Skip to main content
Log in

Ordered small multiple treemaps for visualizing time-varying hierarchical pesticide residue data

The Visual Computer Aims and scope Submit manuscript

Abstract

Small multiples can visually enforce comparisons of changes or differences among objects, revealing potential patterns by providing different views. According to the analyzing requirements in food safety fields and characteristics of pesticide residue detection data, in this paper, we propose a novel visualization approach to explore and analyze the time-varying hierarchical data, which is called ordered small multiple treemaps (OSMT). Inspired by the thought of querying an array by rows or columns, OSMT makes it possible to locate a specific node in the treemap layout by using a unique location 2-tuple and keep a relative stable order of nodes in the layout while we detecting temporal patterns. This algorithm enables the visual representation of the node values varying with time, preserving the hierarchical relationships among nodes in the meanwhile. Based on some interaction techniques (filtering, selecting, highlighting and zooming, etc.), OSMT can help users find some specific changes more easily and thus make corresponding decisions with more efficiency. Besides, we also propose a new metric called TVA (Ability of tracking time-varying data in treemap) with a purpose of evaluating different kinds of treemap layout algorithms from the aspect of the difficulty level for tracking time-varying nodes in the overall layout. Finally, our technique’s applicability is demonstrated on the pesticide residues detection results dataset in this study.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Jia, Y., Chen, Y., Li, Z.: Treemap-based visualization methods for pesticide residues detection data. In: Tan, T., Ruan, Q., Chen, X., Ma, H., Wang, L. (eds.) Advances in Image and Graphics Technologies. IGTA 2013. Communications in Computer and Information Science, vol. 363, pp. 154–162. Springer, Berlin (2013)

  2. Chen, Y., Zhang, X., Feng, Y., Liang, J., Chen, H.: Sunburst with ordered nodes based on hierarchical clustering: a visual analyzing method for associated hierarchical pesticide residue data. J. Vis. 18(2), 237–254 (2015)

    Article  Google Scholar 

  3. Plaisant, C., Grosjean, J., Bederson, B.B.: SpaceTree: supporting exploration in large node link tree, design evolution and empirical evaluation. In: IEEE Symposium on Information Visualization, p. 57. (2002)

  4. Yee, K.P., Fisher, D., Dhamija, R., Hearst, M.: Animated exploration of dynamic graphs with radial layout. In: IEEE Symposium on Information Visualization, INFOVIS, pp. 43–50. (2001)

  5. Johnson, B., Shneiderman, B.: Tree-maps: a space-filling approach to the visualization of hierarchical information structures. In: Proceedings of IEEE Conference on Visualization, pp. 284–291. (1991)

  6. Landwehr, J.M.: Icicle plots: better displays for hierarchical clustering. Am. Stat. 37(2), 162–168 (1983)

    Google Scholar 

  7. Schulz, H.J.: Treevis. net: a Tree Visualization Reference. IEEE Eng. Med. Biol. Mag. Q. Mag. Eng. Med. Biol. Soc. 31(6), 11–15 (2011)

    Google Scholar 

  8. Graham, M., Kennedy, J.: A survey of multiple tree visualisation. Inform. Vis. 9(4), 235–252 (2009)

    Article  Google Scholar 

  9. Oliveira E.C., Oliveira L.C., Cardoso A., Mattioli L., Lamounier E.A.: Meta-model of Information Visualization Based on Treemap. In: Rocha A., Correia A., Costanzo S., Reis L. (eds) New Contributions in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 353, pp. 57–68. Springer, Cham (2015)

  10. Carvalho, M.B.D., Meiguins, B.S., Morais, J.M.D.: Temporal data visualization technique based on treemap. In: International Conference Information Visualisation, pp. 399–403. (2016)

  11. Gotz, D.: Dynamic Voronoi treemaps: a visualization technique for time-varying hierarchical data. Phys. Rev. A 30(2), 150–156 (2011)

    Google Scholar 

  12. Zhang, X., Yuan, X.: Treemap visualization. J. Comput. Aided Des. Comput. Gr. 24(9), 1113–1124 (2012)

    Google Scholar 

  13. Yi, C., Hu, H., Li, Z.: Performance compare and optimization of rectangular treemap layout algorithms. J. Comput. Aided Des. Comput. Gr. 25(11), 1623–1634 (2013)

    Google Scholar 

  14. Shneiderman, B.: Treemaps for space constrained visualization of hierarchies. http://www.cs.umd.edu/hcil/treemap-history/ (1992). Accessed Sept 2014

  15. Hadlak, S., Tominski, C., Schulz, H.J., Schumann, H.: Visualization of hierarchies in space and time. In: Workshop on Geospatial Visual Analytics, GeoVA: Focus on Time at the AGILE International Conference on Geographic Information Science (2010)

  16. Li, Y., Lu, A., William, R., Wei, C.: Automatic animation for time-varying data visualization. Comput. Gr. Forum 29(7), 2271–2280 (2010)

    Article  Google Scholar 

  17. Fekete, J.D., Plaisant, C.: Interactive information visualization of a million items. In: IEEE Symposium on Information Visualization, INFOVIS 2002, pp. 117–124. (2002)

  18. Kehrer, J., Hauser, H.: Visualization and visual analysis of multi-faceted scientific data: a survey. IEEE Trans. Vis. Comput. Gr. 19(19), 495–513 (2013)

    Article  Google Scholar 

  19. Wongsuphasawat, K., Gotz, D.: Exploring flow, factors, and outcomes of temporal event sequences with the outflow visualization. IEEE Trans. Vis. Comput. Gr. 18(12), 2659–2668 (2012)

    Article  Google Scholar 

  20. Claessen, J.H.T., Van Wijk, J.J.: Flexible linked axes for multivariate data visualization. IEEE Trans. Vis. Comput. Gr. 17(12), 2310–2316 (2011)

    Article  Google Scholar 

  21. Shi, C., Cui, W., Liu, S., Xu, P., Chen, W., Qu, H.: RankExplorer: visualization of ranking changes in large time series data. IEEE Trans. Vis. Comput. Gr. 18(12), 2669–2678 (2012)

    Article  Google Scholar 

  22. Anand, A., Talbot, J.: Automatic selection of partitioning variables for small multiple displays. IEEE Trans. Vis. Comput. Gr. 22(1), 1–1 (2015)

    Google Scholar 

  23. Fuchs, J., Fischer, F., Mansmann, F., Bertini, E., Isenberg, P.: Evaluation of alternative glyph designs for time series data in a small multiple setting. In: Conference on Human Factors in Computing Systems, pp. 3237–3246. (2013)

  24. Kehrer, J., Piringer, H., Berger, W., Gröller, M.E.: A model for structure-based comparison of many categories in small-multiple displays. IEEE Trans. Vis. Comput. Gr. 19(12), 2287–2296 (2013)

    Article  Google Scholar 

  25. Robertson, G., Fernandez, R., Fisher, D., Lee, B., Stasko, J.: Effectiveness of animation in trend visualization. IEEE Trans. Vis. Comput. Gr. 14(6), 1325–1332 (2008)

    Article  Google Scholar 

  26. Lampe, O.D., Kehrer, J., Hauser, H.: Visual analysis of multivariate movement data using interactive difference views. Vision, Modeling, and Visualization Workshop, VMV 10, 315–322 (2010)

    Google Scholar 

  27. Pendleton, B.: TimeTree: Exploring Time Changing Hierarchies. In: IEEE Symposium On Visual Analytics Science And Technology, IEEE VAST, pp. 3–10 (2006)

  28. Card, S.K., Nation, D.: Degree-of-interest trees: a component of an attention-reactive user interface. In: Working Conference on Advanced Visual Interfaces, pp. 231–245. (2002)

  29. Burch, M., Beck, F., Diehl, S.: Timeline trees: visualizing sequences of transactions in information hierarchies. In: Working Conference on Advanced Visual Interfaces, pp. 75–82. (2008)

  30. Greilich, M., Burch, M., Diehl, S.: Visualizing the evolution of compound digraphs with TimeArcTrees. Comput. Gr. Forum 28(28), 975–982 (2009)

    Article  Google Scholar 

  31. Guerra-Gómez, J.A., Buck-Coleman, A., Plaisant, C., Shneiderman, B.: Interactive visualizations for comparing two trees with structure and node value changes. www.old.cs.umd.edu. (2012)

  32. Guerra-Gómez, J.A., Pack, M.L., Plaisant, C., Shneiderman, B.: Discovering temporal changes in hierarchical transportation data: visual analytics and text reporting tools. Transp. Res. C Emerg. Technol. 51, 167–179 (2015)

    Article  Google Scholar 

  33. Guerra-Gómez, J.A., Buck-Coleman, A., Pack, M.L., Plaisant, C., Shneiderman, B.: TreeVersity: interactive visualizations for comparing hierarchical datasets. Transp. Res. Rec. 16(2392), 48–58 (2013)

    Article  Google Scholar 

  34. Guerra-Gómez, J., Pack, M.L., Plaisant, C., Shneiderman, B.: Visualizing change over time using dynamic hierarchies: TreeVersity2 and the StemView. IEEE Trans. Vis. Comput. Gr. 19(12), 2566 (2013)

    Article  Google Scholar 

  35. Telea, A., Auber, D.: Code flows: visualizing structural evolution of source code. Comput. Gr. Forum 27(3), 831–838 (2008)

    Article  Google Scholar 

  36. Wittenhagen, M., Cherek, C., Borchers, J.: Chronicler: interactive exploration of source code history. In: CHI Conference, pp. 3522–3532. (2016)

  37. Bono, B.D., Grenon, P., Helvensteijn, M., Kok, J., Kokash, N.: ApiNATOMY: towards multiscale views of human anatomy. In: Intelligent Data Analysis, pp. 72–83. (2014)

  38. Wang, C.: iMap: a stable layout for navigating large image collections with embedded search. In: IS&T/SPIE Electronic Imaging, p. 86540K. (2013)

  39. Rios-Berrios, M., Sharma, P., Lee, T.Y., Schwartz, R., Shneiderman, B.: TreeCovery: coordinated dual treemap visualization for exploring the Recovery Act. Gov. Inform. Q. 29(2), 212–222 (2012)

    Article  Google Scholar 

  40. Hu, H., Yi, C., Zhen, Y., Liu, R.: A squarified and ordered treemap layout algorithm. J. Comput. Aided Des. Comput. Gr. 26(10), 1703–1710 (2014)

    Google Scholar 

  41. Bruls, M., Huizing, K., Wijk, van Wijk J.J.: Squarified treemaps. Data Visualization 2000. Eurographics. Springer, Vienna, pp. 33–42 (2000)

  42. Shneiderman, B., Wattenberg, M.: Ordered treemap layouts. In: IEEE Symposium on Information Visualization, p. 73. (2001)

  43. Bederson, B.B., Shneiderman, B., Wattenberg, M.: Ordered and quantum treemaps : making effective use of 2D space to display hierarchies. Acm Trans. Gr. 21(4), 257–278 (2003)

    Google Scholar 

  44. Tu, Y., Shen, H.W.: Visualizing changes of hierarchical data using treemaps. IEEE Trans. Vis. Comput. Gr. 13(6), 1286–1293 (2007)

    Article  Google Scholar 

  45. Duarte, F.S., Sikansi, F., Fatore, F.M., Fadel, S.G., Paulovich, F.V.: Nmap: a novel neighborhood preservation space-filling algorithm. IEEE Trans. Vis. Comput. Gr. 20(12), 2063–2071 (2014)

    Article  Google Scholar 

  46. Balzer, M., Deussen, O.: Voronoi treemaps. In: IEEE Symposium on Information Visualization, INFOVIS, pp. 49–56. (2005)

  47. Hahn, S., Trümper, J., Moritz, D., Döllner, J.: Visualization of varying hierarchies by stable layout of voronoi treemaps. In: International Conference on Information Visualization Theory and Applications, pp. 50–58. (2014)

  48. Fischer, F., Fuchs, J., Mansmann, F.: ClockMap: enhancing circular treemaps with temporal glyphs for time-series data. In: Eurographics Conference on Visualization, pp. 97–101. (2012)

  49. Liang, J., Nguyen, Q.V., Simoff, S., Huang, M.L.: Divide and conquer treemaps: visualizing large trees with various shapes. J. Vis. Lang. Comput. 31, 104–127 (2015)

    Article  Google Scholar 

  50. Ghoniem, M., Fekete, J.-D.: Animating treemaps. In: Proceeding of 18th HCIL Symposium-Workshop on Treemap Implementations and Applications

  51. Kutz, D.O.: Examining the evolution and distribution of patent classifications. In: Proceedings Eighth International Conference on Information Visualisation, pp. 983–988. (2004)

  52. Chintalapani, G.: Temporal treemaps for visualizing time series data. http://drum.lib.umd.edu/handle/1903/1459 (2004). Accessed 04 June 2004

  53. Liu, S., Cui, W., Wu, Y., Liu, M.: A survey on information visualization: recent advances and challenges. Vis. Comput. 30(12), 1373–1393 (2014)

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by “Twelfth Five Year Plan” National Science and Technology Support Program (No. 2012BAD29B01-2), the open funding project of State Key Laboratory of Virtual Reality Technology and Systems, Beihang University (Grant No. BUAA-VR-17KF-07), and Basic Research Project of the Ministry of Science and Technology (Grand No. 2015FY111200). The authors also would like to thank the conference of CGI 2017, which provides the exchange platform for us.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yi Chen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Y., Du, X. & Yuan, X. Ordered small multiple treemaps for visualizing time-varying hierarchical pesticide residue data. Vis Comput 33, 1073–1084 (2017). https://doi.org/10.1007/s00371-017-1373-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-017-1373-x

Keywords

Navigation