Deep Personalization in Tools for Reflection

Aseniero, B., Carpendale, S., and Tang, A. (2012). Deep Personalization in Tools for Reflection. In Personal Informatics in Practice: Improving Quality of Life Through Data - Workshop at CHI 2012.

Abstract

Personal informatics (PI) tools that support reflection are ``personalized'' insofar as the data consists of an individual's data. Typically, this data is presented in visualizations that are generic and non-individuated. In this paper, we argue for deep personalization, where the visualizations are constructed by individuals. Such functionality gives individuals the power to build visualizations that are personally meaningful, allowing them to meet and address personal needs. We illustrate the power of this approach by considering a case study of the design of a multi-faceted reflection tool. Reflecting on the deep personalization of the design process, we propose an approach that will allow individuals to personalize their own visualizations.

Materials

PDF File (http://hcitang.org/papers/2012-chi2012workshop-deep-personalization.pdf)

Keywords

Deep personalization, Self-awareness, Aesthetic Design, Information Visualization, Feedback techniques

BibTeX

@inproceedings{aseniero2012deeppersonalization,
  year = {2012},
  type = {workshop},
  title = {Deep Personalization in Tools for Reflection},
  pdfurl = {http://hcitang.org/papers/2012-chi2012workshop-deep-personalization.pdf},
  keywords = {Deep personalization, Self-awareness, Aesthetic Design, Information
Visualization, Feedback techniques},
  editor = {Ian Li and Yevgeniy Medynskiy and Jon Froehlich and Jakob Eg Larsen},
  date-modified = {2014-01-18 23:23:16 +0000},
  date-added = {2014-01-18 23:19:27 +0000},
  booktitle = {Personal Informatics in Practice: Improving Quality of Life Through
Data - Workshop at CHI 2012},
  author = {Aseniero, Bon Adriel and Carpendale, Sheelagh and Tang, Anthony},
  abstract = {Personal informatics (PI) tools that support reflection are ``personalized''
insofar as the data consists of an individual's data. Typically, this data
is presented in visualizations that are generic and non-individuated. In this
paper, we argue for deep personalization, where the visualizations are constructed
by individuals. Such functionality gives individuals the power to build visualizations
that are personally meaningful, allowing them to meet and address personal
needs. We illustrate the power of this approach by considering a case study
of the design of a multi-faceted reflection tool. Reflecting on the deep personalization
of the design process, we propose an approach that will allow individuals to
personalize their own visualizations.},
}