Evaluating the Effect of Timeline Shape on Visualization Task Performance

dc.contributor.authorDi Bartolomeo, Sara
dc.contributor.authorPandey, Aditeya
dc.contributor.authorLeventidis, Aristotelis
dc.contributor.authorSaffo, David
dc.contributor.authorSyeda, Uzma Haque
dc.contributor.authorCarstensdottir, Elin
dc.contributor.authorSeif El-Nasr, Magy
dc.contributor.authorBorkin, Michelle A.
dc.contributor.authorDunne, Cody
dc.contributor.departmentDepartment of Computer Science
dc.date.accessioned2026-11-11T09:46:01Z
dc.date.available2026-11-11T09:46:01Z
dc.date.issued2020-04-21
dc.descriptionPublisher Copyright: © 2020 ACM.en
dc.description.abstractTimelines are commonly represented on a horizontal line, which is not necessarily the most effective way to visualize temporal event sequences. However, few experiments have evaluated how timeline shape influences task performance. We present the design and results of a controlled experiment run on Amazon Mechanical Turk (n=192) in which we evaluate how timeline shape affects task completion time, correctness, and user preference. We tested 12 combinations of 4 shapes - - horizontal line, vertical line, circle, and spiral A- and 3 data types A- recurrent, non-recurrent, and mixed event sequences. We found good evidence that timeline shape meaningfully affects user task completion time but not correctness and that users have a strong shape preference. Building on our results, we present design guidelines for creating effective timeline visualizations based on user task and data types. A free copy of this paper, the evaluation stimuli and data, and code are available https://osf.io/qr5yu/en
dc.description.versionPeer revieweden
dc.format.extent1247683
dc.format.extent
dc.format.extent
dc.identifier.citationDi Bartolomeo, S, Pandey, A, Leventidis, A, Saffo, D, Syeda, U H, Carstensdottir, E, Seif El-Nasr, M, Borkin, M A & Dunne, C 2020, Evaluating the Effect of Timeline Shape on Visualization Task Performance. in CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems., 3376237, Conference on Human Factors in Computing Systems - Proceedings, Association for Computing Machinery, 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020, Honolulu, United States, 25/04/20. https://doi.org/10.1145/3313831.3376237en
dc.identifier.citationconferenceen
dc.identifier.doi10.1145/3313831.3376237
dc.identifier.isbn9781450367080
dc.identifier.other251597420
dc.identifier.other45d9adec-a97d-49cf-9aeb-b86fce6bf794
dc.identifier.other85091280783
dc.identifier.urihttps://hdl.handle.net/20.500.11815/9058
dc.language.isoen
dc.publisherAssociation for Computing Machinery
dc.relation.ispartofseriesCHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems; ()en
dc.relation.ispartofseriesConference on Human Factors in Computing Systems - Proceedings; ()en
dc.relation.urlhttps://www.scopus.com/pages/publications/85091280783en
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.subjectcontrolled experimentsen
dc.subjectinformation visualizationen
dc.subjecttemporal event sequencesen
dc.subjecttimelinesen
dc.subjectSoftwareen
dc.subjectHuman-Computer Interactionen
dc.subjectComputer Graphics and Computer-Aided Designen
dc.titleEvaluating the Effect of Timeline Shape on Visualization Task Performanceen
dc.type/dk/atira/pure/researchoutput/researchoutputtypes/contributiontobookanthology/conferenceen

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