Datawear: Self-reflection on the go or how to ethically use wearable cameras for research

Anya Skatova, Victoria E. Shipp, Lee Spacagna, Benjamin Bedwell, Ahmad Beltagui, Tom Rodden

Research output: Chapter in Book/Published conference outputConference publication

Abstract

A growing number of studies use wearable sensors, including cameras, to detect user activity patterns. When an object of academic investigation, these patterns are interpreted by researchers and conclusions are drawn about people's habits and routines. Alternatively, interpretations are provided by users themselves during extensive post-study interviews. Such approaches inevitably expose personal data collected about individuals to researchers, which can potentially change the behavior under investigation. We introduce a new approach to using wearable sensor data in research. It allows people to interpret and selfreflect on their data and submit for investigation only reflections, without sharing their raw data. In this interactivity, we present and discuss the Datawear mobile application prototype, which is designed to conduct "in the wild" studies of personal experiences.

Original languageEnglish
Title of host publicationCHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationCrossings
PublisherACM
Pages323-326
Number of pages4
ISBN (Electronic)9781450331463
DOIs
Publication statusPublished - 18 Apr 2015
Event33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015 - Seoul, Korea, Republic of
Duration: 18 Apr 201523 Apr 2015

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
Volume18

Conference

Conference33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015
Country/TerritoryKorea, Republic of
CitySeoul
Period18/04/1523/04/15

Bibliographical note

Funding Information:
The study is supported by Horizon Digital Economy Research (Research Councils UK grant EP/G065802/1).

Keywords

  • Ethics
  • Experience sampling
  • Self-reflection
  • Sensors
  • Wearable cameras

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