The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.02 - March/April (2010 vol.16)
pp: 205-220
Ross Maciejewski , Purdue University, West Lafayette
Stephen Rudolph , Purdue University Regional Visualization and Analytics Center, Scottsdale
Ryan Hafen , Purdue University, West Lafayette
Ahmad M. Abusalah , Purdue University, Saint Paul
Mohamed Yakout , Purdue University, West Lafayette
Mourad Ouzzani , Purdue University, West Lafayette
William S. Cleveland , Purdue Univeristy, West Lafayette
Shaun J. Grannis , Regenstrief Institute, Inc. and Indiana University School of Medicine, Indianapolis
David S. Ebert , Purdue University, West Lafayette
ABSTRACT
As data sources become larger and more complex, the ability to effectively explore and analyze patterns among varying sources becomes a critical bottleneck in analytic reasoning. Incoming data contain multiple variables, high signal-to-noise ratio, and a degree of uncertainty, all of which hinder exploration, hypothesis generation/exploration, and decision making. To facilitate the exploration of such data, advanced tool sets are needed that allow the user to interact with their data in a visual environment that provides direct analytic capability for finding data aberrations or hotspots. In this paper, we present a suite of tools designed to facilitate the exploration of spatiotemporal data sets. Our system allows users to search for hotspots in both space and time, combining linked views and interactive filtering to provide users with contextual information about their data and allow the user to develop and explore their hypotheses. Statistical data models and alert detection algorithms are provided to help draw user attention to critical areas. Demographic filtering can then be further applied as hypotheses generated become fine tuned. This paper demonstrates the use of such tools on multiple geospatiotemporal data sets.
INDEX TERMS
Geovisualization, kernel density estimation, syndromic surveillance, hypothesis exploration.
CITATION
Ross Maciejewski, Stephen Rudolph, Ryan Hafen, Ahmad M. Abusalah, Mohamed Yakout, Mourad Ouzzani, William S. Cleveland, Shaun J. Grannis, David S. Ebert, "A Visual Analytics Approach to Understanding Spatiotemporal Hotspots", IEEE Transactions on Visualization & Computer Graphics, vol.16, no. 2, pp. 205-220, March/April 2010, doi:10.1109/TVCG.2009.100
REFERENCES
[1] L. Blanton et al., “Update: Influenza Activity—United States and Worldwide, 2006-07 Season, and Composition of the 2007-08 Influenza Vaccine,” Morbidity and Mortality Weekly Report, vol. 56, pp. 789-794, 2007.
[2] W. Aigner, S. Miksch, W. Muller, H. Schumann, and C. Tominski, “Visual Methods for Analyzing Time-Oriented Data,” IEEE Trans. Visualization and Computer Graphics, vol. 14, no. 1, pp. 47-60, Jan./Feb. 2008.
[3] W. Aigner, S. Miksch, B. Thurnher, and S. Biffl, “Planninglines: Novel Glyphs for Representing Temporal Uncertainties and Their Evaluation,” Proc. Ninth Int'l Conf. Information Visualization (IV '05) 2005.
[4] L. Anselin, I. Syabri, and O. Smirnov, “Visualizing Multivariate Spatial Correlation with Dynamically Linked Windows,” Proc. Workshop New Tools for Spatial Data Analysis, CD-ROM, 2002.
[5] R.A. Becker and W.S. Cleveland, “Brushing Scatterplots,” Technometrics, vol. 29, no. 2, pp. 127-142, 1987.
[6] C.A. Brewer, Designing Better Maps: A Guide for GIS Users. ESRI Press, 2005.
[7] A. Buja, D. Cook, and D. Swayne, “Interactive High Dimensional Data Visualization,” J. Computational and Graphical Statistics, vol. 5, pp. 78-99, 1996.
[8] P. Buono, A. Aris, C. Plaisant, A. Khella, and B. Shneiderman, “Interactive Pattern Search in Time Series,” Proc. Conf. Visualization and Data Analysis, pp. 175-186, 2005.
[9] T. Butkiewicz, W. Dou, Z. Wartell, W. Ribarsky, and R. Chang, “Multi-Focused Geospatial Analysis Using Probes,” IEEE Trans. Visualization and Computer Graphics, vol. 14, pp. 1165-1172, Nov./Dec. 2008.
[10] C.C. Calhoun, C.E. Stobbart, D.M. Thomas, J.A. Villarrubia, D.E. Brown, and J.H. Conklin, “Improving Crime Data Sharing and Analysis Tools for a Web-Based Crime Analysis Toolkit: Webcat 2.2,” Proc. 2008 IEEE Systems and Information Eng. Design Symp., 2008.
[11] W.W. Chapman, J.N. Dowling, and M.M. Wagner, “Classification of Emergency Department Chief Complaints into 7 Syndromes: A Retrospective Analysis of 527,228 Patients,” Annals of Emergency Medicine, vol. 46, pp. 445-455, Nov. 2005.
[12] L. Chittaro and C. Combi, “Visualizing Queries on Databases of Temporal Histories: New Metaphors and Their Evaluation,” Proc. IEEE Symp. Information Visualization (INFOVIS '01), p. 159, 2001.
[13] W.S. Cleveland, Visualizing Data. Hobart Press, 1993.
[14] T. Cormen, C. Leiserson, R. Rivest, and C. Stein, Introduction to Algorithms. The MIT Press, 2001.
[15] G. Dang, C. North, and B. Shneiderman, “Dynamic Queries and Brushing on Choropleth Maps,” Proc. Fifth Int'l Conf. Information Visualization (IV '01), pp. 757-764, 2001.
[16] R.M. Edsall, A.M. MacEachren, and L. Pickle, “Case Study: Design and Assessment of an Enhanced Geographic Information System for Exploration of Multivariate Health Statistics,” Proc. IEEE Symp. Information Visualization (INFOVIS '01), pp. 159-162, 2001.
[17] Information Visualization in Data Mining and Knowledge Discovery, U. Fayyad, G.G. Grinstein, and A. Wierse, eds. Morgan Kaufmann Publishers, Inc., 2002.
[18] M. Gibin, P. Longley, and P. Atkinson, “Kernel Density Estimation and Percent Volume Contours in General Practice Catchment Area Analysis in Urban Areas,” Proc. Geographical Information Science Research Conf., 2007.
[19] S.J. Grannis, M. Wade, J. Gibson, and J.M. Overhage, “The Indiana Public Health Emergency Surveillance System: Ongoing Progress, Early Findings, and Future Directions,” Proc. Am. Medical Informatics Assoc. Ann. Symp., 2006.
[20] Hargrove and Hoffman, “Using Multivariate Clustering to Characterize Ecoregion Borders,” Proc. Computing in Science & Eng., the AIP and the IEEE Computer Soc., vol. 1, pp. 18-25, 1999.
[21] S. Havre, E. Hetzler, P. Whitney, and L. Nowell, “Themeriver: Visualizing Thematic Changes in Large Document Collections,” IEEE Trans. Visualization and Computer Graphics, vol. 8, no. 1, pp. 9-20, Jan.-Mar. 2002.
[22] L.C. Hutwagner, W.W. Thompson, and G.M. Seeman, “The Bioterrorism Preparedness and Response Early Aberration Reporting System (EARS),” J. Urban Health, vol. 80, no. 2, pp. i89-i96, 2003.
[23] D. Kao, A. Luo, J.L. Dungan, and A. Pang, “Visualizing Spatially Varying Distribution Data,” Proc. Sixth Int'l Conf. Information Visualization, pp. 219-225, 2002.
[24] M. Kulldorff, “A Spatial Scan Statistic,” Comm. Statistics: Theory and Methods, vol. 26, pp. 1481-1496, 1997.
[25] A.D. Langmuir, “The Surveillance of Communicable Diseases of National Importance,” New England J. Medicine, vol. 268, pp. 182-192, 1963.
[26] K. Liao, “A Visualization System for Space-Time and Multivariate Patterns (VIS-STAMP),” IEEE Trans. Visualization and Computer Graphics, vol. 12, no. 6, pp. 1461-1474, Nov./Dec. 2006.
[27] J.S. Lombardo, “A Systems Overview of the Electronic Surveillance System for the Early Notification of Community Based Epidemics (ESSENCE II),” J. Urban Health, vol. 80, pp. 32-42, 2003.
[28] J.W. Loonsk, “Biosense—A National Initiative for Early Detection and Quantification of Public Health Emergencies,” Morbidity and Mortality Weekly Report, vol. 53, pp. 53-55, 2004.
[29] A.L. Love, A. Pang, and D.L. Kao, “Visualizing Spatial Multivalue Data,” IEEE Computer Graphics and Applications, vol. 25, no. 3, pp.69-79, May/June 2005.
[30] A.M. MacEachren, F.P. Boscoe, D. Haug, and L. Pickle, “Geographic Visualization: Designing Manipulable Maps for Exploring Temporally Varying Georeferenced Statistics,” Proc. IEEE Symp. Information Visualization (INFOVIS '98), p. 87, 1998.
[31] R. Maciejewski, S. Rudolph, R. Hafen, A. Abusalah, M. Yakout, M. Ouzzani, W.S. Cleveland, S.J. Grannis, M. Wade, and D.S. Ebert, “Understanding Syndromic Hotspots—A Visual Analytics Approach,” Proc. IEEE Symp. Visual Analytics Science and Technology (VAST), Oct. 2008.
[32] R. Maciejewski, B. Tyner, Y. Jang, C. Zheng, R. Nehme, D.S. Ebert, W.S. Cleveland, M. Ouzzani, S.J. Grannis, and L.T. Glickman, “Lahva: Linked Animal-Human Health Visual Analytics,” Proc. IEEE Symp. Visual Analytics Science and Technology, Oct. 2007.
[33] A.R. Martin and M.O. Ward, “High Dimensional Brushing for Interactive Exploration of Multivariate Data,” Proc. Sixth Conf. Visualization (VIS '95), pp. 271-278, 1995.
[34] S.F. Messner and L. Anselin, “Spatial Analyses of Homicide with Areal Data,” Spatially Integrated Social Science CD-ROM, pp. 127-144, Oxford Univ. Press, 2002.
[35] C.-C. Pan and P. Mitra, “Femarepviz: Automatic Extraction and Geo-Temporal Visualization of Fema National Situation Updates,” Proc. IEEE Symp. Visual Analytics Science and Technology (VAST '07), pp. 11-18, Oct./Nov. 2007.
[36] J.C. Roberts and M.A.E. Wright, “Towards Ubiquitous Brushing for Information Visualization,” Proc. Int'l Conf. Information Visualization (IV '06), pp. 151-156, 2006.
[37] B.W. Silverman, Density Estimation for Statistics and Data Analysis. Chapman & Hall/CRC, 1986.
[38] J. Stasko, C. Gorg, Z. Liu, and K. Singal, “Jigsaw: Supporting Investigative Analysis through Interactive Visualization,” Proc. IEEE Symp. Visual Analytics Science and Technology, pp. 131-138, 2007.
[39] S.B. Thacker, R.L. Berkelman, and D.F. Stroup, “The Science of Public Health Surveillance,” J. Public Health Policy, vol. 10, pp. 187-203, 1989.
[40] Illuminating the Path: The R&D Agenda for Visual Analytics. J.J.Thomas and K.A. Cook, eds. IEEE Press, 2005.
[41] C. Tominski, J. Abello, and H. Schumann, “Axes-Based Visualizations with Radial Layouts,” Proc. ACM Symp. Applied Computing (SAC '04), pp. 1242-1247, 2004.
[42] C. Tominski, P. Schulze-Wollgast, and H. Schumann, “Visual Analysis of Health Data,” Proc. Int'l Information Resource Management Assoc. (IRMA) Conf., 2003.
[43] C. Tominski, P. Schulze-Wollgast, and H. Schumann, “3D Information Visualization for Time Dependent Data on Maps,” Proc. Int'l Conf. Information Visualization (IV), 2005.
[44] C. Weaver, “Multidimensional Visual Analysis Using Cross-Filtered Views,” Proc. IEEE Symp. Visual Analytics Science and Technology (VAST), Oct. 2008.
[45] M. Weber, M. Alexa, and W. Muller, “Visualizing Time-Series on Spirals,” Proc. IEEE Symp. Information Visualization (INFOVIS '01), pp. 7-14, Oct. 2001.
[46] H. Zhao, B. Shneiderman, and C. Plaisant, “Improving Accessibility and Usability of Geo-Referenced Statistical Data,” Proc. 2003 Ann. Nat'l Conf. Digital Govt. Research (DGO '03), p. 1, 2003.
24 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool