Open government or hide in plain sight?

The datasets available at are bulging with information. Can someone please tell me how to make sense of it all?

I’m all for open government and easy access to data on how the government spends our money.

But so far, the data available at isn’t providing much in terms of insights.

The file is huge and difficult to work with. The next quarterly reporting period ends Jan. 10, so there is little doubt in my mind that the next release will be even bigger as more stimulus money makes its way to contractors.

Frankly, I’ve struggled with the spreadsheet for the last quarter of government fiscal 2009. The question that keeps going through my mind is: How are we supposed to use this thing?

There are obvious answers – who has won what and for how much? Taking the time to sort by NAICS codes yielded some results.

For example, IBM Corp., had a $43 million contract to help with the digital TV crossover. Booz Allen Hamilton won a $30 million contract to help build a system to manage grants to bring broadband services to underutilized areas.

However, to find those rather straightforward results took me several hours of trial and error during which I struggled to interpret column headers in the spreadsheet.

I’m not a whiz with Excel and I don’t have the strongest data analysis skills, but that’s sort of my point. Why do I need those skills to understand what the government and its contractors are doing?

That’s my nagging fear with the push for transparency. We get this flood of data but might miss the insights.

At the same time, I’m not sure what the alternative is. I’d rather have the data out there, even if I can’t make great use of it, than for it not to be out there at all.

In the meantime, we’ll probably see a growing cottage industry of data analysts who can slice and dice the spreadsheets and issue any number of reports – for a fee, of course.

My hope is that some reader will offer me some tips on how to wrestle this spreadsheet into something useful – what NAICS codes are you looking at? What columns of information are you finding most valuable?