More Web Proxy on the site http://driver.im/

research-article

Guess the Data: Data Work to Understand How People Make Sense of and Use Simple Sensor Data from Homes

Authors:

Albrecht Kurze,

Andreas Bischof,

Sören Totzauer,

Maximilian Eibl,

Margot Brereton,

Arne BergerAuthors Info & Claims

CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Pages 1 - 12

https://doi.org/10.1145/3313831.3376273

Published: 23 April 2020 Publication History

Abstract

Simple smart home sensors, e.g. for temperature or light, increasingly collect seemingly inconspicuous data. Prior work has shown that human sensemaking of such sensor data can reveal domestic activities. Such sensemaking presents an opportunity to empower people to understand the implications of simple smart home sensors. To investigate, we developed and field-tested the Guess the Data method, which enabled people to use and make sense of live data from their homes and to collectively interpret and reflect on anonymized data from the homes in our study. Our findings show how participants reconstruct behavior, both individually and collectively, expose the sensitive personal data of others, and use sensor data as evidence and for lateral surveillance within the household. We discuss the potential of our method as a participatory HCI method for investigating design of the IoT and implications created by doing data work on home sensors.

Supplementary Material

MP4 File (a146-kurze-presentation.mp4)

Download
41.87 MB

References

[1]

Mara Balestrini, Tomas Diez, Paul Marshall, Alexander Gluhak, and Yvonne Rogers. 2015. IoT Community Technologies: Leaving Users to Their Own Devices or Orchestration of Engagement? EAI Endorsed Transactions on Internet of Things 1, 1: 150601. https://doi.org/10.4108/eai.26--10--2015.150601

[2]

Ralf Bohnsack. 2004. Group Discussion and Focus Groups. In A companion to qualitative research.

[3]

Nico Castelli, Corinna Ogonowski, Timo Jakobi, Martin Stein, Gunnar Stevens, and Volker Wulf. 2017. What Happened in My Home?: An End-User Development Approach for Smart Home Data Visualization. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17), 853--866. https://doi.org/10.1145/3025453.3025485

Digital Library

[4]

Matt Day, Giles Turner, and Natalia Drozdiak. 2019. Amazon Workers Are Listening to What You Tell Alexa. Bloomberg. Retrieved June 2, 2019 from https://www.bloomberg.com/news/articles/2019-0410/is-anyone-listening-to-you-on-alexa-a-global-teamreviews-audio

[5]

Abigail Durrant, David Kirk, Diego Trujillo Pisanty, Wendy Moncur, Kathryn Orzech, Tom Schofield, Chris Elsden, David Chatting, and Andrew Monk. 2017. Transitions in digital personhood: Online activity in early retirement. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 6398--6411. https://doi.org/10.1145/3025453.3025913

Digital Library

[6]

Joel E. Fischer, Andy Crabtree, James A. Colley, Tom Rodden, and Enrico Costanza. 2017. Data Work: How Energy Advisors and Clients Make IoT Data Accountable. Computer Supported Cooperative Work (CSCW) 26, 4--6: 597--626. https://doi.org/10.1007/s10606-017--9293-x

Digital Library

[7]

Joel E. Fischer, Andy Crabtree, Tom Rodden, James A. Colley, Enrico Costanza, Michael O. Jewell, and Sarvapali D. Ramchurn. 2016. "Just Whack It on Until It Gets Hot": Working with IoT Data in the Home. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI '16), 5933--5944. https://doi.org/10.1145/2858036.2858518

Digital Library

[8]

Tarleton Gillespie, Pablo J. Boczkowski, and Kirsten A. Foot. 2014. The relevance of algorithms. Media Technologies: Essays on Communication, Materiality, and Society 167. https://doi.org/10.7551/mitpress/9780262525374.003.0 009

[9]

Donna Haraway. 1988. Situated Knowledge: The science Question in Feminism and the Privilege of Partial Perspective. Feminist Studies 14: 579--599. https://doi.org/10.2307/3178066

[10]

Jason I. Hong, Jennifer D. Ng, Scott Lederer, and James A. Landay. 2004. Privacy Risk Models for Designing Privacy-sensitive Ubiquitous Computing Systems. In Proceedings of the 5th Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques (DIS '04), 91--100. https://doi.org/10.1145/1013115.1013129

Digital Library

[11]

Timo Jakobi, Corinna Ogonowski, Nico Castelli, Gunnar Stevens, and Volker Wulf. 2017. The Catch(Es) with Smart Home: Experiences of a Living Lab Field Study. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17), 1620--1633. https://doi.org/10.1145/3025453.3025799

Digital Library

[12]

Joseph M. Kahn, Randy H. Katz, and Kristofer SJ Pister. 1999. Next century challenges: mobile networking for "Smart Dust." In Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking, 271--278. https://doi.org/10.1145/313451.313558

Digital Library

[13]

Jack Kelly and William Knottenbelt. 2015. The UKDALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes. Scientific Data 2. https://doi.org/10.1038/sdata.2015.7

[14]

Treffyn Lynch Koreshoff, Tuck Wah Leong, and Toni Robertson. 2013. Approaching a human-centred internet of things. In Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration, 363--366. https://doi.org/10.1145/2541016.2541093

Digital Library

[15]

Gierad Laput, Yang Zhang, and Chris Harrison. 2017. Synthetic Sensors: Towards General-Purpose Sensing. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17), 3986--3999. https://doi.org/10.1145/3025453.3025773

Digital Library

[16]

Ilaria Liccardi, Alfie Abdul-Rahman, and Min Chen. 2016. I Know Where You Live: Inferring Details of People's Lives by Visualizing Publicly Shared Location Data. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI '16), 1--12. https://doi.org/10.1145/2858036.2858272

Digital Library

[17]

Helena M. Mentis, Anita Komlodi, Katrina Schrader, Michael Phipps, Ann Gruber-Baldini, Karen Yarbrough, and Lisa Shulman. 2017. Crafting a View of Self-Tracking Data in the Clinical Visit. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17), 5800--5812. https://doi.org/10.1145/3025453.3025589

Digital Library

[18]

Nick Merrill, John Chuang, and Coye Cheshire. 2019. Sensing is Believing: What People Think Biosensors Can Reveal About Thoughts and Feelings. In Proceedings of the 2019 on Designing Interactive Systems Conference (DIS '19), 413--420. https://doi.org/10.1145/3322276.3322286

Digital Library

[19]

Philipp Morgner, Christian Müller, Matthias Ring, Björn Eskofier, Christian Riess, Frederik Armknecht, and Zinaida Benenson. 2017. Privacy Implications of Room Climate Data. In Computer Security -- ESORICS 2017 (Lecture Notes in Computer Science), 324--343. https://doi.org/10.1007/978--3--319--66399--9_18

[20]

Aare Puussaar, Adrian K. Clear, and Peter Wright. 2017. Enhancing Personal Informatics Through Social Sensemaking. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17), 6936--6942. https://doi.org/10.1145/3025453.3025804

Digital Library

[21]

Emilee Rader and Janine Slaker. 2017. The Importance of Visibility for Folk Theories of Sensor Data. In Thirteenth Symposium on Usable Privacy and Security ({SOUPS} 2017), 257--270. Retrieved July 24, 2017 from https://www.usenix.org/conference/soups2017/technica l-sessions/presentation/rader

[22]

Tobias Schwartz, Gunnar Stevens, Timo Jakobi, Sebastian Denef, Leonardo Ramirez, Volker Wulf, and Dave Randall. 2015. What People Do with Consumption Feedback: A Long-Term Living Lab Study of a Home Energy Management System. Interacting with Computers 27, 6: 551--576. https://doi.org/10.1093/iwc/iwu009

[23]

Tobias Schwartz, Gunnar Stevens, Leonardo Ramirez, and Volker Wulf. 2013. Uncovering Practices of Making Energy Consumption Accountable: A Phenomenological Inquiry. ACM Trans. Comput.Hum. Interact. 20, 2: 12:1--12:30. https://doi.org/10.1145/2463579.2463583

Digital Library

[24]

Alessandro Soro, Aloha Hufana Ambe, and Margot Brereton. 2017. Minding the Gap: Reconciling Human and Technical Perspectives on the IoT for Healthy Ageing. Wireless Communications and Mobile Computing 2017: 1--15. https://doi.org/10.1155/2017/7439361

Digital Library

[25]

Anselm Strauss and Juliet Corbin. 1998. Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. Sage Publications, Inc.

[26]

Anselm L. Strauss. 1987. Qualitative analysis for social scientists. Cambridge University Press, Cambridge [Cambridgeshire]?; New York.

[27]

Lucy Suchman. 2007. Human-machine reconfigurations: Plans and situated actions. Cambridge University Press. Retrieved March 28, 2017 from https://books.google.de/books?hl=de&lr=&id=VwKM DVGv1MC&oi=fnd&pg=PR7&dq=Suchman,+L.+(2007). +Humanmachine+reconfigurations:+Plans+and+situated+action s.+Cambridge+University+Press.&ots=BNIuAMYaG&sig=XsX8h85x_39Ff3F29UbdbjA9RVs

[28]

Texas Instruments. 2017. Simplelink SensorTag. Retrieved August 16, 2017 from http://www.ti.com/ww/en/wireless_connectivity/sensor tag/gettingStarted.html

[29]

Peter Tolmie, Andy Crabtree, Tom Rodden, James Colley, and Ewa Luger. 2016. "This Has to Be the Cats": Personal Data Legibility in Networked Sensing Systems. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing (CSCW '16), 491--502. https://doi.org/10.1145/2818048.2819992

Digital Library

[30]

Max Van Kleek, Ilaria Liccardi, Reuben Binns, Jun Zhao, Daniel J. Weitzner, and Nigel Shadbolt. 2017. Better the Devil You Know: Exposing the Data Sharing Practices of Smartphone Apps. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17), 5208--5220. https://doi.org/10.1145/3025453.3025556

Digital Library

[31]

Gary Wolf. 2010. The Data-Driven Life. The New York Times. Retrieved September 6, 2019 from https://www.nytimes.com/2010/05/02/magazine/02self -measurement-t.html

[32]

Rayoung Yang and Mark W. Newman. 2013. Learning from a learning thermostat: lessons for intelligent systems for the home. In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing (UbiComp '13), 93. https://doi.org/10.1145/2493432.2493489

Digital Library

Cited By

Desjardins ABenabdallah GKaneko M(2024)Un/Making Data Imaginaries: The Data EpicsACM Transactions on Computer-Human Interaction10.1145/368526931:6(1-38)Online publication date: 14-Aug-2024
https://dl.acm.org/doi/10.1145/3685269
Bailey GSeunarine KBaptista De Lima CCarnie MHaymoor ZHyde MJones BJones MPearson JReitmaier TRobinson SSahoo DWilliams A(2024)Older Generation: Self-Powered IoTs, Home-Life and “Ageing Well”Proceedings of the 13th Nordic Conference on Human-Computer Interaction10.1145/3679318.3685410(1-14)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3679318.3685410
Yan DBourgeois JKortuem G(2024)Say You, Say Me: Investigating the Personal insights Generated from One's Own data and Other's dataProceedings of the 13th Nordic Conference on Human-Computer Interaction10.1145/3679318.3685345(1-14)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3679318.3685345
Show More Cited By

Index Terms

Guess the Data: Data Work to Understand How People Make Sense of and Use Simple Sensor Data from Homes
1. Human-centered computing
  1. Human computer interaction (HCI)

Recommendations

Preserving Privacy in Smart Homes: A Socio-Cultural Approach
CHI EA '18: Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems

Smart homes are expected to reduce the time we spend on routine activities. Data becomes an enabler and asset, as smart devices collect and process it. Smart homes also have the potential to exaggerate bewilderment and resistance, feelings people ...
The Connected Shower: Studying Intimate Data in Everyday Life

This paper presents the design and field study of the Connected Shower, a bespoke IoT device that captures water flow, temperature, shower-head movement, and shower product weight. We deployed the device in six UK homes for a week to understand the use ...
Decision making support for privacy data upload in smart home
UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers

A smart home equipped with various smart devices allows a service provider to automatically identify daily living activities from sensor/appliance data, but it is risky for dwellers to upload all the data generated in the home. In this paper, we define ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

April 2020

10688 pages

ISBN:9781450367080

DOI:10.1145/3313831

General Chairs:
Regina Bernhaupt
Eindhoven University of Technology, Netherlands
,
Florian 'Floyd' Mueller
Monash University, Australia
,
David Verweij
Newcastle University, UK
,
Josh Andres
RMIT, Australia
,
Program Chairs:
Joanna McGrenere
University of British Columbia, Canada
,
Andy Cockburn
University of Canterbury, New Zealand
,
Ignacio Avellino
University of Maryland Baltimore County, USA
,
Alix Goguey
Grenoble Alpes University, France
,
Pernille Bjørn
University of Copenhagen, Denmark
,
Shengdong (Shen) Zhao
National University of Singapore, Singapore
,
Briane Paul Samson
Future University Hakodate, Japan & De La Salle University, Philippines
,
Rafal Kocielnik
University of Washington, USA

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 April 2020

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

German Ministry of Education and Research (BMBF)

Conference

CHI '20

Sponsor:

SIGCHI

CHI '20: CHI Conference on Human Factors in Computing Systems

April 25 - 30, 2020

HI, Honolulu, USA

Acceptance Rates

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

Upcoming Conference

CHI 2025

Sponsor:
sigchi

ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

38
Total Citations
View Citations
1,050
Total Downloads

Downloads (Last 12 months)161
Downloads (Last 6 weeks)16

Reflects downloads up to 11 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Desjardins ABenabdallah GKaneko M(2024)Un/Making Data Imaginaries: The Data EpicsACM Transactions on Computer-Human Interaction10.1145/368526931:6(1-38)Online publication date: 14-Aug-2024
https://dl.acm.org/doi/10.1145/3685269
Bailey GSeunarine KBaptista De Lima CCarnie MHaymoor ZHyde MJones BJones MPearson JReitmaier TRobinson SSahoo DWilliams A(2024)Older Generation: Self-Powered IoTs, Home-Life and “Ageing Well”Proceedings of the 13th Nordic Conference on Human-Computer Interaction10.1145/3679318.3685410(1-14)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3679318.3685410
Yan DBourgeois JKortuem G(2024)Say You, Say Me: Investigating the Personal insights Generated from One's Own data and Other's dataProceedings of the 13th Nordic Conference on Human-Computer Interaction10.1145/3679318.3685345(1-14)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3679318.3685345
Toebosch RBerger ALallemand C(2024)Non-judgmental Interfaces: A New Design Space for Personal InformaticsCompanion Publication of the 2024 ACM Designing Interactive Systems Conference10.1145/3656156.3663706(166-170)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3656156.3663706
Gómez Ortega ABourgeois JKortuem G(2024)Sensitive Data Donation: A Feminist Reframing of Data Practices for Intimate Research ContextsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661524(2420-2434)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661524
Gómez Ortega ABourgeois JKortuem G(2024)Participation in Data Donation: Co-Creative, Collaborative, and Contributory Engagements with Athletes and their Intimate DataProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661503(2388-2402)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661503
Jain PXu ADownes TKim IKhan TBiehl JLee A(2024)Understanding Perceived Utility and Comfort of In-Home General-Purpose Sensing through Progressive ExposureProceedings of the ACM on Human-Computer Interaction10.1145/36374328:CSCW1(1-32)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637432
Lee HJung YShin YPark HChoi WLee U(2024)FamilyScope: Visualizing Affective Aspects of Family Social Interactions using Passive Sensor DataProceedings of the ACM on Human-Computer Interaction10.1145/36373348:CSCW1(1-27)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637334
Taylor NChatting DRogers JCiolfi LHogan TDöring TJenkins Tvan Dijk JHuron SLi ZCoyle DSigner B(2024)Data Probes: Reflecting on Connected Devices with Technology-Mediated ProbesProceedings of the Eighteenth International Conference on Tangible, Embedded, and Embodied Interaction10.1145/3623509.3633380(1-13)Online publication date: 11-Feb-2024
https://dl.acm.org/doi/10.1145/3623509.3633380
Brombacher HVan Koningsbruggen RVos SHouben SCiolfi LHogan TDöring TJenkins Tvan Dijk JHuron SLi ZCoyle DSigner B(2024)SensorBricks: a Collaborative Tangible Sensor Toolkit to Support the Development of Data LiteracyProceedings of the Eighteenth International Conference on Tangible, Embedded, and Embodied Interaction10.1145/3623509.3633378(1-17)Online publication date: 11-Feb-2024
https://dl.acm.org/doi/10.1145/3623509.3633378
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Table of Contents