Talk, text, tag? Understanding self-annotation of smart home data from a user’s perspective

Emma L. Tonkin*, Alison Burrows, Przemyslaw R Woznowski, Pawel Laskowski, Kristina Yordanova, Niall Twomey, Ian Craddock

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

14 Citations (Scopus)
401 Downloads (Pure)


Delivering effortless interactions and appropriate interventions through pervasive systems requires making sense of multiple streams of sensor data. This is particularly challenging when these concern people’s natural behaviours in the real world. This paper takes a multidisciplinary perspective of annotation and draws on an exploratory study of 12 people, who were encouraged to use a multi-modal annotation app while living in a prototype smart home. Analysis of the app usage data and of semi-structured interviews with the participants revealed strengths and limitations regarding self-annotation in a naturalistic context. Handing control of the annotation process to research participants enabled them to reason about their own data, while generating accounts that were appropriate and acceptable to them. Self-annotation provided participants an opportunity to reflect on themselves and their routines, but it was also a means to express themselves freely and sometimes even a backchannel to communicate playfully with the researchers. However, self-annotation may not be an effective way to capture accurate start and finish times for activities, or location associated with activity information. This paper offers new insights and recommendations for the design of self-annotation tools for deployment in the real world.

Original languageEnglish
Article number2365
Number of pages22
Issue number7
Early online date20 Jul 2018
Publication statusPublished - Jul 2018

Structured keywords

  • Digital Health


  • Activity logging
  • Ground-truth acquisition
  • Labelling
  • Location
  • Naturalistic data
  • NFC
  • Self-annotation
  • Smart homes


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