What makes something “Information Visualization?” Is it just visual titillation? Or is it a tool that interprets, analyzes, and facilitates deeper understanding of data?
Visualization is a technique to graphically represent sets of data. When data is large or abstract, visualization can help make the data easier to read or understand. There are visualization tools for search, music, networks, online communities, and almost anything else you can think of. Whether you want a desktop application or a web-based tool, there are many specific tools are available on the web that let you visualize all kinds of data. Here are some of the best:
The burgeoning interest in R demonstrates that there’s demand for analytics to solve real, business-critical problems in a broad spectrum of companies and roles, and that some of the incumbent analytics offerings, in particular SAS and SPSS, don’t sufficiently meet the growing need for analytics in many major companies. Annotated link http://www.diigo.com/bookmark/http%3A%2F%2Fspotfire.tibco.com%2Fcommunity%2Fblogs%2Fenterpriseanalytics%2Farchive%2F2009%2F01%2F08%2Fanalytics-in-the-nyt.aspx
We propose a joint optical flow and principal component analysis (PCA) method for motion detection. PCA is used to analyze optical flows so that major optical flows corresponding to moving objects in a local window can be better extracted. This joint approach can efficiently detect moving objects and more successfully suppress small turbulence. It is particularly useful for motion detection from outdoor videos with low quality. It can also effectively delineate moving objects in both static and dynamic background. Experimental results demonstrate that this approach outperforms other existing methods by extracting the moving objects more completely with lower false alarms.
I. Cadez, D. Heckerman, C. Meek, P. Smyth, and S. White. Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, page 280--284. New York, NY, USA, ACM, (2000)
F. Hermans, M. Pinzger, and A. van Deursen. (2011)cite arxiv:1111.6895Comment: 9 Pages, 5 Colour Figures; Proc. European Spreadsheet Risks Int. Grp. (EuSpRIG) 2011 ISBN 978-0-9566256-9-4.