Skip to main content
SpringerLink
Log in

Exploring Changes in Census Time Series with Interactive Dynamic Maps and Graphics

  • Published:
Computational Statistics Aims and scope Submit manuscript

Summary

Interactive graphical tools are available in a number of statistical packages. However, none of them provide interactive tools for visual exploration of time series data that have spatial reference (spatio-temporal data), such as census data. Analysis of spatio-temporal data requires simultaneous representation of their spatial, temporal, and thematic aspects. We propose a system that combines interactive thematic maps, dynamic statistical graphics, and advanced controls for manipulating them. These components as well as interaction between them are specifically designed in order to support visual investigation of changes in data, the ultimate goal being to help users to reveal spatio-temporal trends. The suggested tools facilitate also detecting errors and anomalies in data.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 3a
Figure 4
Figure 4a
Figure 5
Figure 6

Similar content being viewed by others

Notes

  1. 2We assure that the error reported here was really present in the data set and not artificially introduced. Data sets very often contain errors, even after careful verification. An important feature of the system is that it facilitates detecting errors in data by providing special displays and interactive tools.

References

  • Andrienko, G. and Andrienko, N. (1999a) Knowledge-Based Visualization to Support Spatial Data Mining. In Hand, D.J., Kok, J.N., and Berthold, M.R. (Eds.) Advances in Intelligent Data Analysis, Lecture Notes in Computer Science, vol. 1642. Berlin: Springer-verlag, pp. 149–160

    Article  Google Scholar 

  • Andrienko, G. and Andrienko, N. (1999b), Data Mining with C4.5 and Cartographic Visualization. In N.W. Paton and T. Griffiths (eds.) User Interfaces to Data Intensive Systems, IEEE Computer Society. Los Alamitos, CA, pp. 162–165

    Chapter  Google Scholar 

  • Andrienko, N., Andrienko, G., and Gatalsky, P. (2000), Supporting Visual Exploration of Object Movement. In V. Di Gesu, S. Levialdi, L. Tarantino (eds.) Proceedings of the Working Conference on Advanced Visual Interfaces AVI 2000, Palermo, Italy, May 23–26, 2000. ACM Press, 2000, pp.217–220, 315

    Chapter  Google Scholar 

  • Avidan, T. and Avidan, S. (1999), ParallAX — a data mining tool based on parallel coordinates, Computational Statistics, 14 (1), 79–90.

    Article  Google Scholar 

  • Bertin, J. (1967/1983) Semiology of Graphics. Diagrams, Networks, Maps (Madison: The University of Wisconsin Press)

    Google Scholar 

  • Blok, C., Koebben, B., Cheng, T., and Kuterema, A.A. (1999), Visualization of Relationships Between Spatial Patterns in Time by Cartographic Animation, Cartography and Geographic Information Science, 26 (2), pp. 139–151.

    Article  Google Scholar 

  • Brewer, C.A. (1994). Colour Use Guidelines for Mapping and Visualisation. In Visualisation in Modern Cartography (NY: Elsevier Science Inc.), pp.123–147.

    Chapter  Google Scholar 

  • Buja, A., McDonald, J.A., Michalak, J., and Stuetzle, W. (1991), Interactive data visualization using focusing and linking. In Proceedings IEEE Visualization’91 (Washington: IEEE Computer Society Press), 156–163.

    Google Scholar 

  • Buziek, G. (1999) Dynamic Elements of Multimedia Cartography, In Multimedia Cartography: Cartwright, W., Peterson, M.P., Gartner, G. (Eds.), Springer-Verlag, Berlin Heidelberg, pp. 231–244.

    Chapter  Google Scholar 

  • Edsall, R., Peuquet, D., (1997), A graphical user interface for the integration of time into GIS. Proceedings of the 1997 American Congress of Surveying and Mapping Annual Convention and Exhibition, Seattle, WA, pp.182–189.

  • Fredrikson, A., Plaisant, C., and Shneiderman, B., (1999), Temporal, geographic and categorical aggregations viewed through coordinated displays: a case study with highway incident data, In Proceedings of Workshop on New Paradigms in Information Visualization and Manipulation (NPIV’99), NY, ACM Press, pp.26–34

    Google Scholar 

  • Inselberg, A. (1985). The plane with parallel coordinates. Visual Computer, 1 (1), pp.69–97.

    Article  MathSciNet  Google Scholar 

  • Jankowski, P., Andrienko, N., and Andrienko, G. (2001), Map-Centered Exploratory Approach to Multiple Criteria Spatial Decision Making. International Journal Geographical Information Science, v.15 (2), pp.101–127

    Article  Google Scholar 

  • Kraak, M.J., Edsall, R., and MacEachren, A.M., 1997. Cartographic animation and legends for temporal maps: exploration and/or interaction, Proceedings 18th International Cartographic Conference, vol. 1, pp. 253–261.

    Google Scholar 

  • Monmonier, M., (1990). Strategies for the visualization of geographic time-series data. Cartographica, 27 (1), pp. 30–45.

    Article  Google Scholar 

  • Oberholzer, C., Hurni, L., (2000), Visualization of change in the Interactive Multimedia Atlas of Switzerland, Computer & Geosciences, 26 (1), pp. 423–435.

    Article  Google Scholar 

  • Quinlan, Q.R., (1993) C4.5 Programs for Machine Learning. Morgan Kaufmann

  • Slocum, T. A., S. C. Yoder, F. C. Kessler and R. S. Sluter (in press). MapTime: Software for exploring spatiotemporal data associated with point locations. Cartographica.

  • Tobler, W., 1970. Computer movie simulating urban growth in the Detroit region, Economic Geography, 46 (2), pp.234–240.

    Article  Google Scholar 

  • Unwin, A. and Wills, G. (1998), Exploring Time Series Graphically, Statistical Computing and Graphics Newsletter, (2), 13–15

    Google Scholar 

  • Vasiliev, I.R. (1997), Mapping Time. Cartographica, 34 (2), pp.1–51.

    Article  Google Scholar 

  • Wrobel, S., Wettschereck, D., Sommer, E., and Emde, W. (1996),“Extensibility in Data Mining Systems”, Proceedings of KDD’96 2nd International Conference on Knowledge Discovery and Data Mining, AAAI Press, pp.214–219

  • Yamahira, T., Kasahara, Y., and Tsurutani, T. (1985) How map designers can represent their ideas in thematic maps. The Visual Computer, 1, 174–184

    Article  Google Scholar 

Download references

Acknowledgements

Our research is partly supported by the European Commission in projects EuroFigures — a digital portrait of the EU’s General Statistics (Eurostat SUPCOM 97, Project n. 13648, Subcontract to JRC 15089-1999-06) and SPIN! — Spatial Mining for Data of Public Interest (IST Program, project No. IST-1999-10536). Orientation of our research interests to spatio-temporal data exploration was inspired by stimulating discussions on meetings of the ICA Visualization Commission (URL http://www.geovista.psu.edu/icavis/). We are grateful to M.-J.Kraak, C.Blok and N.Emmer (ITC) for providing data and checking our hypothesis. We thank reviewers of the paper for their useful comments.

Author information

Authors and Affiliations

  1. Knowledge Discovery Research Group, Schloss Birlinghoven, GMD — German National Research Center for Information Technology, Institute for Autonomous Intelligent Systems, Sankt Augustin, D-53754, Germany

    Natalia Andrienko, Gennady Andrienko & Peter Gatalsky

Authors
  1. Natalia Andrienko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gennady Andrienko
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Peter Gatalsky
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Andrienko, N., Andrienko, G. & Gatalsky, P. Exploring Changes in Census Time Series with Interactive Dynamic Maps and Graphics. Computational Statistics 16, 417–433 (2001). https://doi.org/10.1007/s001800100076

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s001800100076

Keywords

Search

Navigation