Visualization of the use of temporal vs spatial language in book titles over time (and space).

SELECT DAY(checkOut), MONTH(checkOut), YEAR(checkOut), SUM(CASE WHEN ((title LIKE '%chron%' OR title LIKE '%temp%' OR title LIKE '%time%' OR title LIKE '%pre%' OR title LIKE '%post%' OR title LIKE '%before%' OR title LIKE '%after%' OR title LIKE '%ever%' OR title LIKE '%eter%' OR title LIKE '%ago%' )) THEN 1 ELSE 0 END) AS time, SUM(CASE WHEN ((title LIKE '%trans%' OR title LIKE '%space%' OR title LIKE '%aero%' OR title LIKE '%astro%' OR title LIKE '%aster%' OR title LIKE '%gon%' OR title LIKE '%spat%' OR title LIKE '%left%' OR title LIKE '%right%' OR title LIKE '%above%' OR title LIKE '%under%' OR title LIKE '%behind%' OR title LIKE '%front%' )) THEN 1 ELSE 0 END) AS space SUM(CASE WHEN ((title LIKE '%trans%' OR title LIKE '%aero%' OR title LIKE '%astro%' OR title LIKE '%aster%' OR title LIKE '%gon%' OR title LIKE '%space%' OR title LIKE '%spat%' OR title LIKE '%left%' OR title LIKE '%right%' OR title LIKE '%above%' OR title LIKE '%under%' OR title LIKE '%behind%' OR title LIKE '%front%') AND (title LIKE '%chron%' OR title LIKE '%temp%' OR title LIKE '%time%' OR title LIKE '%pre%' OR title LIKE '%post%' OR title LIKE '%before%' OR title LIKE '%after%' OR title LIKE '%ever%' OR title LIKE '%eter%' OR title LIKE '%ago%')) THEN 1 ELSE 0 END) AS trans FROM spl3._rawXmlDataCheckOuts WHERE DATE(checkOut) > '2005-12-31' AND DATE(checkOut) <= '2014-12-31' GROUP BY DAY(checkOut) , MONTH(checkOut) , YEAR(checkOut) ORDER BY YEAR(checkOut) , MONTH(checkOut) , DAY(checkOut)

For this project, I wanted to find out whether there is a detectable difference in regards to the usage of time and space in item titles. I enquired about the number of checkouts per day that include either temporal verbiage, spatial verbiage or both (trans). The query is by no means exhaustive, but covers some of the most common words and roots.
For the visualization, I chose a spiral graph in which each revolution captures one year in the period from 2006 to 2013. Each cell represents the number of checkouts for that particular day in one of the three categories. The further the cells are away from the center, the higher the number of checkouts.

Two observations become readily apparent: Spatial language seems to be much less common in comparison to temporal language. Titles that include both domains are significantly rarer, still. Second, the shape of the graph also clearly indicates that the overall number of checkouts is largest towards the middle of the time period, and tapers off towards both ends.

I used Processing and MySQL_Workbench.

Control: (via controlp5 panel)
adjust time and checkout value scale
toggle categories on/off
hide/show labels, and adjust label size and opacity
invert colors
'n' to show checkout values per day

Source Code + Data