecture and on digital forum

17 to citizen-sensor-holders and project members Evening lecture Forum

18 Sensor Jose (binnenwerk) Data die Jose sensoren doorgeven: NO2 (Stikstofdioxide) Ozon CO2 CO Geluidsdruk (in frequentiebanden) Trillingen (x,y,z) Barometer Altimeter Luchtvochtigheid Temperatuur (buiten) Temperatuurcompensatie (intern) Lichtintentsiteit reflectie Luchtkleur Made by: Sensor: Janus Hoeks & Antoine van de Cruyssen, Intemo. Intemo Datum Tijd Lokatie y (Latitude) Lokatie x (Longitude) Voeding status Foutmeldingen status Base timer Tijdsduur sessie Serienummer van sensor 17

19 Whale SmartApp Heron SOS Verfijnde Data Picture Just van den Broecke, Geonovum

20 Infrastructure by Robert Kieboom, Just van den Broecke, Paul Geurts, Michel Grothe CityGIS and Geonovum Setup of Spatial Data Infrastructure Private- Public division in the spatial data infrastructure

21 Data infrastructuur en Viewers (dashboards) Smart Emission sensor data Portal: Viewers: Nieuw: Data Platform: 22

22 Viewers Smart Emission sensor data SmartApp (live data, 24/7, 7 dagen per week)

23 Viewers Smart Emission sensor data Heron viewer Heron viewer combineert: - Geluid - Lucht - Meteo - Historische data - Download functie - (ook: - RIVM Lucht - KNMI meteo) Whale viewer

24 Nieuwe Viewer door ImageM: SensorSmartMapp/ data fusion. (smart emission en verkeer doorstroming)

25 Setting up citizen participation with mathe student Cecile Kerssemakers (Mathe in Dutch) Hoofdvraag: Op welke manier kan de burgerparticipatie worden opgezet bij citizen-sensor-networks, specifiek in het citizen-sensor-network Smart Emission, en past deze opzet bij de wensen en doelstellingen van burgers en projectteam? Deelvragen: 1. Wat is Smart Emission? 2. Wat is een citizen-sensor-network? 3. Welke vormen van burgerparticipatie bestaan er? 4. Hoe kan de burgerparticipatie bij Smart Emission worden ingericht? a. Hoe richten andere citizen-sensor-networks de burgerparticipatie in? b. Welke rol voor de burger voorziet het projectteam van Smart Emission? c. Welke rol wil de burger innemen in Smart Emission? d. Waarom willen de burgers meedoen aan het citizen-sensor-network Smart Emission? 5. In hoeverre passen de rollen van burgers en projectteam Smart Emission bij de wensen en doelstellingen van deze partijen? a. Welke rol hebben de burgers en het projectteam Smart Emission? b. In hoeverre draagt de gekozen vorm van burgerparticipatie bij aan de doelstellingen van Smart Emission? c. Sluit de rol van de burger aan op de wensen en doelstellingen van de burger? d. Voldoet de burgerparticipatie aan de voorwaarden van goede burgerparticipatie?

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29 De participatieladder 21

30 Citizen participation and network monitoring for governance/planning Mathe Ellen Klein Gunnewiek: How does the Participation Network function? Based on a theoretical framework on Voluntary Environmental Monitoring (Lawrence, 2006) Elements: Internal and External knowledge, explication (coding) and internalization (attitudes, relations, culture) Motivation, engagement and empowerment Observation, learning, collective sensemaking Conceptual model Lawrence, 2006

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32 Research Approach Participation network in Citizen-sensor-network, Ellen Klein Gunnewiek

33 Waar staan we nu?

34 Use cases, Analysing Data: Casus Groenestraat (slide in Dutch) Is de Groenestraat een punt die relatief zwaarder belast is dan andere punten in Nijmegen? 6 sensoren gebruikt: (7 met sensor 25 erbij) 2 aan groenestraat (16, 57) 2 achtergrond (21,26) 25 2 kalibratie (12,14) Periode van 23 mei t/m 31 mei CO2, NO2, O3, Geluid en temp. 12 & Data afkomstig van Heronviewer Ook gekeken of gassen beïnvloed 16 & worden door temperatuur.

35 Work in progress, student-assistenten (o.a. nationale GI-minor. This case by Freek Thuis) First experiments with user cases Noise on 5 sensor locations, during 10 days. Two noise peaks on 30 May

36 T00:00: T04:00: T08:00: T12:00: T16:00: T20:00: T00:00: T04:00: T08:00: T12:00: T16:00: T20:00: T00:00: T04:00: T08:00: T12:00: T16:00: T20:00: T00:00: T04:00: T08:00: T12:00: T16:00: T20:00: T00:00: T04:00: T08:00: T12:00: T16:00: T20:00: T00:00: T04:00: T08:00: T12:00: T16:00: T20:00: T00:00: T04:00: T08:00: T12:00: T16:00: T20:00: T00:00: T04:00: T08:00: T12:00: T16:00: T20:00: T00:00: T04:00: T08:00: T12:00: T16:00: T20:00: T00:00:00 Eerste experimenten met gebruikerscases analyses CO2 in periode van 10 dagen 3-30 mei, casus Groenestraat CO2 op 7 sensorlocaties, gedurende 10 dagen. S12 S14 S16 S21 S25 S26 S57 Work in progress, student-assistenten

37 Experiments with use case analyses Ozone O3 op 6 sensor locations, during 10 days. S12 S14 S16 S21 S25 S26 S S21 10 S26 0 S57 Work in progress, student-assistents. Zoi Katsamani

38 Experiments with use case analyses NO2 op 4 sensor locations. Work in progress, student-assistents. Zoi Katsamani

39 Noise peaks during Vierdaagse festival Work in progress, student-assistents. Zoi Katsamani

40 Noise peaks during Vierdaagse festival

41 Data calibration Scatterplot prediction by Jose sensor relative to RIVM data Explained variance Ozon (O3) = 91% Ozon vergelijking RIVM Smart Emission data

42 Conclusions Idea of fine-grained citizen-sensor-network: Proof of concept: the citizen sensor network can be used to see and signal variations and increases of emissions and noise in the city, with dynamics in space-time. Sensors implemented in field, new data infrastructure works. Data can be viewed and analyzed by experts as well as citizens, available as Open Data and data interoperability standards. Active citizen-sensor holders join in the collaborative learning and sense-making process Collective sense-making implemented in practice, making intangble environmental urban qualities visible Roles and attitudes: There seems to be more trust than in the beginning among critical citizens (survey in december), Technology: 1st generation sensor works Calibration: Ozon (O3) well, CO2 has offset (can be solved), NO2 not so good. (other NO2-device in sensor station?) Data: De Open Data approach and standardised Sensor Data Infrastructuur inivtes more options in data presentatie. 42

43 Process of Sense-making in participatory monitoring Participatory setup: Issues/goals Monitor/ observe Measure [unit of analysis] Classification system Viewing and Interpreting apply informed consent Sensor-holders consent in participation

44 Process of Sense-making in participatory monitoring Participatory setup: Issues/goals Monitor/ observe Measure [unit of analysis] Classification system Viewing and Interpreting apply informed consent Sensor-holders consent in participation Small Feedback loops, sensemaking: Meaning contextualizing Trust in data Kalibration Validation Use of data for applications Experimenting and learning, build data infrastructure apply sense-making with participants Urban noise/air footprint as dynamic urban rhythmic patterns (weekdays, festivals)

45 Process of Sense-making in participatory monitoring Participatory setup: Issues/goals Monitor/ observe Measure [unit of analysis] Classification system Viewing and Interpreting apply informed consent Sensor-holders consent in participation Small Feedback loops, sensemaking: Meaning contextualizing Trust in data Kalibration Validation Use of data for applications Experimenting and learning, build data infrastructure apply sense-making with participants Urban noise/air footprint as dynamic urban rhythmic patterns (weekdays, festivals) Long feedback loops and reflection of relations: Social learning across organizations: Relation to existing models, norms and institutions Sustainability of the network itself Legitimation of rules of work, resources for maintenance, organization => Roles between citizens and government: Self-organizing or co-creation between civil society and (city-) government? Using new data infrastructure (and big data) for new apps New emerging questions and barriers

46 Sense-making, informed consent and social roles in monitoring Clarifying difference between policy objective and research objective this context is a research project data-inquiry technically, then interpretationmeaning construction with citizens, contextualization Informed consent obtained in participatory process: social contract Monitoring with citizen science, experts and government: Added value, practices by using CSN? Data accurate, valid? Data useful in hand of a diversity of users, with conflicting beliefs and worldviews? Thoughts on collaborative sense-making, citizen science, social-technical validity Open Data approach: Openness, Transparency, Trustworthiness a subjective approach to sense-making, should involve evaluating questions of trust/legitimacy? Max Weber: the presence of legitimate authority structures the society in such a way that even those who do not share the belief in its legitimacy face incentives to behave as if they did. This he called the validity of the social system.

47 Vervolg onderzoek Suggesties voor vervolg onderzoek, op 4 punten: 1. Burgerparticipatie en beheer: Vervolgonderzoek beoogd, zowel met sensorhouders werkgroep van burgers als met ondersteuning landelijk (beoogd: vervolg innovatief onderzoek met hulp van STW of NWO) 2. Data science: Onderzoek vervolg naar kalibratie en meetnet-vereffening, nauwkeurigheid 3. Betere spreiding door de stad: Meer sensoren in de stad, voor een beter fijnmazig beeld van stads- (centrum) activiteiten en effecten op geluid en emissies. 4. Uitbreiding met scholen: Bewustwording over luchtkwaliteit, en samenhang gedrag/dagelijkse patronen in de stad en effect op gezamenlijke milieukwaliteit. 47

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