Abstract
Recently, the expertise accumulated in the field of geovisualization has found application in the visualization of abstract multidimensional data, on the basis of methods called spatialization methods. Spatialization methods aim at visualizing multidimensional data into low-dimensional representational spaces by making use of spatial metaphors and applying dimension reduction techniques. Spatial metaphors are able to provide a metaphoric framework for the visualization of information at different levels of granularity. The present paper makes an investigation on how the issue of granularity is handled in the context of representative examples of spatialization methods. Furthermore, this paper introduces the prototyping tool Geo-Scape, which provides an interactive spatialization environment for representing and exploring multidimensional data at different levels of granularity, by making use of a kernel density estimation technique and on the landscape “smoothness” metaphor. A demonstration scenario is presented next to show how Geo-Scape helps to discover knowledge into a large set of data, by grouping them into meaningful clusters on the basis of a similarity measure and organizing them at different levels of granularity.
Similar content being viewed by others
References
Skupin A (2000) From metaphor to method: cartographic perspectives on information visualization [C]. Proceedings of the IEEE Symposium on Information Visualization, Salt Lake City, Utah
Demsar U (2006) Data mining of geospatial data: combining visual and automatic methods [D]. Sweden: KTH — Royal Institute of Technology
Card S K, Mackinlay J D, Shneiderman B (1999) Trees [M]. Readings in Information Visualization. Card S K, Mackinlay J D, Shneiderman B, (Eds.). San Francisco: Morgan Kaufmann Publishers
Kuhn W, Blumenthal B (1996) Spatialization: spatial meta phors for user interfaces [R]. Reprinted Tutorial Notes from the ACM Conference on Human Factors in Computing Systems in Vancouver, GeoInfo 8, Department of Geoinformation, Technical University of Vienna
Dieberger A, Frank A U (1998) A city metaphor for supporting navigation in complex information spaces [J]. Journal of Visual Languages and Computing, 9: 597–622
Derthick M, Christel M, Hauptmann A, et al. (2003) A cityscape visualization of video perspectives [C]. Proceedings of the National Academy of Sciences, Irvine, CA
Wettel R, Lanza M (2008) CodeCity: 3D visualization of large-scale software [C]. Companion of the 30th International Conference on Software Engineering, Leipzig, Germany
Fabrikant S I, Buttenfield B P (2001) Formalizing semantic spaces for information access [J]. Annals of the Association of American Geographers, 91(2): 263–280
Benking H, Judge A J N (1994) Design considerations for spatial metaphors: reflections on the evolution of viewpoint rransportation systems [OL]. http://www.uia.org/uiadocs/spatialm.htm
Wise J A (1999) The ecological approach to text visualization [J]. Journal of the American Society for Information Science, 50(13): 1224–1233
Boyack K W, Wylie B N, Davidson G S (2002) Domain visualization using VxInsight for science and technology management [J]. Journal of the American Society for Information Science and Technology, 53(9): 764–774
Zavesky E, Chang S F, Yang C C (2008) Visual islands: intuitive browsing of visual search results [C]. Proceedings of the 2008 International Conference on Content-based Image and Video Retrieval, Niagara Falls
Martinez A A, Dolado Cosin J J, Presedo Garcia C (2008) A landscape metaphor for visualization of software projects [C]. Proceedings of the 4th ACM Symposium on Software Visualization, Ammersee, Germany
Skupin A, Buttenfield B P (1997) Spatial metaphors for display of information spaces [C]. Proceedings of the International Research Symposium on Computer-based Cartography AUTO-CARTO 13, Seattle, WA
Kontaxaki S, Tomai E, Kokla M, et al.(2010) Visualizing multidimensional data through granularity-dependent spatialization [C]. Proceedings of the SPIE Conference on Visualization and Data Analysis 2010, San Jose, Califormia
Kohonen T (1995) Self-organizing maps [M]. Berlin: Springer-Verlag
Joliffe I T (2002) Principal component analysis [M]. New York: Springer-Verlag
Mardia K V, Kent J T, Bibby J M (1980) Multivariate analysis (probability and mathematical statistics) [M]. London: Academic Press
Ultsch A (1993) Self-organizing neural networks for visualization and classification [M]. Information and Classification-Concepts, Methods, and Applications. Opitz O, Lausen B, Klar R (Eds.). Berlin: Springer-Verlag
Vesanto J, Himberg J, Alhoniemi E, et al.(2000) SOM toolbox for Matlab 5 [R]. Technical Report A57, Helsinki University of Technology, Finland
Kohonen T, Kaski S, Lagus K, et al. (2000) Self organization of a massive document collection [J]. IEEE Transactions on Neural Networks, 11(3): 574–585
Skupin A (2001) Cartographic considerations for maplike interfaces to digital libraries [OL]. http://www.indiana.edu/visual01/skupin.pdf. Last date accessed 10.2009
Skupin A (2002) A Cartographic approach to visualizing conference abstracts [J]. IEEE Computer Graphics and Applications, 22(1): 50–58
Berkhin P (2006) A Survey of clustering data mining techniques [M]. Grouping Multidimensional Data-Recent Advances in Clustering. Kogan J, Teboulle M, Nicholas C, (Eds.). Berlin, Heidelberg, New York: Springer
Gorg C, Pohl M, Qeli E, et al. (2006) Visual representations [M]. Human-Centered Visualization Environments. Kerren A, Ebert A, Meyer J, (Eds.). Berlin, Heidelberg: Springer
Lakoff G, Johnson M (1980) Metaphors we live by [M]. Chicago: The University of Chicago Press
Skupin A, Fabrikant S I (2003) Spatialization methods: a cartographic research agenda for non-geographic information visualization [J]. Cartography and Geographic Information Science, 30(2): 95–119
Kulyk O, Kosara R, Urquiza J, et al.(2006) Human-centered aspects [B]. Human-Centered Visualization Environments. Kerren A, Ebert A, Meyer J, (Eds.). Berlin, Heidelberg: Springer
Nollenburg M (2006) Geographic Visualization [M]. Human-Centered Visualization Environments. Kerren A, Ebert A, and Meyer J, (Eds.). Berlin, Heidelberg: Springer
Author information
Authors and Affiliations
Corresponding author
Additional information
Sofia Kontaxaki received her Diploma in Electrical and Computer Engineering from the National Technical University of Athens (NTUA) in 1993, and her MScE degree in Geoinformatics from the same University in 2002. From 1993 to 1999, she worked as a computer engineer at Intrasoft S.A, an IT Service Provision company, providing services in the fields of systems development and integration, systems management and managed services. She is currently at the Ministry of Education, Lifelong Learning and Religious Affairs, working as an Informatics Teacher in the Secondary Education. At the same time, she is a Ph.D. candidate in the Department of Rural and Surveying Engineering of the NTUA. Her research interests include information visualization and especially spatialization, knowledge representation and extraction, geospatial ontology integration, and semantic interoperability.
About this article
Cite this article
Sofia, K., Margarita, K. & Marinos, K. Geo-scape, a granularity depended spatialization tool for visualizing multidimensional data sets. Geo-spat. Inf. Sci. 13, 275–284 (2010). https://doi.org/10.1007/s11806-010-0385-8
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11806-010-0385-8