The University of Southampton
University of Southampton Institutional Repository

Revealing Visualization Insights from Quantified-Selfers' Personal Data Presentations.

Choe, Eun Kyoung, Lee, Bongshin and schraefel, m.c. (2015) Revealing Visualization Insights from Quantified-Selfers' Personal Data Presentations. IEEE Computer Graphics and Applications

Record type: Article


Data visualization and analytics research has great potential to empower people to improve their lives by leveraging their own personal data. However, most Quantified-Selfers are neither visualization experts nor data scientists. Consequently, their visualizations of their data are often not ideal for conveying their insights. Aiming to design a visualization system to help non-experts explore and present their personal data, we conducted a pre-design empirical study. Through the lens of Quantified-Selfers, we examined what insights people gain specifically from their personal data and how they use visualizations to communicate their insights. Based on our analysis of 30 Quantified Self presentations, we characterized eight insight types (detail, self-reflection, trend, comparison, correlation, data summary, distribution, outlier) and mapped the visual annotations used to communicate them. We further discussed four areas for the design of personal visualization systems, including support for encouraging self-reflection, gaining valid insight, communicating insight, and using visual annotations.

Full text not available from this repository.

More information

Published date: May 2015
Organisations: Agents, Interactions & Complexity


Local EPrints ID: 405295
PURE UUID: 8e6be94c-cce8-4d0f-82be-0fcb38b48b9d

Catalogue record

Date deposited: 31 Jan 2017 12:15
Last modified: 24 Jul 2017 16:36

Export record


Author: Eun Kyoung Choe
Author: Bongshin Lee
Author: m.c. schraefel

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.