Abstract
Most statistical graphics on theWeb are static, noninteractive and undynamic, even though other statistical analysis systems usually provide various interactive statistical graphics. Interactive and dynamic graphics, see Symanzik (2004), can be implemented using Internet technologies such as Java or Flash (Adobe, 2007). Scalable Vector Graphics (SVG) and Extensible 3D (X3D) offer alternative means of realizing an XML-based graphics format. One advantage of using XML is that data from a wide range of research topics are easy to deal with, because they are all presented in the XML format. Another advantage is that XML is a text-based graphics format, i.e., it is scriptable, meaning that it can be generated dynamically by a statistical analysis system or web application. Before introducing XML-based graphics, we introduce the relationship between theWeb, XML, and statistical graphics.
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References
Boyens, C., Günther, O. and Lenz, H.-J. (2004). Statistical Databases. In: Gentle, J.E., Härdle, W., Mori, Y. (eds) Handbook of Computational Statistics – Concepts and Methods. Springer, Berlin.
Eisenberg, J.D. (2002). SVG Essentials. O’Reilly, Sebastopol, CA.
Fitzgerald, M. (2004). XML Hacks. O’Reilly, Sebastopol, CA.
Fujino, T., Yamamoto, Y. and Tarumi, T. (2004). Possibilities and Problems of the XML-Based Graphics in Statistics. In: Antoch, J. (ed) COMPSTAT2004 Proceedings in Computational Statistics. Physica, Heidelberg, pp. 1043–1052.
Geroimenko, V. and Chen, C. (eds) (2004). Visualizing Information Using SVG and X3D. Springer, Berlin.
Geroimenko, V. and Chen, C. (eds) (2003). Visualizing the Semantic Web. Springer, Berlin.
Härdle, W., Klinke, S. and Müller, M. (2000). XploRe Learning Guide. Springer, Berlin.
Haselett, J., Bradley, R., Craig, P., Unwin, A. and Wills, G. (1991). Dynamic Graphics for Exploring Spatial Data With Application to Locating Global and Local Anomalies. The American Statistician, 45(3):234–242.
Klinke, S. (2004). Statistical User Interfaces. In: Gentle, J.E., Härdle, W., Mori, Y. (eds) Handbook of Computational Statistics – Concepts and Methods. Springer, Berlin.
Marchette, D.J. (2004). Network Intrusion Detection. In: Gentle, J.E., Härdle, W., Mori, Y. (eds) Handbook of Computational Statistics – Concepts and Methods. Springer, Berlin.
Meyer, D., Leisch, F., Hothorn, T. and Hornik, K. (2004). StatDataML: An XML Format for Statistical Data. Computational Statistics, 19(3):493–509.
Mori, Y., Fujino, T., Yamamoto, Y. and Tarumi, T. (2004). XML-based Applications in Statistical Analysis. In: Proceedings of Interface 2004: Computational Biology and Bioinformatics, 36th Symposium on the Interface, 26–29 May 2004, Baltimore, MD.
Mori, Y., Fujino, T., Yamamoto, Y., Kubota, T. and Tarumi, T. (2004). XML-based Applications in Statistical Analysis. In: Proceedings of Interface 2004: Computational Biology and Bioinformatics, 36th Symposium on the Interface (CD-ROM), 26–29 May 2004, Baltimore, MD.
Symanzik, J. (2004). Interactive and Dynamic Graphics. In: Gentle, J.E., Härdle, W., Mori, Y. (eds) Handbook of Computational Statistics – Concepts and Methods. Springer, Berlin.
Wilhelm, A. (2004). Data and Knowledge Mining. In: Gentle, J.E., Härdle, W., Mori, Y. (eds) Handbook of Computational Statistics – Concepts and Methods. Springer, Berlin.
Yamamoto, Y., Iizuka, M. and Fujino, T. (2005). Consideration for Developing Environments of Web-based Interactive Statistical Graphics. 55th Session, International Statistical Institute, Sydney, Australia.
@d Project (2006). @d – Data Oriented Statistical System. http://mo161.soci.ous.ac.jp/@d/
Adobe (2007). Flash. http://www.macromedia.com/flash/
Adobe (2007). SVG Viewer. http://www.adobe.com/svg/
Apache Software Foundation (2007). Batik SVG Toolkit. http://xml.apache.org/batik/
BMBF (2007). EMILeA Stat. http://www.emilea.de/
DandD Project (2007). http://stat.math.keio.ac.jp/DandDIV/
DASL Project (1996). DASL – The Data and Story Library. http://lib.stat.cmu.edu/DASL/
ISR, Univ. Michigan (2007). ICPSR (The Interuniversity Consortium for Political and Social Research). http://www.icpsr.umich.edu/
Luciani, T.J. (2005). Scalable Vector Graphics for R: RSvgDevice. http://www.darkridge.com/ jake/RSvg/
MD*Tech (2005). XploRe e-books. http://www.xplore-stat.de/ebooks/ebooks.html
MD*Tech (2007). XploRe homepage. http://www.xplore-stat.de/
MD*Tech (2007). MD*Base. http://www.quantlet.org/mdbase/
MD*Tech (2007). MM*Stat. http://www.quantlet.com/mdstat/mmstat.html
Meyer, D. (2004). The StatDataML Package. http://www.omegahat.org/StatDataML/
Octaga AS (2007). Homepage. http://www.octaga.com/
Open Geospatial Consortium (2004). GML – the Geograpy Markup Language. http://opengis.net/gml/
Project CASE (2007). Homepage (in Japanese). http://case.f7.ems.okayama-u.ac.jp/
Project Jasp (2005). Jasp – Java-Based Statistical Processor. http://jasp.ism.ac.jp/index-e.html
R Project (2007). Homepage. http://www.r-project.org/
UCLA Department of Statistics (2007). Homepage. http://www.stat.ucla.edu/
University of Hagen (2007). Multimedia Project: New Statistics. http://www.fernuni-hagen.de/newstatistics/
Vlachos, P. (2007). Statlib – Data, Software and News from the Statistics Community. http://lib.stat.cmu.edu/
W3C (World Wide Web Consortium). http://www.w3.org/
W3C (2007). Semantic Web. http://www.w3.org/2001/sw/
W3C (2007). SMIL, the Synchronized Multimedia Integration Language. http://www.w3.org/AudioVideo/
W3C (2007). SVG (Scalable Vector Graphics). http://www.w3.org/Graphics/SVG/
Web3D Consortium (2007). Homepage. http://www.web3d.org/
Web3D Consortium (2007). X3D: Extensible 3D. http://www.web3d.org/x3d/
WISE Project (2007). WISE – Web Interface for Statistical Education. http://wise.cgu.edu/
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Yamamoto, Y., Iizuka, M., Fujino, T. (2008). Web-Based Statistical Graphics using XML Technologies. In: Handbook of Data Visualization. Springer Handbooks Comp.Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-33037-0_29
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DOI: https://doi.org/10.1007/978-3-540-33037-0_29
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