Iraq Trend Data: O'Hanlon's Testimony to the Foreign Relations Committee

Michael O'Hanlon who is the lead author of the Brookings Iraq Index testified last week before the Senate Foreign Relations Committee. Here's the 4 page text of his January 10th testimony.

The last two pages show a relatively easy to read and understand printed table. The table lists, all in one place, what I assume to be what O'Hanlon thinks are the 30 key factors on the ground in Iraq and how they have varied year by year from November 2003 to November 2006.

Here's a version of that table that I have edited for even better visibility and to keep it from covering two pages. (please click on image for full size view):

The four data columns of the table show the trends for those factors with the data values being captured for the month of November in each of the past 4 years. From a standpoint of printed table readability, limiting the number of trend samples to 4 makes this table much more suited for direct human consumption at the cost of reducing overall trend data quality compared to a set of trend samples for a given factor that showed how that factor changes every month.

While most people are not comfortable with reading tables, this one is actually readable and understandable with the application of a modest amount of effort. Please let us know what you think?

This table as text is of course not a readily-reusable (RR) file. However, it was relatively straightforward for us to convert it into RR format and you can download your own copy by right clicking on ohanlon-key-factors.csv. This RR file is ready for examination with Microsoft Excel or even better with the T4 & Friends tools TLViz or CSVPNG.

You will note that the layout of the data has been inverted with the data rows now representing the 4 monthly sample reading time periods, and the 30 data columns representing the 30 key factors which is the orientation required for TLViz and CSVPNG. This makes for a very wide page, but of course, when using TLViz or CSVPNG to examine the trend data, we do not actually need to read it.

In our next post, we will show you why this conversion from printed table to RR format is so helpful in the way it allows the tabular data to come alive in visual form with very little effort by using a tool such as TLViz.