Census 2000 Summary File 3 now online, Summary File 1 completed

With the new server online (see previous post), I finally have the disk space I need to really start building out the available data sets - I'm going from about 55GB on my old machine to just about 1100GB on the new one. (Well, technically, the "old" machine (my desktop) is newer than the "new" one, but since it was the first gCensus server, let's keep calling it "old").

The first beneficiary of this storage largesse has been Summary File 1. I've expanded the coverage from California, Oregon, and Pennsylvania to cover all 50 states plus the District of Columbia.

The second major step was to add Summary File 3, which covers a lot of interesting economic and housing statistics such as median and aggregate income, housing prices, and housing facilities. Fortunately, the file structure between SF1 and SF3 is very similar, so I was able to re-use most of the import code that I had already written for SF1. The coverage for SF3 is the same as for SF1 - all 50 states + DC.

It turns out in the end that my estimates of disk consumption were off - way off. I had originally believed that it would take 750-1000GB to store all of Summary File 1. Instead, it's taking about 410GB to store both SF1 and SF3. While my friends in the theory group would call that "a small constant factor", I prefer to think of it as "a whole lot of space". Consequently, if anyone has ideas for large (nationwide or even worldwide) data sets that would be cool to import, I'd like to hear about them.

New gCensus server online!

I have a big update here, so I'm breaking it into several pieces. The first part - the new gCensus hardware is finally up and running! I got the replacement motherboard from Intel and, luckily enough, everything actually came up on the first try.

Thanks to the generous donation by Ken Schmidt of Steel in the Air, I now have a fourth 400GB hard drive in the gCensus server, for a total of 1.2TB RAID5 storage. That brings the current specs of the machine up to the following:

- Intel D955XBK motherboard
- Intel Pentium EE 955 CPU (dual-core 3.46GHz with Hyperthreading)
- Zalman CNPS9500 cooler
- 2GB RAM
- 4x400GB Seagate HDD (3xSATA, 1xPATA)
- PC Power and Cooling Turbo-Cool 510ATX-SLI power supply
- Diamond Stealth 64 VRAM graphics

Everything except the PATA hard drive and the video card was a donation. I'd like to thank everyone who's helped me out with this equipment - I couldn't have done it without you!

Documentation now online

I've finally written up the first part of the gCensus documentation - that detailing the database backend code. It's up in both PostScript and PDF format.

Hardware diagnosis

After doing some testing, it looks like the power supply and motherboard died - which one triggered which is unclear. As far as I can tell, the other components (CPU, RAM, drives, video) all still work fine.

Loyd very graciously donated a replacement power supply that seems more than up to the task, and I've returned the motherboard to Intel for warranty replacement. With any luck, the replacement will be around in two weeks and I'll be able to get the new machine running again.

Hardware failures and gCensus GT downtime

At about 5PM today, my test server went up in smoke. I'm still trying to figure out exactly what failed, but in the meantime, gCensus-GT (which was hosted on that machine) will be unavailable.

gCensus-GT - Google Earth visualization for GeoTIFF files and more

Lisa Jordan, a geography professor at Florida State, recently pointed out to me that there's a wealth of GIS data out there in raster data formats that can't be viewed in the free Google Earth client. For example, Columbia University's Socioeconomic Data Analysis Center generates raster imagery for a variety of different data trends. Although it's possible get higher-resolution vector data (like the main gCensus app does), these files tend to be faster to render and provide a quick overview of relevant trends.

To fill this gap, I've just put out the gCensus-GT application (http://gecensus.stanford.edu/gcensus-gt), which allows you to visualize these raster formats in the free version of Google Earth. In addition to the GeoTIFF format SEDAC generates, gCensus-GT should be able to render any raster format supported by the open-source GDAL library (www.gdal.org) (but GeoTIFF is the only one I've had test data for). Comments are, as always, welcome.

If you're interested in doing this conversion on your home machine, I've released the core code behind it as a Python module named gdaltokmz; it's available at http://www.python.org/pypi/gdaltokmz. The module has a few dependencies (notably, the GDAL Python bindings and the ImageMagick graphics tools) and is licensed under the GPL.

gCensus Beta version, with new features

Since feature requests are coming in, I've decided to maintain a parallel version of the gCensus app where I develop new features. You can find it here:

http://gecensus.stanford.edu/gcensus-beta/ajax/gcensus.php

So far, the only new feature I've added in the beta client is the ability to map multiple regions in the same KML file. This lets you (for example) compare multiple regions while having the same bins apply to all of them, which you couldn't do before. There are some rough edges, like the unbounded growth of the top (status) pane, and incorrect titling in the KML file, but you're welcome to try it out.

Keep in mind that this is the dev site, so at any given time it might not work quite right. Of course, if you find bugs or have feature requests, send them to gcensus@gmail.com as always.