Stop the Noise!: Enhancing Meaningfulness in Participatory Sensing with Community Level Indicators

Saskia Coulson; Melanie Woods; Michelle  Scott; Drew Hemment; M Balestrini

doi:10.1145/3196709.3196762

Stop the Noise! Enhancing Meaningfulness in Participatory Sensing with Community Level Indicators

Saskia Coulson, Melanie Woods, Michelle Scott, Drew Hemment, M Balestrini

Contemporary Art Practice

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

22 Citations (Scopus)

383 Downloads (Pure)

Abstract

In this paper we examine ways to make data more meaningful and useful for citizens in participatory sensing. Participatory sensing has evolved as a digitally enabled grassroots approach to data collection for citizens with shared concerns. However, citizens often struggle to understand data in relation to their daily lives, and use them effectively. This paper presents a qualitative study on the development of a novel approach to Community Level Indicators (CLIs) during two participatory sensing projects focused on noise pollution. It investigates how CLIs can provide an infrastructure to address challenges in participatory sensing, specifically, making data meaningful and useful for non-experts. Furthermore, we consider how this approach moves towards an ambition of achieving change and impact through participatory sensing and discuss the challenges in this way of working and provide recommendations for future use of CLIs.

Original language	English
Title of host publication	Proceedings of the 2018 Designing Interactive Systems Conference
Publisher	Association for Computing Machinery (ACM)
Pages	1183-1192
Number of pages	10
ISBN (Electronic)	978-1-4503-5198-0
DOIs	https://doi.org/10.1145/3196709.3196762
Publication status	Published - 8 Jun 2018
Event	Design interactive Systems 2018 - The School of Design of the Hong Kong Polytechnic University, Hong Kong, China Duration: 9 Jun 2018 → 13 Jun 2018 http://dis2018.org/

Conference

Conference	Design interactive Systems 2018
Abbreviated title	DIS 2018
Country/Territory	China
City	Hong Kong
Period	9/06/18 → 13/06/18
Internet address	http://dis2018.org/

Keywords

Community Level Indicators
Noise pollution
Participatory Sensing
Research Methods
Co-Design

Access to Document

10.1145/3196709.3196762

Author Accepted ManuscriptAccepted author manuscript, 2.38 MB

Cite this

@inproceedings{bd6f3efa4d394eb6a70bb2999d70f30d,

title = "Stop the Noise!: Enhancing Meaningfulness in Participatory Sensing with Community Level Indicators",

abstract = "In this paper we examine ways to make data more meaningful and useful for citizens in participatory sensing. Participatory sensing has evolved as a digitally enabled grassroots approach to data collection for citizens with shared concerns. However, citizens often struggle to understand data in relation to their daily lives, and use them effectively. This paper presents a qualitative study on the development of a novel approach to Community Level Indicators (CLIs) during two participatory sensing projects focused on noise pollution. It investigates how CLIs can provide an infrastructure to address challenges in participatory sensing, specifically, making data meaningful and useful for non-experts. Furthermore, we consider how this approach moves towards an ambition of achieving change and impact through participatory sensing and discuss the challenges in this way of working and provide recommendations for future use of CLIs.",

keywords = "Community Level Indicators, Noise pollution, Participatory Sensing, Research Methods, Co-Design",

author = "Saskia Coulson and Melanie Woods and Michelle Scott and Drew Hemment and M Balestrini",

note = "This research was supported by European Commission within the H2020 ICT 2015 Research and Innovation action under the grant agreement number 688620. ; Design interactive Systems 2018, DIS 2018 ; Conference date: 09-06-2018 Through 13-06-2018",

year = "2018",

month = jun,

day = "8",

doi = "10.1145/3196709.3196762",

language = "English",

pages = "1183--1192",

booktitle = "Proceedings of the 2018 Designing Interactive Systems Conference",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

url = "http://dis2018.org/",

}

Coulson, S , Woods, M, Scott, M, Hemment, D & Balestrini , M 2018, Stop the Noise! Enhancing Meaningfulness in Participatory Sensing with Community Level Indicators. in Proceedings of the 2018 Designing Interactive Systems Conference. Association for Computing Machinery (ACM), pp. 1183-1192, Design interactive Systems 2018, Hong Kong, China, 9/06/18. https://doi.org/10.1145/3196709.3196762

Stop the Noise! Enhancing Meaningfulness in Participatory Sensing with Community Level Indicators. / Coulson, Saskia ; Woods, Melanie; Scott, Michelle et al.
Proceedings of the 2018 Designing Interactive Systems Conference. Association for Computing Machinery (ACM), 2018. p. 1183-1192.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Stop the Noise!

T2 - Design interactive Systems 2018

AU - Coulson, Saskia

AU - Woods, Melanie

AU - Scott, Michelle

AU - Hemment, Drew

AU - Balestrini , M

N1 - This research was supported by European Commission within the H2020 ICT 2015 Research and Innovation action under the grant agreement number 688620.

PY - 2018/6/8

Y1 - 2018/6/8

N2 - In this paper we examine ways to make data more meaningful and useful for citizens in participatory sensing. Participatory sensing has evolved as a digitally enabled grassroots approach to data collection for citizens with shared concerns. However, citizens often struggle to understand data in relation to their daily lives, and use them effectively. This paper presents a qualitative study on the development of a novel approach to Community Level Indicators (CLIs) during two participatory sensing projects focused on noise pollution. It investigates how CLIs can provide an infrastructure to address challenges in participatory sensing, specifically, making data meaningful and useful for non-experts. Furthermore, we consider how this approach moves towards an ambition of achieving change and impact through participatory sensing and discuss the challenges in this way of working and provide recommendations for future use of CLIs.

AB - In this paper we examine ways to make data more meaningful and useful for citizens in participatory sensing. Participatory sensing has evolved as a digitally enabled grassroots approach to data collection for citizens with shared concerns. However, citizens often struggle to understand data in relation to their daily lives, and use them effectively. This paper presents a qualitative study on the development of a novel approach to Community Level Indicators (CLIs) during two participatory sensing projects focused on noise pollution. It investigates how CLIs can provide an infrastructure to address challenges in participatory sensing, specifically, making data meaningful and useful for non-experts. Furthermore, we consider how this approach moves towards an ambition of achieving change and impact through participatory sensing and discuss the challenges in this way of working and provide recommendations for future use of CLIs.

KW - Community Level Indicators

KW - Noise pollution

KW - Participatory Sensing

KW - Research Methods

KW - Co-Design

UR - http://dis2018.org/index.html

U2 - 10.1145/3196709.3196762

DO - 10.1145/3196709.3196762

M3 - Conference contribution

SP - 1183

EP - 1192

BT - Proceedings of the 2018 Designing Interactive Systems Conference

PB - Association for Computing Machinery (ACM)

Y2 - 9 June 2018 through 13 June 2018

ER -

Stop the Noise! Enhancing Meaningfulness in Participatory Sensing with Community Level Indicators

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Community Level Indicators Tool

Making Sense

Community Level Indicators & tools for impact co-evaluation

Cite this

Stop the Noise! Enhancing Meaningfulness in Participatory Sensing with Community Level Indicators

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Research output

Community Level Indicators Tool

Making Sense

Activities

Community Level Indicators & tools for impact co-evaluation

Cite this