Ruddle, Roy A. ; Bernard, Jürgen ; May, Thorsten ; Lücke-Tieke, Hendrik ; Kohlhammer, Jörn (2016)
Methods and a Research Agenda for the Evaluation of Event Sequence Visualization Techniques.
IEEE VIS 2016 Workshop on Temporal and Sequential Event Analysis.
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (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.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2016 |
| Autor(en): | Ruddle, Roy A. ; Bernard, Jürgen ; May, Thorsten ; Lücke-Tieke, Hendrik ; Kohlhammer, Jörn |
| Art des Eintrags: | Bibliographie |
| Titel: | Methods and a Research Agenda for the Evaluation of Event Sequence Visualization Techniques |
| Sprache: | Englisch |
| Publikationsjahr: | 2016 |
| Veranstaltungstitel: | IEEE VIS 2016 Workshop on Temporal and Sequential Event Analysis |
| Kurzbeschreibung (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. |
| Freie Schlagworte: | 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 |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
| Hinterlegungsdatum: | 07 Mai 2019 08:53 |
| Letzte Änderung: | 07 Mai 2019 08:53 |
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