Healthcare Data Visualization: Geospatial and Temporal Integration

Shenhui Jiang, Shiaofen Fang, Sam Bloomquist, Jeremy Keiper, Mathew Palakal, Yuni Xia, Shaun Grannis


Healthcare data visualization is challenging due to the needs for integrating geospatial information, temporal information, text information, and heterogenious health attributes within a common visual context. We recently developed a web-based healthcare data visualization system, Health-Terrain, based on a Notifiable Condition Detector (NCD) use case. In this paper, we will describe this system, with emphasis on the visualization techniques developed specifically for healthcare data. Two new visualization techniques will be described: (1) A spatial texture based visualization approach for multi-dimensional attributes and time-series data; (2) A spiral theme plot technique for visualizing time-variant patient data.


  1. Grossman, C., Powers B., McGinnis J. M., 2011. Digital infrastructure for the learning health care system: the foundation for continuous improvement in health and health care. The National Academies Press.
  2. Plaisant, C., Milash, B., Rose, A., Widoff, S., Shneiderman, B., 1996. Lifeline: Visualizing Personal Histories, CHI, pp. 221-227.
  3. Wang, T. D., Plaisant, C., et al. 2008. Aligning Temporal Data by Sentinel Events: Discovering Patterns in Electronic Health Records, CHI'08, pp. 457-466.
  4. Bui, A., Aberle, D. R., Kangarloo, H, 2007. Timeline: Visualizing Integrated Patient Records. IEEE Trans. Information Technology in Biomedicine 11(4):462- 473.
  5. Klimov D., Shahar Y, 2005. A framework for intelligent visualization of multiple time-oriented medical records. AMIA Annual Symp Proc.; 405-409.
  6. Klimov D., Shahar Y, Taieb-Maimon M, 2009. Intelligent interactive visual exploration of temporal associations among multiple time-oriented patient records. Methods Inf Med. 48: 254-262.
  7. Hallett, C., 2008. Multi-Modal Presentation of Medical Histories. IUI'08: 13th International Conference on Intelligent User Interfaces. pp. 80-89.
  8. Bade, R., Schlechtweg, S. and Miksch, S., 2004. Connecting time-oriented data and information to a coherent interactive visualization. CHI'04. 105-112.
  9. Maciejewski, R., Rudolph, S. and Hafen, R. 2009. A Visual Analytics Approach to Understanding Spatiotemporal Hotspots. IEEE Transactions on Visualization and Computer Graphics, 16, 205-220.
  10. Carroll LN et al. 2014. Visualization and analytics tools for infectious disease epidemiology: A systematic review. J Biomed Inform, 51:287-98.
  11. Chittaro, L., 2001. Information Visualization and Its Application to Medicine. Artificial Intelligence in Medicine, 22(2), 81-88.
  12. Gemmell, J., Aris A., Lueder R. 2005. Telling stories with MyLifeBits. IEEE International Conference on Multimedia and Expo, pp. 1536-1539.
  13. The New York Times Company: Openpaths, Feb. 2013. URL:
  14. Google: Latitude, 2013. Eccles, R., Kapler T., Harper, R., Eright, W. 2007. Stories in GeoTime. In IEEE VAST, 19-26.
  15. Kraak, M. 2003. The Space Time Cube Revisited from a Geovisualization Perspective, Proc. 21st Int'l Cartographic Conf., 1988-1996.
  16. Kraak, M. J., and P. F. Madzudzo, 2007. Space time visualization for epidemiological research. Proceedings of the 23nd international cartographic conference: Cartography for everyone and for you.
  17. Kraak, M. J. and A. Kousoulakou, 2004. A visualization environment for the space-time-cube. Developments in spatial data handling. 11th International Symposium on Spatial Data Handling. 189-200.
  18. Kwan, M. P., 2000. Interactive geovisualization of activity travel patterns using 3D geographical information systems: a methodological exploration with a large data set. Transportation Research C 8: 185-203.
  19. Andrienko, N., G. L. Andrienko, et al., 2003. Visual data exploration using space-time cube. 21st International Cartographic Conference, Durban, South Africa.
  20. Tominski, C., Schulze-Wollgast, P. and Schumann, H., 2005. 3D information visualization for time dependent data on maps. IEEE Information Visualization'05, 175-181.
  21. Tufte, E. R., 1983. The Visual Display of Quantitative Information. Graphics Press.
  22. Havre, S., Richland, W. A., Hetzler, B., 2000. ThemeRiver: visualizing theme changes over time. IEEE Information Visualization, 115-123.
  23. Cui, W., S. Liu, et. al., 2011. Textflow: Towards better understanding of evolving topics in text. IEEE Trans. on Visualization and Computer Graphics, 17 (12), 2412-2421.
  24. Weber, M., Marc Alexa, Wolfgang Müller. 2001. Visualizing Time-Series on Spirals. IEEE Information Visualization, 7-13.
  25. Tominski, C., Schumann, H., 2008. Enhanced Interactive Spiral Display, Annual SIGRAD Conference Special Theme: Interaction. 53-56.
  26. Cabral, B., and L. C. Leedom. 1993. Imaging Vector Fields Using Line Integral Convolution. In Poceedings of ACM SIGGRAPH, 263-272.
  27. Stalling, D. and H. Hege. 1995. Fast and Resolution Independent Line Integral Convolution. In Proceedings of ACM SIGGRAPH 95, 249-256.
  28. Laramee, R. S., et al., 2004. The State of the Art in Flow Visualization: Dense and Texture-Based Techniques. Computer Graphics Forum, 3(2):203-221.
  29. McGraw, T., M. Nadar. 2007. Fast Texture-Based Tensor Field Visualization for DT-MRI. 4th IEEE International Symposium on Biomedical Imaging: Macro to Nano, 760-763.
  30. Auer, C., Stripf, C., Kratz, A., Hotz, I., 2012. Glyph- and Texture-based Visualization of Segmented Tensor Fields. Proc. Int. Conf. on Information Visualization Theory and Applications, 670-677.
  31. Overhage J. M, Grannis S. J., McDonald C. J., 2008. A comparison of the completeness and timeliness of automated electronic laboratory reporting and spontaneous reporting of notifiable conditions. Am J Public Health. 98(2):344-50.
  32. Stephen, G., Kobourov, 2012. Spring Embedders and Force Directed Graph Drawing Algorithms. arXiv: 1201.3011.
  33. Humphreys, B. L., D. A. Lindberg, H. M. Schoolman, G. O. Barnett, 1998. The unified medical language system: An informatics research collaboration J. Am. Med. Inform. Assoc., 5 (1), 1-11.
  34. Osinski, S., D Weiss, 2005. A concept-driven algorithm for clustering search results - Intelligent Systems, IEEE Intelligent Systems, 48-54.
  35. Gossett, N., Baoquan Chen, 2004. Paint Inspired Color Mixing and Compositing for Visualization. IEEE Symposium on Information Visualization. 113-117.
  36. Perlin, K., 1982. An image synthesizer. In Proceedings of SIGGRAPH'85, 287-296.
  37. Rosenfeld, A. and A.C. Kak, 1982. Digital Picture Processing. Academic Press, New York.
  38. Hoschek, J., 1988. Spline Approximation of Offset Curves. Computer Aided Geometric Design. 33-40.

Paper Citation

in Harvard Style

Jiang S., Fang S., Bloomquist S., Keiper J., Palakal M., Xia Y. and Grannis S. (2016). Healthcare Data Visualization: Geospatial and Temporal Integration . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: IVAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 212-219. DOI: 10.5220/0005714002120219

in Bibtex Style

author={Shenhui Jiang and Shiaofen Fang and Sam Bloomquist and Jeremy Keiper and Mathew Palakal and Yuni Xia and Shaun Grannis},
title={Healthcare Data Visualization: Geospatial and Temporal Integration},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: IVAPP, (VISIGRAPP 2016)},

in EndNote Style

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: IVAPP, (VISIGRAPP 2016)
TI - Healthcare Data Visualization: Geospatial and Temporal Integration
SN - 978-989-758-175-5
AU - Jiang S.
AU - Fang S.
AU - Bloomquist S.
AU - Keiper J.
AU - Palakal M.
AU - Xia Y.
AU - Grannis S.
PY - 2016
SP - 212
EP - 219
DO - 10.5220/0005714002120219