“Topics on Aesthetic Data Visualization: Viewpoints, Interpretation, and Alternative Senses” by Park

Conference:


Title:

    Topics on Aesthetic Data Visualization: Viewpoints, Interpretation, and Alternative Senses

Presenter(s):



Abstract:


    Aesthetic data visualization, which looks at complex data sets from an ingenious perspective, is difficult to empirically organize due to its insufficient records. Fortunately, insightful artists and curators have recently provided some notable interdisciplinary exhibitions and publications. This author was a recent participant at such an event; however, it is not easy to summarize the various projects into a single vision because each artist’s value, method, philosophy, and aesthetic preference are unique. This paper categorizes data visualization based on various topics. Aesthetic data visualization is similar to conventional data visualization in that it organizes ambiguous data into a database. Artists then tend to integrate the information into their art. In this regard, it might be possible to identify tendencies and examine data as contemporary iconology, as well as discover hidden possibilities of recent aesthetic data visualizations.

References:


    BEVILACQUA, F. 2002. 3D motion capture data: motion analysis and mapping to music. Proceedings of the Workshop/ Symposium on Sensing and Input for Media-centric Systems.

    BEVILACQUA, F., NAUGLE, L., VALVERDE, I. 2001. Virtual dance and music environment using motion capture. Proceedings of the IEEE Multimedia Technology And Applications Conference 2001. Burke, J. 2002. Interactive performance environments and the visualization of actor movement. Digital Creativity, 13, 2, 122128.

    CAMURRI, A., MAZZARINO, B., RICCHETTI, M., TIMMERS, R., VOLPE, G. 2004. Multimodal analysis of expressive gesture in music and dance performances. Lecture Notes in Computer Science, 2915.

    CARD, S. K., MACKINLAY, J. D., SHNEIDERMAN, B. 1999. Readings in information visualization: using vision to think. Academic Press.

    CAWTHON, N., MOERE, A. V. 2007. The Effect of Aesthetic on the Usability of Data Visualization. Proceedings of Information Visualization 2007 (Jul.), 637-648.

    CORBY, T. 2008. Landscapes of Feeling, Arenas of Action: Information Visualization as Art Practice. Leonardo, 41, 5, MIT Press, 460-467.

    DISALYO, C. F. 1999. Philosophy and Visual Representation: Imaging the Impossible. Leonardo, 32, 2, MIT Press, 83-86.

    DOWNIE, M. and Massachusetts Institute of Technology, Dept. of Architecture, 2005. Program in Media Arts and Sciences Choreographing the Extended Agent: performance graphics for dance theater. Massachusetts Institute of Technology.

    GAVIRIA, A. R. 2008. When Is Information Visualization Art? Determining the Critical Criteria. Leonardo, 41, 5, MIT Press, 479-482.

    GOMBRICH, E. H. 2000. Art and Illusion. Princeton University Press. GOODMAN, N. 1978. Ways of Worldmaking. Hackett Pub Co Inc..

    KOSARA, R. 2007. Visualization Criticism: The Missing Link Between Information Visualization and Art. Proceedings of Information Visualization 2007 (Jul.), 631-636.

    KURBAK, E. News Knitter. http://casualdata.com/newsknitter/.

    LAFAYETTE, C., PARKE, F., MCNAMARA, A., GALANTER, P. 2009. I’m not there: extending the range of human senses to benefit wildlife corridors. Proceedings of ACM SIGGRAPH 2009, Art Gallery, ACM.

    LAU, A., MOERE, A. V. 2007. Towards a Model of Information Aesthetic Visualization. Proceedings of Information Visualization 2007 (Jul.), 87-92.

    MANOVICH, L. Cultural Analytics. http://manovich.net/culturalanalytics/.

    MÜLLER, B. 2006. Poetry on the Road. http://www.esono.com. PARK, J. W. 2011. Information Aesthetics with Visual Genealogy Project. Leonardo, 44, 5, MIT Press, 464-465.

    PARK, J. W., CHOE, G. 2009. Visual Genealogy. Proceedings of ACM SIGGRAPH 2009, Art Gallery, ACM. PALAZZI, M. 2007. Synchronous Objects for One Flat Thing, Reproduced. http://synchronousobjects.osu.edu/.

    POUMAN, Z., STASKO, J. T., MATEAS, M. 2007. Casual Information Visualization: Depictions of Data in Everyday Life. IEEE Trans. Visualization and Computer Graphics, 13, 6, 1145-1152.

    PSARRA, S. 2009. Architecture and Narrative: The Structure of Space and Cultural Meaning, Routledge. TUFTE, E. R., 2001. The Visual Display of Quantitative Information. Graphics Press.

    TUKEY, W. J. 1965. The Technical Tools of Statistics. American Statistician.

    VIÉGAS, F. B., WATTENBERG, M. 2007. Artistic Data Visualization: Beyond Visual Analytics. Lecture Notes in Computer Science, 4564, 182-191.

    WEST, R., LEWIS, J. P., MARGOLIS, T., GOSSMANN, J., SCHULZE, J., TENEDORIO, D., SINGH, R. 2009. Multiscale Meta-Shape Grammar Objects for: …a grain of sand turns the balance and ATLAS in silico. Proceedings of ACM SIGGRAPH 2009, Art Gallery, ACM.

    WOOLMAN, M. 2002. Digital Information Graphics. WatsonGuptill.

    XU, R. R., ZHAI, S. H. Out of Statistics: Beyond Legal. 2009. http://floatingcube.org/beyondlegal/.


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Art Paper/Presentation Type: