Abstract
Many different types of data are related to time. Meteorological data, financial data, census data, medical data, simulation data, news articles, photo collections, or project plans, to name only a few examples, all contain temporal information. In theory, because all these data are time-oriented, they should be representable with one and the same visualization approach. In practice, however, the data exhibit specific characteristics and hence each of the above examples requires a dedicated visualization.
Chapter PDF
References
Aigner, W., C. Kainz, R. Ma, and S. Miksch. 2011. BertinWas Right: An Empirical Evaluation of Indexing to Compare Multivariate Time-Series Data Using Line Plots. Computer Graphics Forum 30 (1): 215–228. https://doi.org/10.1111/j.1467-8659.2010.01845.x.
Aigner, W., S. Miksch, W. Müller, H. Schumann, and C. Tominski. 2007. Visualizing Time-Oriented Data - A Systematic View. Computers & Graphics 31 (3): 401–409. https://doi.org/10.1016/j.cag.2007.01.030.
Aigner, W., S. Miksch, W. Müller, H. Schumann, and C. Tominski. 2008. Visual Methods for AnalyzingTime-Oriented Data. IEEE Transactions onVisualization and Computer Graphics 14 (1): 47–60. https://doi.org/10.1109/TVCG.2007.70415.
Aigner, W., S. Miksch, B. Thurnher, and S. Biffl. 2005. PlanningLines: Novel Glyphs for Representing Temporal Uncertainties and Their Evaluation. In Proceedings of the International Conference Information Visualisation (IV), 457–463. IEEE Computer Society. https://doi.org/10.1109/IV.2005.97.
Albers, D., M. Correll, and M. Gleicher. 2014. Task-Driven Evaluation of Aggregation in Time Series Visualization. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI), 551–560. ACM Press. https://doi.org/10.1145/2556288.2557200.
Andrienko, N., and G. Andrienko. 2006. Exploratory Analysis of Spatial and Temporal Data. Berlin: Springer. https://doi.org/10.1007/3-540-31190-4.
Bach, B., P. Dragicevic, D.W. Archambault, C. Hurter, and S. Carpendale. 2017. A Descriptive Framework for Temporal Data Visualizations Based on Generalized Space-Time Cubes. Computer Graphics Forum 36 (6): 36–61. https://doi.org/10.1111/cgf.12804.
Bai, Z., Y. Tao, and H. Lin. 2020. Time-varying Volume Visualization: A Survey. Journal of Visualization 23 (5): 745–761. https://doi.org/10.1007/s12650-020-00654-x.
Beck, F., M. Burch, S. Diehl, and D. Weikopf. 2017. A Taxonomy and Survey of Dynamic Graph Visualization. Computer Graphics Forum 36 (1): 133–159. https://doi.org/10.1111/cgf.12791.
Been, K., E. Daiches, and C.-K. Yap. 2006. Dynamic Map Labeling. IEEE Transactions on Visualization and Computer Graphics 12 (5): 773–780. https://doi.org/10.1109/TVCG.2006.136.
Bergman, L., B.E. Rogowitz, and L.A. Treinish. 1995. A Rule-based Tool for Assisting Colormap Selection. In Proceedings of the IEEE Visualization Conference (Vis), 118–125. IEEE Computer Society. https://doi.org/10.1109/VISUAL.1995.480803.
Bernard, J., M. Steiger, S. Mittelstädt, S. Thum, D.A. Keim, and J. Kohlhammer. 2015. A Survey and Task-based Quality Assessment of Static 2D Colormaps. In Proceedings of the Conference on Visualization and Data Analysis (VDA), vol. 9397. SPIE Proceedings. SPIE. https://doi.org/10.1117/12.2079841.
Bertin, J. 1983. Semiology of Graphics: Diagrams, Networks. Maps. Translated by William J. Berg: University of Wisconsin Press.
Borland, D., and R.M. Taylor. 2007. Rainbow Color Map (Still) Considered Harmful. IEEE Computer Graphics and Applications 27 (2): 14–17. https://doi.org/10.1109/mcg.2007.323435.
Bors, C., C. Eichner, S. Miksch, C. Tominski, H. Schumann, and T. Gschwandtner. 2020. Exploring Time Series Segmentations Using Uncertainty and Focus+ Context Techniques. In Proceedings of the Eurographics / IEEE Conference on Visualization (EuroVis) - Short Papers, 7–11. Eurographics Association. https://doi.org/10.2312/evs.20201040.
Card, S., J. Mackinlay, and B. Shneiderman. 1999. Readings in Information Visualization: Using Vision to Think. Burlington: Morgan Kaufmann Publishers.
Ceneda, D., T. Gschwandtner, S. Miksch, and C. Tominski. 2018. Guided Visual Exploration of Cyclical Patterns in Time-series. In Proceedings of the IEEE Symposium on Visualization in Data Science (VDS). IEEE Computer Society.
Claessen, J.H.T., and J.J. van Wijk. 2011. Flexible Linked Axes for Multivariate Data Visualization. IEEE Transactions on Visualization and Computer Graphics 17 (12): 2310–2316. https://doi.org/10.1109/TVCG.2011.201.
Cleveland, W.S., M.E. McGill, and R. McGill. 1988. The Shape Parameter of a Two-Variable Graph. Journal of the American Statistical Association 83 (402): 289–300. https://doi.org/10.1080/01621459.1988.10478598.
Constantine, L.L. 2003. CanonicalAbstract Prototypes forAbstractVisual and Interaction Design. In Interactive Systems: Design, Specification, and Verification, ed. J. Jorge, N.J. Nunes, and J.F. e Cunha, vol. 2844, 1–15. Lecture Notes in Computer Science. Springer. https://doi.org/10.1007/978-3-540-39929-2_1.
Courage, C., and K. Baxter. 2005. Understanding Your Users. Burlington: Morgan Kaufmann. https://doi.org/10.1016/B978-1-55860-935-8.X5029-5.
Daassi, C., L. Nigay, and M.-C. Fauvet. 2005. A Taxonomy of Temporal Data Visualization Techniques. In Interaction Information Intelligence 5 (2), 41–63. https://www.irit.fr/journal-i3/volume05/numero02/revue_i3_05_02_02.pdf.
Draper, G.M., Y. Livnat, and R.F. Riesenfeld. 2009. A Survey of Radial Methods for Information Visualization. IEEE Transactions on Visualization and Computer Graphics 15 (5): 759–776. https://doi.org/10.1109/TVCG.2009.23.
Dübel, S., M. Röhlig, H. Schumann, and M. Trapp. 2014. 2D and 3D Presentation of Spatial Data: A Systematic Review. In Proceedings of the International Workshop on 3DVis (3DVis@IEEE VIS), 11–18. IEEE Computer Society. https://doi.org/10.1109/3DVis.2014.7160094.
Elmqvist, N., and P. Tsigas. 2007. A Taxonomy of 3D Occlusion Management Techniques. In Proceedings of the IEEE Conference on Virtual Reality (VR), 51–58. IEEE Computer Society. https://doi.org/10.1109/vr.2007.352463.
Fang, Y., H. Xu, and J. Jiang. 2020. A Survey of Time Series Data Visualization Research. In IOP Conference Series: Materials Science and Engineering, vol 782. https://doi.org/10.1088/1757-899x/782/2/022013.
Farquhar, A.B., and H. Farquhar. 1891. Economic and Industrial Solutions. New York: G. B. Putnam’s Sons.
Fuchs, G., and H. Schumann. 2004. Intelligent Icon Positioning for Interactive Map-Based Information Systems. In Proceedings of the International Conference of the Information Resources Management Association (IRMA), 261–264. Idea Group Inc. https://www.irma-international.org/proceeding-paper/intelligent-icon-positioning-interactivemap/32349/.
Fuchs, J., F. Fischer, F. Mansmann, E. Bertini, and P. Isenberg. 2013. Evaluation of Alternative Glyph Designs for Time Series Data in a Small Multiple Setting. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI), 3237–3246. ACM Press. https://doi.org/10.1145/2470654.2466443.
Gapminder Foundation. 2021. Gapminder Tools. https://www.gapminder.org/tools.
Gschwandtner, T., M. Bögl, P. Federico, and S. Miksch. 2016. Visual Encodings of Temporal Uncertainty: A Comparative User Study. IEEE Transactions on Visualization and Computer Graphics 22 (1): 539–548. https://doi.org/10.1109/TVCG.2015.2467752.
Hackos, J.T., and J.C. Redish. 1998. User and Task Analysis for Interface Design. New York: Wiley.
Hall, K.W., C. Perin, P.G. Kusalik, C. Gutwin, and S. Carpendale. 2014. Formalizing Emphasis in Information Visualization. Computer Graphics Forum 35 (3): 717–737. https://doi.org/10.1111/cgf.12936.
Harris, R.L. 1999. Information Graphics: A Comprehensive Illustrated Reference. Oxford: Oxford University Press. https://global.oup.com/academic/product/information-graphics-9780195135329.
Harrower, M.A., and C.A. Brewer. 2003. ColorBrewer.org: An Online Tool for Selecting Color Schemes for Maps. The Cartographic Journal 40 (1): 27–37. https://doi.org/10.4324/9781351191234-18.
Havre, S., E. Hetzler, and L. Nowell. 2000. ThemeRiver: Visualizing Theme Changes Over Time. In Proceedings of the IEEE Symposium Information Visualization(InfoVis), 115–124. IEEE Computer Society. https://doi.org/10.1109/INFVIS.2000.885098.
Havre, S., E. Hetzler, P. Whitney, and L. Nowell. 2002. ThemeRiver: Visualizing Thematic Changes in Large Document Collections. IEEE Transactions on Visualization and Computer Graphics 8 (1): 9–20. https://doi.org/10.1109/2945.981848.
Healey, C.G., and J.T. Enns. 2012. Attention and Visual Memory in Visualization and Computer Graphics. IEEE Transactions on Visualization and Computer Graphics 18 (7): 1170–1188. https://doi.org/10.1109/TVCG.2011.127.
Heer, J., and M. Agrawala. 2006. Multi-Scale Banking to 45 Degrees. IEEE Transactions on Visualization and Computer Graphics 12 (5): 701–708. https://doi.org/10.1109/TVCG.2006.163.
Inselberg, A., and B. Dimsdale. 1990. Parallel Coordinates: A Tool for Visualizing Multi-Dimensional Geometry. In Proceedings of the IEEE Visualization Conference (Vis), 361–378. IEEE Computer Society. https://doi.org/10.1109/VISUAL.1990.146402.
Jabbari, A., R. Blanch, and S. Dupuy-Chessa. 2018. Composite Visual Mapping for Time Series Visualization. In Proceedings of the IEEE Pacific Visualization Symposium (PacificVis), 116–124. IEEE. https://doi.org/10.1109/PacificVis.2018.00023
Knight, D., B. Knight, M. Pearson, and M. Quintana. 2018. Microsoft Power BI Quick Start Guide: Build Dashboards and Visualizations to Make Your DataCome to Life, 1st ed. Birmingham: Packt Publishing. https://www.packtpub.com/product/microsoft-power-bi-quick-start-guide/9781789138221.
Kraak, M.-J. 2003. The Space-Time Cube Revisited from a Geovisualization Perspective. In Proceedings of the 21st International Cartographic Conference (ICC), 1988–1996. The International Cartographic Association (ICA). https://icaci.org/files/documents/ICC_proceedings/ICC2003/Papers/255.pdf.
Kraus, M., K. Klein, J. Fuchs, D.A. Keim, F. Schreiber, M. Sedlmair, and T.-M. Rhyne. 2021. The Value of Immersive Visualization. IEEE Computer Graphics and Applications 41 (4): 125–132. https://doi.org/10.1109/MCG.2021.3075258.
Kristensson, P.O., N. Dahlback, D. Anundi, M. Bjornstad, H. Gillberg, J. Haraldsson, I. Martensson, M. Nordvall, and J. Stahl. 2009. An Evaluation of Space Time Cube Representation of Spatiotemporal Patterns. IEEE Transactions on Visualization and Computer Graphics 15 (4): 696–702. https://doi.org/10.1109/TVCG.2008.194.
Loth, A. 2019. Visual Analytics with Tableau. New York: Wiley. https://doi.org/10.1002/9781119561996.
Luboschik, M., H. Schumann, and H. Cords. 2008. Particle-Based Labeling: Fast Point-feature Labeling Without Obscuring Other Visual Features. IEEE Transactions on Visualization and Computer Graphics 14 (6): 1237–1244. https://doi.org/10.1109/tvcg.2008.152.
MacEachren, A.M. 1995. How Maps Work: Representation, Visualization, and Design. New York: Guilford Press.
Mackinlay, J. 1986. Automating the Design of Graphical Presentations of Relational Information. ACM Transactions on Graphics 5 (2): 110–141. https://doi.org/10.1145/22949.22950.
Mairena, A., C. Gutwin, and A. Cockburn. 2022. Which Emphasis Technique to Use? Perception of Emphasis Techniques with Varying Distractors, Backgrounds, and Visualization Types. Information Visualization 21 (2): 95–129. https://doi.org/10.1177/14738716211045354.
Marriott, K., F. Schreiber, T. Dwyer, K. Klein, N.H. Riche, T. Itoh,W. Stuerzlinger, and B.H. Thomas (eds.). 2018. Immersive Analytics, vol. 11190. Lecture Notes in Computer Science. Berlin: Springer. https://doi.org/10.1007/978-3-030-01388-2.
McNabb, L., and R.S. Laramee. 2019. Multivariate Maps - A Glyph-Placement Algorithm to Support Multivariate Geospatial Visualization. Information 10 (10). https://doi.org/10.3390/info10100302.
Mittelstädt, S., D. Jäckle, F. Stoffel, and D.A. Keim. 2015. ColorCAT: Guided Design of Colormaps for Combined Analysis Tasks. In Proceedings of the Eurographics / IEEE Conference on Visualization (EuroVis) - Short Papers, 115–119. Eurographics Association. https://doi.org/10.2312/eurovisshort.20151135.
Mittelstädt, S., A. Stoffel, and D.A. Keim. 2014. Methods for Compensating Contrast Effects in Information Visualization. Computer Graphics Forum 33 (3): 231–240. https://doi.org/10.1111/cgf.12379.
Müller, W., and H. Schumann. 2003. Visualization Methods for Time-Dependent Data - An Overview. In Proceedings of Winter Simulation Conference (WSC), 737–745. IEEE Computer Society. https://doi.org/10.1109/WSC.2003.1261490.
Munzner, T. 2009. A Nested Process Model for Visualization Design and Validation. IEEE Transactions on Visualization and Computer Graphics 15 (6): 921–928. https://doi.org/10.1109/TVCG.2009.111.
Munzner, T. 2014. Visualization Analysis and Design. Natick: A K Peters/CRC Press. https://doi.org/10.1201/b17511.
Nardini, P., M. Chen, F. Samsel, R. Bujack, M. Böttinger, and G. Scheuermann. 2021. The Making of Continuous Colormaps. IEEE Transactions on Visualization and Computer Graphics 27 (6): 3048–3063. https://doi.org/10.1109/TVCG.2019.2961674.
Paternò, F., C. Mancini, and S. Meniconi. 1997. ConcurTaskTrees: A Diagrammatic Notation for Specifying Task Models. In Proceedings of IFIP TC13 International Conference on Human-Computer Interaction (INTERACT), 362–369. Springer. https://doi.org/10.1007/978-0-387-35175-9_58.
Perin, C., T. Wun, R. Pusch, and S. Carpendale. 2018. Assessing the Graphical Perception of Time and Speed on 2D+Time Trajectories. IEEE Transactions on Visualization and Computer Graphics 24 (1): 698–708. https://doi.org/10.1109/TVCG.2017.2743918.
Petzold, I. 2003. Beschriftung von Bildschirmkarten in Echtzeit. PhD thesis. Rheinische Friedrich-Wilhelms-Universität Bonn. https://hdl.handle.net/20.500.11811/1870.
Reinders, F., F.H. Post, and H.J.W. Spoelder. 2001. Visualization of Time- Dependent Data with Feature Tracking and Event Detection. The Visual Computer 17 (1): 55–71. https://doi.org/10.1007/pl00013399.
Robertson, G., R. Fernandez, D. Fisher, B. Lee, and J. Stasko. 2008. Effectiveness of Animation in Trend Visualization. IEEE Transactions on Visualization and Computer Graphics 14 (6): 1325–1332. https://doi.org/10.1109/TVCG.2008.125.
Röhlig, M., M. Luboschik, and H. Schumann. 2017. VisibilityWidgets for Unveiling Occluded Data in 3D Terrain Visualization. Journal of Visual Languages & Computing 42: 86–98. https://doi.org/10.1016/j.jvlc.2017.08.008.
Schulze-Wollgast, P., C. Tominski, and H. Schumann. 2005. Enhancing Visual Exploration by Appropriate Color Coding. In Proceedings of the International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG). University of West Bohemia, 203–210.
Silva, S., J. Madeira, and B.S. Santos. 2007. There is More to Color Scales than Meets the Eye: A Review on the Use of Color in Visualization. In Proceedings of the International Conference Information Visualisation (IV), 943–950. IEEE Computer Society. https://doi.org/10.1109/iv.2007.113.
Silva, S., B.S. Santos, and J. Madeira. 2011. Using Color in Visualization: A Survey. In Computers & Graphics 35 (2): 320–333. https://doi.org/10.1016/j.cag.2010.11.015.
Silva, S.F., and T. Catarci. 2000. Visualization of Linear Time-Oriented Data: A Survey. In Proceedings of the International Conference on Web Information Systems Engineering (WISE), 310–319. IEEE Computer Society. https://doi.org/10.1109/WISE.2000.882407
Simons, D.J., and R.A. Rensink. 2005. Change Blindness: Past, Present, and Future. Trends in Cognitive Sciences 9 (1): 16–20. https://doi.org/10.1016/j.tics.2004.11.006.
Talbot, J., J. Gerth, and P. Hanrahan. 2012. An Empirical Model of Slope Ratio Comparisons. IEEE Transactions on Visualization and Computer Graphics 18 (12): 2613–2620. https://doi.org/10.1109/TVCG.2012.196.
Telea, A.C. 2014. Data Visualization: Principles and Practice, 2nd ed. Natick: A K Peters/CRC Press. https://doi.org/10.1201/b17217.
Thompson, J.R., Z. Liu, W. Li, and J. Stasko. 2020. Understanding the Design Space and Authoring Paradigms for Animated Data Graphics. Computer Graphics Forum 39 (3): 207–218. https://doi.org/10.1111/cgf.13974.
Tominski, C., J. Abello, and H. Schumann. 2004. Axes-Based Visualizations with Radial Layouts. In Proceedings of the ACM Symposium on Applied Computing (SAC), 1242–1247. ACM Press. https://doi.org/10.1145/967900.968153.
Tominski, C., G. Fuchs, and H. Schumann. 2008. Task-Driven Color Coding. In Proceedings of the International Conference Information Visualisation (IV), 373–380. IEEE Computer Society. https://doi.org/10.1109/IV.2008.24.
Tominski, C., and H.-J. Schulz. 2012. The GreatWall of Space-Time. In Proceedings of the Workshop on Vision, Modeling & Visualization (VMV), 199–206. Eurographics Association. https://doi.org/10.2312/PE/VMV/VMV12/199-206.
Tominski, C., P. Schulze-Wollgast, and H. Schumann. 2005. 3D Information Visualization for Time Dependent Data on Maps. In Proceedings of the International Conference Information Visualisation (IV), 175–181. IEEE Computer Society. https://doi.org/10.1109/IV.2005.3.
Tominski, C., and H. Schumann. 2020. Interactive Visual Data Analysis. AK Peters Visualization Series: CRC Press. https://doi.org/10.1201/9781315152707.
Tufte, E.R. 1983. The Visual Display of Quantitative Information. Graphics Press. https://www.edwardtufte.com/tufte/books_vdqi.
Tversky, B., J.B. Morrison, and M. Betrancourt. 2002. Animation: Can It Facilitate? International Journal of Human-Computer Studies 57 (4): 247–262. https://doi.org/10.1006/ijhc.2002.1017.
Unger, A., and H. Schumann. 2009. Visual Support for the Understanding of Simulation Processes. In Proceedings of the IEEE Pacific Visualization Symposium (PacificVis), 57–64. IEEE Computer Society. https://doi.org/10.1109/PACIFICVIS.2009.4906838.
Vande Moere, A. 2004. Time-Varying Data Visualization Using Information Flocking Boids. In Proceedings of the IEEE Symposium Information Visualization (InfoVis), 97–104. IEEE Computer Society. https://doi.org/10.1109/INFVIS.2004.65.
Waldner, M., A. Karimov, and M.E. Gröller. 2017. Exploring Visual Prominence of Multi-channel Highlighting in Visualizations. In Proceedings of the Spring Conference on Computer Graphics (SCCG), 8:1–8:10. ACM Press. https://doi.org/10.1145/3154353.3154369.
Weber, M., M. Alexa, and W. Müller. 2001. Visualizing Time-Series on Spirals. In Proceedings of the IEEE Symposium Information Visualization (InfoVis), 7–14. IEEE Computer Society. https://doi.org/10.1109/INFVIS.2001.963273.
Weiss, D.J., A. Nelson, H.S. Gibson, W. Temperley, S. Peedell, A. Lieber, M. Hancher, E. Poyart, S. Belchior, N. Fullman, B. Mappin, U. Dalrymple, J. Rozier, T.C.D. Lucas, R.E. Howes, L.S. Tusting, S.Y. Kang, E. Cameron, D. Bisanzio, K.E. Battle, S. Bhatt, and P.W. Gething. 2018a. A Global Map of Travel Time to Cities to Assess Inequalities in Accessibility in 2015. Nature 553 (7688): 333–336. https://doi.org/10.1038/nature25181.
Weiss, D., H. Gibson, U. Dalrymple, J. Rozier, T. Lucas, R. Howes, L. Tusting, S. Kang, E. Cameron, K. Battle, S. Bhatt, and P. Gething. 2018b. Accessibility to Cities. https://malariaatlas.org/research-project/accessibility-to-cities/. https://malariaatlas.org/wp-content/uploads/2017/12/MAP_Accessibility_To_Cities_Press_Release.zip.
Wills, G. 2012. Visualizing Time - Designing Graphical Representations for Statistical Data. Berlin: Springer. https://doi.org/10.1007/978-0-387-77907-2.
Wolter, M., I. Assenmacher, B. Hentschel, M. Schirski, and T. Kuhlen. 2009. A Time Model for Time-Varying Visualization. Computer Graphics Forum 28 (6): 1561–1571. https://doi.org/10.1111/j.1467-8659.2008.01314.x.
Yang, J., W. Wang, and P.S. Yu. 2000. Mining Asynchronous Periodic Patterns in Time Series Data. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 275–279. ACM Press. https://doi.org/10.1145/347090.347150.
Zhou, L., and C.D. Hansen. 2016. A Survey of Colormaps in Visualization. IEEE Transactions on Visualization and Computer Graphics 22 (8): 2051–2069. https://doi.org/10.1109/TVCG.2015.2489649.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Copyright information
© 2023 The Author(s)
About this chapter
Cite this chapter
Aigner, W., Miksch, S., Schumann, H., Tominski, C. (2023). Crafting Visualizations of Time-Oriented Data. In: Visualization of Time-Oriented Data. Human–Computer Interaction Series. Springer, London. https://doi.org/10.1007/978-1-4471-7527-8_4
Download citation
DOI: https://doi.org/10.1007/978-1-4471-7527-8_4
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-7526-1
Online ISBN: 978-1-4471-7527-8
eBook Packages: Computer ScienceComputer Science (R0)