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A System to Visualize Quantified Self Data Using Avatars
Linnaeus University, Faculty of Technology, Department of Media Technology.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
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 visit, the music they listen to, and pictures they take. These data are used by the services for various purposes, but usually there are limitations for the users to explore or interact with them. This 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.

This thesis discusses the feasibility of creating a system that allows users to connect the activity tracking applications they already use, analyse the amount of activities, and then present the resulting information. The visualization of the information is done with 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
2015. , 101 p.
Keyword [en]
Quantified Self, Avatars, Data Visualization, Social Networks, Wearables, Mashup
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:lnu:diva-47219OAI: oai:DiVA.org:lnu-47219DiVA: diva2:869026
Subject / course
Media Technology
Educational program
Social Media and Web Technologies, Master Programme, 120 credits
Supervisors
Examiners
Available from: 2015-11-16 Created: 2015-11-12 Last updated: 2018-01-10Bibliographically approved

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ASystemToVisualizeQuantifiedSelfDataUsingAvatars.pdf(9532 kB)154 downloads
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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • 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
  • rtf