In recent decades, we have made several attempts to use expert knowledge of data visualisation principles for the automated generation of data displays. Thus, in [1], we describe how various thematic mapping techniques can be chosen automatically, depending on the characteristics of the data, such as the number and types of attributes and the semantic relationships between them. To enable knowledge-based design of thematic maps, it is necessary to describe the semantics of the data. We discuss the relevant aspects of the semantics of data in [2]. Reference [3] proposes a dialogue procedure for acquiring such information from domain experts. This procedure is an adaptation of our previous work on knowledge engineering and expertise transfer [4]. In our later papers, we extend the idea of knowledge- based user support from automated visualisation design to helping users to choose and apply various tools for exploratory data analysis. In [5], we discuss what categories of knowledge are needed for an intelligent software assistant. Reference [6] describes how knowledge-based visualisation and intelligent guidance can support data analysts and decision makers.
In parallel to our research on knowledge-based visualisation design and user guidance, we have developed a concept of interactive maps that change their appearance in response to manipulation by the user [1]. This concept was later extended to dynamic classification maps [7] and to techniques for the exploration of raster data [8]. Reference [9] reports the results of our study of the usability of interactive maps. Our general experience is that new users must first learn and "feel" the high interactivity of the novel tools with some examples. A short introduction of 30 to 60 minutes and some hands-on experience should generally induce a sufficient sense of fun and sufficient courage that users can continue with their own exploration of further tools.
The next group of publications relates to our contribution to forming the research agenda for geovisualisation and computer cartography. Reference [10] demonstrates the need for extending cartographic knowledge to interactive and dynamic maps. Two collective papers consider the research agenda in cartographic representation [11] and in the design of geovisualisation tools [12]. References [13, 14] present some steps towards the implementation of the research agenda in the area of the visualisation and interactive exploration of spatio-temporal data. Writing these papers initiated our thinking about this book.
The next series of publications presents the tools and techniques that we have designed to support the exploratory analysis of various categories of spatio-temporal data: exploration of object movement [15], detection of changes and analysis of variance in spatially distributed time series data [16, 17], characterisation and comparison of spatial development scenarios [18], and analysis of point events [19].
Several publications deal with the use of interactive statistical graphics. Thus, in [20], we have suggested a procedure of classification according to the dominant attribute. In [21], we have considered several different ways of scaling the axes of parallel-coordinates displays with the aim of supporting particular types of tasks. Reference [22] proposes an extension of the parallel-coordinates technique to large data sets. In [23], we introduce our extension of the cumulative-curve technique that generalises the ideas of histograms and the Lorenz curve.
The next group of publications reflects our work on visual data mining - the combination of interactive visualisation with computational methods of data analysis. We have proposed some methods for the visualisation of data-mining outputs and for the use of various data-mining techniques in combination with thematic maps [24]. In [22], we suggest some specific visualisation enhancements for cluster analysis. Reference [25] describes the integration of two software research prototypes: Descartes for geographic visualisation, and Kepler for data mining.
A significant part of our research relates to multicriteria decision analysis. We have highlighted the importance of visualisation for this kind of activity and proposed several visualisation techniques supporting various computational optimisation methods [26], as well as purely visual and interactive decision support methods that suit a variety of individual decision- making styles [27]. In [28], we discuss the value of display coordination for making informed, well-grounded spatial decisions.
In several publications, we describe the application of our tools and data exploration methods in various domains: simulation modelling [29, 30], forestry [31], seismology [32], and official statistics [23, 33].
1. Andrienko, G., Andrienko, N.: Interactive maps for visual data exploration. International Journal of Geographical Information Science 13(4), 355-374 (1999) 2. Andrienko, G., Andrienko, N.: Data characterization schema for intelligent support in visual data analysis. In: Spatial Information Theory - Cognitive and Computational Foundations of Geographic Information Science, COSIT'99, ed. by Freksa, C., Mark, D., Lecture Notes in Computer Science, Vol. 1661 (Springer, Berlin, Heidelberg 1999) pp. 349-366 3. Andrienko, G., Andrienko, N.: Knowledge engineering for automated map design in DESCARTES. In: Advances in Geographic Information Systems, ed. by Medeiros, C.B., 7th International Symposium ACM GIS'99, Kansas City, November 1999 (ACM Press, New York 1999) pp. 66-72 4. Andrienko, G., Andrienko, N.: AFORIZM approach: creating situations to facilitate expertise transfer. In: EKAW'94: a Future for Knowledge Acquisition, ed. by Steels, L., Schreiber, G., Van de Velde, W., Lecture Notes in Artificial Intelligence, vol. 867 (Springer, Berlin, Heidelberg 1994) pp. 244-261 5. Andrienko, G., Andrienko, N.: Making a GIS intelligent: CommonGIS project view. In: AGILE'99 Conference, Rome, April 1999, pp. 19-24 6. Andrienko, N., Andrienko, G.: Intelligent support for geographic data analysis and decision making in the Web. Journal of Geographic Information and Decision Analysis 5(2), 115-128 (2001) 7. Andrienko, G., Andrienko, N., Savinov, A.: Choropleth maps: classification revisited. In: Proceedings of ICA 2001, Beijing, Vol.2, pp. 1209-1219 (2001) 8. Andrienko, G., Andrienko, N., Gitis, V.: Interactive maps for visual exploration of grid and vector geodata. ISPRS Journal of Photogrammetry and Remote Sensing 57(5-6), 380-389 (2003) 9. Andrienko, N., Andrienko, G., Voss, H., Bernardo, F., Hipolito, J., Kretchmer, U.: Testing the usability of interactive maps in CommonGIS. Cartography and Geographic Information Science 29(4), 325-342 (2002) 10. Andrienko, G., Andrienko, N.: Computer cartography and cartographic knowledge. In: Diskussionsbeitrge zur Kartosemiotik und zur Theorie der Kartographie, Heft 4, ed. by Wolodtschenko, A., Schlichtmann, H. (Selbstverlag der Technischen Universitt Dresden, Dresden 2001) pp. 7-14 11. Fairbain, D., Andrienko, G., Andrienko, N., Buziek, G., Dykes, J.: Representation and its relationship with cartographic visualization: a research agenda. Cartography and Geographic Information Science 28(1), 13-28 (2001) 12. Andrienko, G., Andrienko, N., Dykes, J., Gahegan, M., Mountain, D., Noy, P., Roberts, J., Rodgers, P., Theus, M.: Creating instruments for ideation: software approaches to geovisualization. In: Exploring Geovisualization, ed. by Dykes, J., MacEachren, A., Kraak, M.-J. (Elsevier, Oxford 2005) pp 103-125 13. Andrienko, N., Andrienko, G., Gatalsky, P.: Exploratory spatio-temporal visualization: an analytical review. Journal of Visual Languages and Computing 14(6), 503-541 (2003) 654 Appendix II: A Guide to Our Major Publications Relevant to the Contents of This Book 14. Andrienko, N., Andrienko, G., Gatalsky, P.: Impact of data and task characteristics on design of spatio-temporal data visualization tools. In: Exploring Geovisualization, ed. by Dykes, J., MacEachren, A., Kraak, M.-J. (Elsevier, Oxford 2005) pp. 201-222 15. Andrienko, N., Andrienko, G., Gatalsky, P.: Supporting visual exploration of object movement. In: Proceedings of the Working Conference on Advanced Visual Interfaces AVI 2000, ed. by Di Ges, V., Levialdi, S., Tarantino L., Palermo, May 2000 (ACM Press, New York 2000) pp. 217-220 16. Andrienko, N., Andrienko, G., Gatalsky, P.: Exploring changes in census time series with interactive dynamic maps and graphics. Computational Statistics 16(3), 417-433 (2001) 17. Andrienko, N., Andrienko, G.: Interactive visual tools to explore spatiotemporal variation. In: (Ed.) Proceedings of the Working Conference on Advanced Visual Interfaces AVI 2004, ed. by Coastabile, M.F., Gallipoli, May 2004, (ACM Press, New York 2004) pp. 417-420 18. Andrienko, N., Andrienko, G., Gatalsky, P.: Tools for visual comparison of spatial development scenarios. In: IV 2003. 7th International Conference on Information Visualization, Proceedings, ed. by Banissi, E., London, July 2003 (IEEE Computer Society, Los Alamitos 2003) pp. 237-244 19. Gatalsky, P., Andrienko, N., Andrienko, G.: Interactive analysis of event data using space-time cube. In: IV 2004. 8th International Conference on Information Visualization, Proceedings, ed. by Banissi, E., London, July 2004, (IEEE Computer Society, Los Alamitos 2004) pp. 145-152 20. Andrienko, G., Andrienko, N.: Exploring Spatial Data with Dominant Attribute Map and Parallel Coordinates. Computers, Environment and Urban Systems 25(1), 5-15 (2001) 21. Andrienko, G., Andrienko, N.: Constructing parallel coordinates plot for problem solving. In: 1st International Symposium on Smart Graphics, ed by Butz, A., Krger, A., Oliver, P., Zhou, M., Hawthorne, NY, March 2001, (ACM Press, New York 2001) pp. 9-14 22. Andrienko, G., Andrienko, N.: Blending aggregation and selection: adapting parallel coordinates for the visualisation of large datasets. The Cartographic Journal 42(1), 49-60 (2005) 23. Andrienko, N., Andrienko, G.: Cumulative curves for exploration of demographic data: a case study of northwest England. Computational Statistics 19(1), 9-28 (2004) 24. Andrienko, N., Andrienko, G., Savinov, A., Voss, H., Wettschereck, D.: Exploratory analysis of spatial data using interactive maps and data mining. Cartography and Geographic Information Science 28(3), 151-165 (2001) 25. Wrobel, S., Andrienko, G., Andrienko, N., Luthje, A.: Kepler and Descartes. In: Handbook of Data Mining and Knowledge Discovery, ed. by Kloesgen, W., Zytkow, J. (Oxford University Press, New York 2002) pp. 576-583 References 655 26. Jankowski, P., Andrienko, N., Andrienko: G., Map-centered exploratory approach to multiple criteria spatial decision making. International Journal of Geographical Information Science 15(2), 101-127 (2001) 27. Andrienko, G., Andrienko, N., Jankowski, P.: Building spatial decision support tools for individuals and groups. Journal of Decision Systems 12(2), 193-208 (2003) 28. Andrienko, N., Andrienko, G.: Informed spatial decisions through coordinated views. Information Visualization 2(4), 270-285 (2003) 29. Chertov, O., Komarov, A., Andrienko, G., Andrienko, N., Gatalsky, P.: Integrating forest simulation models and spatial-temporal interactive visualisation for decision making at landscape level. Ecological Modelling 148(1), 47-65 (2002) 30. Chertov, O., Komarov, A., Mikhailov, A., Andrienko, G., Andrienko, N., Gatalsky, P.: Geovisualization of forest simulation modelling results: a case study of carbon sequestration and biodiversity. Computers and Electronics in Agriculture 49(1), 175-191 (2005) 31. Schuck, A., Andrienko, G., Andrienko, N., Folving, S., Kohl, M., Miina, S., Paivinen, R., Richards, T., Voss, H.: The European Forest Information System - an Internet based interface between information providers and the user community. Computers and Electronics in Agriculture 47(3), 185-206 (2005) 32. Gitis, V., Andrienko, G., Andrienko, N.: Exploration of seismological information in analytical Web-GIS. Izvestya Physics of the Solid Earth 40(3), 216-225 (2004) 33. Andrienko, G., Andrienko, N., Voss, H., Carter, J.: Internet mapping for dissemination of statistical information. Computers, Environment and Urban Systems 23(6), 425-441 (1999)