A Field Study of On-Calendar Visualizations

TL;DR

This study explores integrating personal feedback data into digital calendars to enhance understanding and reasoning about personal habits, revealing that calendar context aids pattern recognition and anomaly detection over an eight-week period.

Contribution

It introduces a novel on-calendar visualization approach for personal data and presents a model of behavior feedback processes based on field study insights.

Findings

Calendar context improves pattern recognition in personal data.

Users can identify anomalies more easily with on-calendar visualizations.

The study proposes a model extending existing technology adoption frameworks.

Abstract

Feedback tools help people to monitor information about themselves to improve their health, sustainability practices, or personal well-being. Yet reasoning about personal data (e.g., pedometer counts, blood pressure readings, or home electricity consumption) to gain a deep understanding of your current practices and how to change can be challenging with the data alone. We integrate quantitative feedback data within a personal digital calendar; this approach aims to make the feedback data readily accessible and more comprehensible. We report on an eight-week field study of an on-calendar visualization tool. Results showed that a personal calendar can provide rich context for people to reason about their feedback data. The on-calendar visualization enabled people to quickly identify and reason about regular patterns and anomalies. Based on our results, we also derived a model of the behavior feedback process that extends existing technology adoption models. With that, we reflected on potential barriers for the ongoing use of feedback tools.