TY - GEN
T1 - LifeFlow
T2 - Visualizing an overview of event sequences
AU - Wongsuphasawat, Krist
AU - Gómez, John Alexis Guerra
AU - Plaisant, Catherine
AU - Wang, Taowei David
AU - Ben, Shneiderman
AU - Taieb-Maimon, Meirav
PY - 2011/1/1
Y1 - 2011/1/1
N2 - Event sequence analysis is an important task in many domains: medical researchers may study the patterns of transfers within the hospital for quality control; transportation experts may study accident response logs to identify best practices. In many cases they deal with thousands of records. While previous research has focused on searching and browsing, overview tasks are often overlooked. We introduce a novel interactive visual overview of event sequences called LifeFlow. LifeFlow is scalable, can summarize all possible sequences, and represents the temporal spacing of the events within sequences. Two case studies with healthcare and transportation domain experts are presented to illustrate the usefulness of LifeFlow. A user study with ten participants confirmed that after 15 minutes of training novice users were able to rapidly answer questions about the prevalence and temporal characteristics of sequences, find anomalies, and gain significant insight from the data.
AB - Event sequence analysis is an important task in many domains: medical researchers may study the patterns of transfers within the hospital for quality control; transportation experts may study accident response logs to identify best practices. In many cases they deal with thousands of records. While previous research has focused on searching and browsing, overview tasks are often overlooked. We introduce a novel interactive visual overview of event sequences called LifeFlow. LifeFlow is scalable, can summarize all possible sequences, and represents the temporal spacing of the events within sequences. Two case studies with healthcare and transportation domain experts are presented to illustrate the usefulness of LifeFlow. A user study with ten participants confirmed that after 15 minutes of training novice users were able to rapidly answer questions about the prevalence and temporal characteristics of sequences, find anomalies, and gain significant insight from the data.
KW - Temporal categorical data
KW - Timestamped event sequences
UR - http://www.scopus.com/inward/record.url?scp=79958158585&partnerID=8YFLogxK
U2 - 10.1145/1978942.1979196
DO - 10.1145/1978942.1979196
M3 - Conference contribution
AN - SCOPUS:79958158585
SN - 9781450302289
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 1747
EP - 1756
BT - CHI 2011 - 29th Annual CHI Conference on Human Factors in Computing Systems, Conference Proceedings and Extended Abstracts
PB - Association for Computing Machinery
ER -