Publication Type
Journal Article
Version
publishedVersion
Publication Date
3-2015
Abstract
Data surrounds each and every one of us in our daily lives, ranging from exercise logs, to archives of our interactions with others on social media, to online resources pertaining to our hobbies. There is enormous potential for us to use these data to understand ourselves better and make positive changes in our lives. Visualization (Vis) and visual analytics (VA) offer substantial opportunities to help individuals gain insights about themselves, their communities and their interests; however, designing tools to support data analysis in non-professional life brings a unique set of research and design challenges. We investigate the requirements and research directions required to take full advantage of Vis and VA in a personal context. We develop a taxonomy of design dimensions to provide a coherent vocabulary for discussing personal visualization and personal visual analytics. By identifying and exploring clusters in the design space, we discuss challenges and share perspectives on future research. This work brings together research that was previously scattered across disciplines. Our goal is to call research attention to this space and engage researchers to explore the enabling techniques and technology that will support people to better understand data relevant to their personal lives, interests, and needs.
Keywords
interaction design, Mobile and ubiquitous visualization, personal context, Taxonomy
Discipline
Graphics and Human Computer Interfaces
Research Areas
Information Systems and Management
Publication
IEEE Transactions on Visualization and Computer Graphics
Volume
21
Issue
3
First Page
420
Last Page
433
ISSN
1077-2626
Identifier
10.1109/TVCG.2014.2359887
Publisher
Institute of Electrical and Electronics Engineers
Citation
HUANG, Dandan; TORY, Melanie; ASENIERO, Bon Adriel; BARTRAM, Lyn; BATEMAN, Scott; CARPEDALE, Sheelagh; TANG, Anthony; and WOODBURY, Robert.
Personal visualization and personal visual analytics. (2015). IEEE Transactions on Visualization and Computer Graphics. 21, (3), 420-433.
Available at: https://ink.library.smu.edu.sg/sis_research/7996
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/TVCG.2014.2359887