Local governments are increasingly looking for new ways to involve citizens in policy and decision-making, for example by combining public sector data sources with data gathered by citizens. Several examples exist of data gathering where personal mobile devices act as data collectors. While these efforts illustrate the technical capability of data sourcing, they neglect the value of local knowledge where people use their senses to capture and interpret data. Traditional data gathering initiatives, however, exploit this local knowledge to inform policy makers, e.g., neighborhood policing. To understand data gather-ing processes of these traditional data gathering initiatives, three cases are ex-amined. We analyze these cases, focusing on the various elements they contain, concluding how digital data gathering can be informed by these traditional vari-ants, concerning what the benefits of using digital means can be for data gather-ing and how traditional initiatives ensure data re-use by the public sector. Paper presented at the IFIP EGOV Conference 2013. Paper available here: http://link.springer.com/chapter/10.1007/978-3-642-40358-3_8

1. Participatory Data Gathering
for Public Reuse
Nathalie Stembert1, Peter Conradie1, Ingrid Mulder1,2, and Sunil Choenni11,3
1. Creating 010, Rotterdam University of Applied Sciences (n.stembert@hr.nl,
p.d.conradie@hr.nl)
2. ID-StudioLab, Delft University of Technology (I.J.Mulder@tudelft.nl)
3. Research and Documentation Centre, Ministry of Justice, The Netherlands
(r.choenni@minvenj.nl)
Lessons Learned from Traditional
Initatives

2. Introduction

3. Introduction
Digital means that enable people to passively gather data
are emerging, among others to map noise pollution or
indicate quality of roads or congestion
Maisonneuve, N., Stevens, M., Ochab, B.: Participatory noise pollution monitoring using mobile phones. Information Polity. 15, 51–71 (2010).
Eriksson, J., Girod, L., Hull, B., Newton, R., Madden, S., Balakrishnan, H.: The Pothole Patrol: Using a Mobile Sensor Network for Road Surface Monitoring.
MobiSys 2008 (2008).
Savage, N.: Cycling through data. Communications of the ACM. 53, 16 (2010).
Image source: http://www.flickr.com/photos/johnkarakatsanis/8551270040

4. Example – Pothole Patrol
Image source: http://www.flickr.com/photos/_chrisuk/6621444233/

5. Introduction
Initiatives constitute the use of people as carriers of
mobile sensors
Image Source: http://www.flickr.com/photos/tronixstuff/4524900783

6. Introduction
Beneficial for data quality, non comparibility of data,
logistical issues
Gouveia, C., Fonseca, A., Câmara, A., Ferreira, F.: Promoting the use of environmental data collected by concerned citizens through information and
communication technologies. Journal of environmental management. 71, 135–54 (2004).
Image Source: http://www.flickr.com/photos/tronixstuff/4524900783

7. Introduction
Neglects qualitative information embedded in communities
Image Source: http://www.flickr.com/photos/kheelcenter/5279081507
Coleman, S., Gøtze, J.: Bowling Together: Online Public Engagement in Policy Deliberation Online Public Engagement in Policy Deliberation. (2001).
Corburn, J.: Bringing Local Knowledge into Environmental Decision Making Improving Urban Planning for. 420–433 (2003).
Corburn, J.: Community knowledge in environmental health science: co-producing policy expertise. Environmental Science & Policy. 10, 150–161 (2007).
Fischer, F.: Citizens, experts, and the environment: The politics of local knowledge. Duke University Press (2000).
Stokes, P., Havas, M., Brydges, T.: Public participation and volunteer help in monitoring programs: An assessment. Environmental Monitoring and
Assessment. 15, 225–229 (1990).

8. How can digital data gathering
processes benefit from traditional data
gathering initiatives?

9. Rotterdam
Source: Wikimedia Commons: http://en.wikipedia.org/wiki/File:RotterdamMaasNederland.jpg
2nd biggest Dutch city
+/- 600 000 inhabitants
Higher than average crime and unemployment

10. Cases

11. Case overview
Drugs in Color (DC) Housing Report (HR) Citizen Blue (CB)
Goal
Stop long-term annoyance of
drug nuisance in the
neighborhood
Raise attention for the
housing shortage in the
neighborhood
Stop long-term annoyance
of disturbance in the
neighborhood
Data Quantitative Quantitative & Qualitative Qualitative
Frequency Quarterly
Non-recurrent half year
project
Once every two weeks
Supporters Community worker, Local Police Community center
Community center, Local
Police
Gatherers Concerned citizens Independent researcher Concerned citizens
Interpreters Independent interpreter Independent researcher Trained citizens
Data Recipients
Municipality, Local police, Housing
corporation
Local residents,
Municipality, Housing
corporation
Municipality, Local police,
Housing corporation,
maintenance service

12. Case selection
Multiple case study approach
Selection criteria:
(a) it is an initiative in which citizens use their senses to gather data,
(b) ownership of the initiative lies with citizens, and
(c) the data is gathered to influence local policy and decision making

13. Approach
Structured, semi-structured interviews, obervations and
shadowing

14. Statement card analysis
Visser, F.S., Lugt, R. Van Der, Stappers, P.J.: Participatory design needs participatory communication: New tools for sharing user insights in the product
innovation process. Proceedings of 9th European Conference on Creativity and Innovation - September 2005. pp. 1–17. , Łódź, Poland (2005).

15. Results: Actors

16. Bron:
Actormap per case

17. Actors
Process
supporters
Data
Recipients
Data
Interpreters
Data
Gatherers

18. Results: Process

19. Process
1 - Mother organizations: Make us of existing socials
structures, logistical support, subsidies

20. Process
2 - Motivational trigger: Mostly negative trigger, resulting
in data gathering

21. Process
3 - Legitimacy: Collaborative data gathering with
legitimizing actors (police, local council, bureau of
statistics)

22. Process
4 - Standardization and methodology: Agreement on
method of gathering, standardized measurements

23. Process
5 - Data Gathering:
Contextual knowledge applied during gathering
Data interpreted to gain insights
Analysed data presented
Acknowledgement of data gathering by local authority

24. Process
6 - Feedback:
Short, medium or long term feedback on results. Common
ground or understanding of the issues, to concrete actions
undertaken to change situation

25. Discussion

26. Points of discussion
Hyper-local context – how can digital data gatherers
benefit from local support?
What is the right balance between loosely organized online
communities of interest and more stricter organizations?
How can the value of the data be retained during ad-hoc
digital gathering?

27. Outlook

28. Outlook

29. Outlook

30. Outlook
Source: Wikimedia Commons http://commons.wikimedia.org/wiki/File:Rotterdam_stadhuis.jpg
Small pilots in collaboration with
Rotterdam Municipality

31. Thank you!