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Visualizing Quantified Self Data Using Avatars
Linnaeus University, Faculty of Technology, Department of Media Technology.
Linnaeus University, Faculty of Technology, Department of Media Technology.ORCID iD: 0000-0003-4162-6475
Linnaeus University, Faculty of Technology, Department of Media Technology.ORCID iD: 0000-0002-6893-0461
2016 (English)In: ACHI 2016: The Ninth International Conference on Advances in Computer-Human Interactions / [ed] Alma Leora Culén, Leslie Miller, Irini Giannopulu, and Birgit Gersbeck-Schierholz, International Academy, Research and Industry Association (IARIA), 2016, 57-66 p.Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, it is becoming more common for people to use applications or devices that keep track of their activities, such as fitness activities, places they visited, the music they listen to, and pictures they took. These data are used by the services for various purposes, but usually there are limitations for the users to explore or interact with them. Our project investigates a new approach of visualizing such Quantified Self data, in a meaningful and enjoyable way that gives the users insights into their data. The paper discusses the feasibility of creating a service that allows users to connect the activity tracking applications they already use, analyse the amount of activities, and then presents them the resulting information. The visualization of the information is proposed as an avatar that maps the different activities the user is engaged with, along with the activity levels, as graphical features. Within the scope of this work, several user studies were conducted and a system prototype was implemented to explore how to build, using web technologies, such a system that aggregates and analyses personal activity data, and also to determine what kind of data should and can be collected, to provide meaningful information to the users. Furthermore, it was investigated how a possible design for the avatar could look like, to be clearly understood by the users.

Place, publisher, year, edition, pages
International Academy, Research and Industry Association (IARIA), 2016. 57-66 p.
Keyword [en]
Quantified Self, Avatars, Data Visualization
National Category
Media and Communication Technology
Research subject
Computer and Information Sciences Computer Science, Media Technology; Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-52381ISBN: 978-1-61208-468-8 (print)OAI: oai:DiVA.org:lnu-52381DiVA: diva2:926180
Conference
ACHI 2016: The Ninth International Conference on Advances in Computer-Human Interactions
Available from: 2016-05-04 Created: 2016-05-04 Last updated: 2016-05-24Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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