Article

Progressive multiples for communication-minded visualization

Authors:

Andreas Paepcke,

Terry WinogradAuthors Info & Claims

GI '07: Proceedings of Graphics Interface 2007

Pages 225 - 232

https://doi.org/10.1145/1268517.1268554

Published: 28 May 2007 Publication History

Abstract

This paper describes a communication-minded visualization called progressive multiples that supports both the forensic analysis and presentation of multidimensional event data. We combine ideas from progressive disclosure, which reveals data to the user on demand, and small multiples [21], which allows users to compare many images at once. Sets of events are visualized as timelines. Events are placed in temporal order on the x-axis, and a scalar dimension of the data is mapped to the y-axis. To support forensic analysis, users can pivot from an event in an existing timeline to create a new timeline of related events. The timelines serve as an exploration history, which has two benefits. First, this exploration history allows users to backtrack and explore multiple paths. Second, once a user has concluded an analysis, these timelines serve as the raw visual material for composing a story about the analysis. A narrative that conveys the analytical result can be created for a third party by copying and reordering timelines from the history. Our work is motivated by working with network security administrators and researchers in political communication. We describe a prototype that we are deploying with administrators and the results of a user study where we applied our technique to the visualization of a simulated epidemic.

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Cheng FLiu DDu FLin YZytek ALi HQu HVeeramachaneni K(2022)VBridge: Connecting the Dots Between Features and Data to Explain Healthcare ModelsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.311483628:1(378-388)Online publication date: 1-Jan-2022
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Published In

cover image ACM Other conferences

GI '07: Proceedings of Graphics Interface 2007

May 2007

352 pages

ISBN:9781568813370

DOI:10.1145/1268517

Program Chairs:
Christopher G. Healey
North Carolina State University
,
Edward Lank
University of Waterloo

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 28 May 2007

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Cited By

Cheng FLiu DDu FLin YZytek ALi HQu HVeeramachaneni K(2022)VBridge: Connecting the Dots Between Features and Data to Explain Healthcare ModelsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.311483628:1(378-388)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1109/TVCG.2021.3114836
Zakreuskaya AHapfelmeier J(2019)progViz: Visualizing Patient Journeys Based on Finite State Models2019 23rd International Conference Information Visualisation (IV)10.1109/IV.2019.00075(405-410)Online publication date: Jul-2019
https://doi.org/10.1109/IV.2019.00075
Zhao ZMarr RShaffer JElmqvist N(2019)Understanding Partitioning and Sequence in Data-Driven StorytellingInformation in Contemporary Society10.1007/978-3-030-15742-5_32(327-338)Online publication date: 13-Mar-2019
https://doi.org/10.1007/978-3-030-15742-5_32
Guimaraes VFreitas CSadre RTarouco LGranville L(2016)A Survey on Information Visualization for Network and Service ManagementIEEE Communications Surveys & Tutorials10.1109/COMST.2015.245053818:1(285-323)Online publication date: Sep-2017
https://doi.org/10.1109/COMST.2015.2450538
Wongsuphasawat KLin J(2014)Using visualizations to monitor changes and harvest insights from a global-scale logging infrastructure at Twitter2014 IEEE Conference on Visual Analytics Science and Technology (VAST)10.1109/VAST.2014.7042487(113-122)Online publication date: Oct-2014
https://doi.org/10.1109/VAST.2014.7042487
Gotz DStavropoulos H(2014)DecisionFlow: Visual Analytics for High-Dimensional Temporal Event Sequence DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2014.234668220:12(1783-1792)Online publication date: 31-Dec-2014
https://doi.org/10.1109/TVCG.2014.2346682
Inglot BLiu L(2014)Enhanced Timeline Analysis for Digital Forensic InvestigationsInformation Security Journal: A Global Perspective10.1080/19393555.2014.89740123:1-2(32-44)Online publication date: 1-Jan-2014
https://dl.acm.org/doi/10.1080/19393555.2014.897401
Zhao JDrucker SFisher DBrinkman D(2012)TimeSliceProceedings of the International Working Conference on Advanced Visual Interfaces10.1145/2254556.2254639(433-436)Online publication date: 21-May-2012
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Inglot BLiu LAntonopoulos N(2012)A Framework for Enhanced Timeline Analysis in Digital ForensicsProceedings of the 2012 IEEE International Conference on Green Computing and Communications10.1109/GreenCom.2012.50(253-256)Online publication date: 20-Nov-2012
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Wongsuphasawat KGuerra Gómez JPlaisant CWang TTaieb-Maimon MShneiderman BTan DFitzpatrick GGutwin CBegole BKellogg W(2011)LifeFlowProceedings of the SIGCHI Conference on Human Factors in Computing Systems10.1145/1978942.1979196(1747-1756)Online publication date: 7-May-2011
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