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The Visual Computer

, Volume 32, Issue 3, pp 403–413 | Cite as

EnergyViz: an interactive system for visualization of energy systems

  • Haleh AlemasoomEmail author
  • Faramarz Samavati
  • John Brosz
  • David Layzell
Original Article

Abstract

Energy systems are under pressure to transform to address concerns about climate change. The modeling and visualization of energy systems can play an important role in communicating the costs, benefits and trade-offs of energy systems choices. We introduce EnergyViz, a visualization system that provides an interface for exploring time-varying, multi-attribute and spatial properties of a particular energy system. EnergyViz integrates several visualization techniques to facilitate exploration of a particular energy system. These techniques include flow diagram representation to show energy flow, 3D interaction with flow diagrams for expanding viewable data attributes such as emissions and an interactive map integrated with flow diagrams for simultaneous exploration of spatial and abstract information. We also perform level-of-detail exploration on flow diagrams and use smooth animation across the visualizations to represent time-varying data. Finally, we include evaluation results of EnergyViz collected from expert and inexperienced participants.

Keywords

Energy system Visualization Flow Sankey diagram Time-varying Spatial Animation 

Notes

Acknowledgments

The authors would like to thank whatIf? Technologies Inc. (Ottawa, ON) for providing access to the data from their Canadian Energy Systems Simulator (CanESS) model. Research funding was provided by Canada School of Energy and Environment and GRAND NCE.

References

  1. 1.
    Aigner, W., Miksch, S., Muller, W., Schumann, H., Tominski, C.: Visualizing time-oriented data. A systematic view. Comput. Graph. 31(3), 148–252 (2007)Google Scholar
  2. 2.
    Aigner, W., Miksch, S., Schumann, H., Tominski, C.: Visualization of Time-Oriented Data, 1st edn. Springer, Berlin (2011)CrossRefGoogle Scholar
  3. 3.
    Alemasoom, H., Samavati, F., Brosz, J., Layzell, D.: Interactive visualization of energy system. In: Cyberworlds International Conference, Santander, Spain (2014)Google Scholar
  4. 4.
    Auber, D., Jourdan, F.: Interactive refinement of multi-scale network clusterings. In: Proceedings of Ninth International Conference on Information Visualisation, pp. 703–709 (2005)Google Scholar
  5. 5.
    Bendix, F., Kosara, R., Hauser, H.: Parallel sets: visual analysis of categorical data. In: IEEE Symposium on Information Visualization, pp. 133–140 (2005)Google Scholar
  6. 6.
    Bezerianos, A., Chevalier, F., Dragicevic, P., Elmqvist, N., Fekete, J.D.: Graphdice: a system for exploring multivariate social networks. In: Proceedings of the 12th Eurographics VGTC Conference on Visualization, pp. 863–872 (2010)Google Scholar
  7. 7.
    Bondy, J.A., Murty, U.S.R.: Graph Theory with Applications, vol. 6. Macmillan, London (1976)CrossRefzbMATHGoogle Scholar
  8. 8.
    Brockenauer, R., Cornelsen, S.: Drawing Graphs: Methods and Models, Chap. Drawing Clusters and Hierarchies. Springer, Berlin (2001)zbMATHGoogle Scholar
  9. 9.
    Canadian Energy System Simulator (CanESS). http://www.whatiftechnologies.com/index.php/caness. (Online; accessed Feb-2015)
  10. 10.
    Collins, C., Carpendale, S.: Vislink: revealing relationships amongst visualizations. IEEE Trans. Vis. Comput. Graph. 13(6), 1192–1199 (2007)CrossRefGoogle Scholar
  11. 11.
    Doantam Phan, L.X., Yeh, R., Hanrahan, P., Winograd, T.: Flow map layout. In: Proceedings of the IEEE Symposium on Information Visualization, pp. 219–224 (2005)Google Scholar
  12. 12.
    Erten, C., Harding, P.J., Kobourov, S.G., Wampler, K., Yee, G.: Graphael: graph animationswith evolving layouts. In: Liotta, G. (ed.) Graph Drawing, pp. 98–110. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  13. 13.
    Gapminder. http://www.gapminder.org (2014). (Online; accessed Feb-2015)
  14. 14.
    Guo, D., Chen, J., MacEachren, A., Liao, K.: A visualization system for space-time and multivariate patterns (vis-stamp). IEEE Trans. Vis. Comput. Graph. 12(6), 1461–1474 (2006)CrossRefGoogle Scholar
  15. 15.
    Healy, P., Nikolov, N.S.: Handbook of Graph Drawing and Visualization, 1st edn. Chapman and Hall, London (2013)Google Scholar
  16. 16.
    International Energy Agency’s Interactive Sankey Diagram. http://www.iea.org/Sankey (2014). (Online; accessed Feb-2015)
  17. 17.
    Kothur, P., Sips, M., Kuhlmann, J., Dransch, D.: Visualization of geospatial time series from environmental modeling output, pp. 115–119 (2012)Google Scholar
  18. 18.
    Muller, W., Schumann, H.: Visualization methods for time-dependent data—an overview. In: Proceedings of the Simulation Conference, vol. 1, pp. 737–745 (2003)Google Scholar
  19. 19.
    North, S.C., Woodhull, G.: Online hierarchical graph drawing. In: Mutzel, P., Jünger, M., Leipert, S. (eds.) Graph Drawing, pp. 232–246. Springer, Heidelberg (2002)Google Scholar
  20. 20.
    Numeric.js: http://numericjs.com/ (2015). (Online; accessed Feb 2015)
  21. 21.
    Riehmann, P., Hanfler, M., Froehlich, B.: Interactive sankey diagrams. In: IEEE Symposium on Information Visualization, pp. 233–240 (2005)Google Scholar
  22. 22.
    Robertson, G., Fernandez, R., Fisher, D., Lee, B., Stasko, J.: Effectiveness of animation in trend visualization. IEEE Trans. Vis. Comput. Graph. 14(6), 1325–1332 (2008)Google Scholar
  23. 23.
    Steele, J., Illinsky, N.: Beautiful Visualization, 1st edn. O’Reilly Media, Sebastopol (2011)Google Scholar
  24. 24.
    Sugiyama, K., Tagawa, S., Toda, M.: Methods for visual understanding of hierarchical system structures. IEEE Trans. Syst. Man Cybern. 11(2), 109–125 (1981)MathSciNetCrossRefGoogle Scholar
  25. 25.
    Tiller, W., Hanson, E.G.: Offsets of two-dimensional profiles. IEEE Comput. Graph. Appl. 4(9), 36–46 (1984)CrossRefGoogle Scholar
  26. 26.
    Tufte, E.R., Graves-Morris, P.: The Visual Display of Quantitative Information, vol. 2. Graphics Press, Cheshire (1983)Google Scholar
  27. 27.
    von Landesberger, T., Bremm, S., Andrienko, N., Andrienko, G., Tekusova, M.: Visual analytics methods for categoric spatio-temporal data. In: IEEE Conference on Visual Analytics Science and Technology (VAST), pp. 183–192 (2012)Google Scholar
  28. 28.
    Wongsuphasawat, K., Gotz, D.: Exploring flow, factors, and outcomes of temporal event sequences with the outflow visualization. Vis. Comput. Graph. IEEE Trans. 18(12), 2659–2668 (2012)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Haleh Alemasoom
    • 1
    Email author
  • Faramarz Samavati
    • 1
  • John Brosz
    • 2
  • David Layzell
    • 3
  1. 1.Department of Computer ScienceUniversity of CalgaryCalgaryCanada
  2. 2.Libraries and Cultural ResourcesUniversity of CalgaryCalgaryCanada
  3. 3.Canadian Energy Systems Analysis Research (CESAR) InstituteCalgaryCanada

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