Abstract
It is a well-known fact that large fractions of human population consume information more quickly when expressed in diagrams/pictures than when presented as text or numbers. Complex data, when represented by a single image, can be quickly absorbed by the human mind. Especially when the data is abstract, such as relationships, geographical coordinates etc., data visualization reinforces human cognition in finding patterns. We can think of visualization as an alternate data mining technique in contrast to the methods we have already touched upon, like time series analysis, machine learning etc. Visualization is a pictographic representation of data or concepts. It is the process of representing data as a visual image. In this chapter, we will go beyond simple visualization such as scatter plots and histograms; and focus on representing more complex data as images for the purpose of detecting patterns in schematic distribution of the data.
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References
Krzywinski, M., Birol, I., Jones, S. J., & Marra, M. A. (2012). Hive plots—rational approach to visualizing networks. Briefings in Bioinformatics, 13(5), 627–644.
Weber, M., Alexa, M., & Müller, W. (2001). Visualizing time-series on spirals, Proceedings of the IEEE Symposium Information Visualization (InfoVis ’01), pp. 7–14, Oct. 2001.
Martin, S., Brown, W. M., Klavans, R., & Boyack, K. W. (2011, January). OpenOrd: An open-source toolbox for large graph layout. In IS&T/SPIE Electronic Imaging. (pp. 786806–786806-11). International Society for Optics and Photonics.
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Roy, S.D., Zeng, W. (2015). Data Visualization: Gazing at Ripples. In: Social Multimedia Signals. Springer, Cham. https://doi.org/10.1007/978-3-319-09117-4_12
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DOI: https://doi.org/10.1007/978-3-319-09117-4_12
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