A Wordle is an interesting way to represent text. It creates a “word cloud” where the words are positioned and sized relative to how often they appear in the text. For example, the United States Constitution:
This alternate look at The Constitution gives us an interesting perspective. Although it may seem obvious, it is clear from the Wordle that the Founding Fathers placed a lot of emphasis on a few key parts of our government, the States and the President. It is interesting how the Wordle highlights the important parts of the constitution by simply using word counts!
This approach to analyzing text can also be applied to analyzing map data.
Follow the link above to get to the ArcGIS Online page for the application. I have included several example maps that make interesting Wordles, and a brief description of my thoughts as well. Feel free to click on one of the maps in the gallery or run a search for other maps, and see what Wordles you can make! If you get an error about the Wordle being unable to generate, it is probably because the map has no feature services or edit layers in it. There is not much I can do about that at the moment, so for the time being try another map. If you get an error on a map you think should work, please let me know.
One interesting map that is not in the gallery, is the map from Eagle’s PUG conference. Similar to Eagle’s GITA Map, attendees were able to create new features and submit them into the system for processing from a variety of inputs including: iPhone, iPad, Android, Web, DeLorme, Leica GeoSystems, and ArcGIS Mobile. This demo featured a workflow where the final step was “COMPLETE.” As you can see, “COMPLETE” features quite largely in the Wordle. If you look a little closer you can see a few other trends like top users. Interestingly, the most popular feature during PUG was a swimming pool, followed very closely by leak and well!
I plan to build future versions of the app to allow filters to be specified on data to remove things like “COMPLETE” and to use the coded domain values provided by the feature service to get more readable words and phrases. This should give us an interesting look into things!