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Methods and a Research Agenda for the Evaluation of Event Sequence Visualization Techniques

Ruddle, Roy A. and Bernard, Jürgen and May, Thorsten and Lücke-Tieke, Hendrik and Kohlhammer, Jörn (2016):
Methods and a Research Agenda for the Evaluation of Event Sequence Visualization Techniques.
In: IEEE VIS 2016 Workshop on Temporal and Sequential Event Analysis, [Conference or Workshop Item]

Abstract

The present paper asks how can visualization help data scientists make sense of event sequences, and makes three main contributions. The first is a research agenda, which we divide into methods for presentation, interaction & computation, and scale-up. Second, we introduce the concept of Event Maps to help with scale-up, and illustrate coarse-, medium- and fine-grained Event Maps with electronic health record (EHR) data for prostate cancer. Third, in an experiment we investigated participants' ability to judge the similarity of event sequences. Contrary to previous research into categorical data, color and shape were better than position for encoding event type. However, even with simple sequences (5 events of 3 types in the target sequence), participants only got 88 correct despite averaging 7.4 seconds to respond. This indicates that simple visualization techniques are not effective.

Item Type: Conference or Workshop Item
Erschienen: 2016
Creators: Ruddle, Roy A. and Bernard, Jürgen and May, Thorsten and Lücke-Tieke, Hendrik and Kohlhammer, Jörn
Title: Methods and a Research Agenda for the Evaluation of Event Sequence Visualization Techniques
Language: English
Abstract:

The present paper asks how can visualization help data scientists make sense of event sequences, and makes three main contributions. The first is a research agenda, which we divide into methods for presentation, interaction & computation, and scale-up. Second, we introduce the concept of Event Maps to help with scale-up, and illustrate coarse-, medium- and fine-grained Event Maps with electronic health record (EHR) data for prostate cancer. Third, in an experiment we investigated participants' ability to judge the similarity of event sequences. Contrary to previous research into categorical data, color and shape were better than position for encoding event type. However, even with simple sequences (5 events of 3 types in the target sequence), participants only got 88 correct despite averaging 7.4 seconds to respond. This indicates that simple visualization techniques are not effective.

Uncontrolled Keywords: Guiding Theme: Digitized Work, Guiding Theme: Individual Health, Guiding Theme: Smart City, Research Area: Computer graphics (CG), Research Area: Human computer interaction (HCI), Visual analytics, Information visualization, Event sequence visualization, Event sequence comparison, Evaluation, User study
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: IEEE VIS 2016 Workshop on Temporal and Sequential Event Analysis
Date Deposited: 07 May 2019 08:53
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