I'm drawing (choropleth) maps visualizing language use in big text corpora, e.g. words which are attributed to places. Currently I'm doing that using R and the cshapes Package (http://nils.weidmann.ws/projects/cshapes/r-package). I'm also experimenting with Nolan's and Lang's R package to produce interactive SVG graphs (http://www.omegahat.org/SVGAnnotation/SVGAnnotationPaper/SVGAnnotationPaper.html) to show tooltips on the map. As you can see here (http://www.bubenhofer.com/sprechtakel/2013/08/06/geocollocations-die-welt-der-zeit/) it works generally, but the resulting SVG (and also PDF) files are huge. There is also the problem of the SVG files produced in R, that all text is converted to vector graphics which again increases the complexity of the plot. This seems to be a known problem of SVG in R (http://stackoverflow.com/questions/17555331/how-to-preserve-text-when-saving-ggplot2-as-svg).
What are better means to produce interactive maps showing a lot of data?
Here I provide a example of input data to be visualized. The data is a tab separated text file consisting of place names (column name) geocoded and collocates to these place names with frequency information and a value of significance. I calculated the collocations in a text corpus of articles of ZEIT ONLINE (january to july 2013) as described here: http://www.bubenhofer.com/sprechtakel/2013/08/06/geocollocations-die-welt-der-zeit/
You are welcome to use this data for visualization experiments and I'd be happy if you shared your visualizations with me!
For interactive maps my first pick would be D3.js - as long as you don't need R for complex calculations. If you are already familiar with Tableau: Its mapping functionality has improved a lot as well...
Thanks a lot! I've come already across D3.js some months back, but I forgot about it. I'll try it!
I suggest head/tail breaks, if your data are heavy tailed.
Jiang B. (2015), Head/tail breaks for visualization of city structure and dynamics, Cities, 43, 69-77.
Jiang B. (2013), Head/tail breaks: A new classification scheme for data with a heavy-tailed distribution, The Professional Geographer, 65 (3), 482 – 494.
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