Its Arbor Day somewhere.

I have been, slowly, working on placing 3D trees that are in the city's urban forest/Take Root project in Google SketchUp for eventual inclusion in Google Earth. This is part of the Chattanooga 3D project. While there are scripts that can be used to mass import objects to SketchUp, I have been placing them, some 1700 trees, by hand. The initial placement on the block tiles moves pretty quickly, but some of the placement points are on top of cars, in the middle of the street, or on a building - so some fine tuning is required. The KMZ file that I am using can be downloaded for your browsing pleasure. (I finally setup a Google Doc share to hold the files and datasets that I keep saying I am going to post.) Once you download the file, just open it in Google Earth. Another piece I have been working on is a file that has the species list as well. This is where it can get fun. I was recently in San Francisco and New York, both cities are releasing data to the public, and both cities have tree loving developers that built tree apps, SF Trees and TreesNY(Near You) respectively. Both functionally and aesthetically, I prefer TreesNY, but I had much more time to play with it than I did SF Trees.

Now, to real trees. I hear that VW has been planting a lot of trees around town. Hopefully all of those are being documented by plant date, geocode, and species and that they will get added to the map. If you don't get rained out, show some arboreal love this weekend. I have some small trees that I am going to try to get in the ground with the kids. If you can't plant a real tree, I would bet volunteer virtual tree planters would be welcomed to the Chattanooga 3D project!

Oh, and here are the Chattanooga Stand results for the tree category. Go and explore.

Back in CHA

Nice to be back in Chattanooga after being gone for 2 weeks! Came back in time to do Day of Service in East Chattanooga on Saturday and to get strawberries at Chattanooga Market. My trip started off in San Francisco for higher ed tech conference. Luckily there was time for food and some opengov. Open Gov West had a follow up meeting to their conference in Seattle while I was there. It was an incredible group of people from the bay area, Seattle, Canada...oh, and Tennessee. Some of the attendees were from the city and county of San Francisco and are behind DataSF, other groups represented included Code for America, and Knowledge as Power. Big ideas and wonderful conversations that I was honored to be a part of.

Next up was 5 days without wireless and almost without cell signal in and around Stillwater, NY. After that, I rode with some friends down to NYC. On the way we dropped one person off at Gate Hill Co-Op. Her house is feet from the old farm house where John Cage, David Tudor, and 7 others lived in the early to mid 50s. (Cage later built a house up the hill. ) Then on to the city. I rented a bike and rode from midtown up to the Cloisters. Almost everyday, I put the Trees Near You app to work identifying trees.

In my downtime in two of the best open data cities, I took time to work on some ChattaData too. I took the csv of the Stand data and reshaped it to use for category browsing in Tableau. I also broke it up and put it in a simple mysql database to run ad hoc queries against. I will post both sometime soon once I get back into the swing of things.

The Value of Data, Pt. 1

"The cynic knows the price of everything and the value of nothing." - Oscar Wilde

For the most part, data has a price. Whether it is a survey crew using GPS to gather geographic information or a Stand survey crew with clipboards to collect responses, data has a price. It costs money to prepare to gather it, to gather it, to process it, to analyze it, to report on it and finally to present it. The price tag is always there. I have to admit, there have been several times where I have questioned the price of a dataset. One in particular was one of the food economy reports that the Ochs Center produced. In the moment, I only looked at the price and wondered why we wouldn't just use that money to *do something*. Now, I have no doubt that things like the Benwood Foundation's Gaining Ground project/initiative might not exist had the Ochs Center not done those studies and reports. At the time, I was unable to see the value in the work.

Value is something latent in data. It is not until people use the data to *do something* that value starts to emerge. The exciting thing, for some datasets, is that we have no idea what great ideas people are going to come up with to put them to use. Governments can open data, but it takes developers, organizations, and individuals to transform a dataset into something valuable. Something informative. Something formative.

Chattanooga Stand

The Stand results are up and ready for you to explore. There is a nice intro video to demonstrate the use of the query interface as well. I think the best starting point is at the bottom of the page where you can download the Ochs Center's summary and report of Stand. It presents the Stand results alongside the Center's own SOCCR report, giving more breadth and depth to both, in my opinion. Also available are the raw results in both csv and mysql formats. If you intend to spend some time looking at the results via the web interface, it would be a good idea to at least spend a few minutes with the csv file to familiarize yourself with the structure of the data.

Above is a map showing results by zip code in the Chattanooga MSA. There are dots all over the US as well, but that image doesn't translate well....and honestly this map, in its static form doesn't either. The bar chart below does a better job. It is filtered to show only zip codes with 300 or more responses. I chose 300 as the cut off in order to make the image manageable and readable. While I didn't double check it, I am pretty sure most of the ones in the chart are in the MSA as well.

Stay tuned for more Stand data and info as the exploration continues. There are certainly a lot of great individual responses. I will use the ChattaData Twitter feed for one-off observations and post for more substantial ones. Feel free to share any thoughts and/or observations here as well. Go explore!!

2010 Chattanooga Shootings

I have been working with some people for a while on mapping the sites of the shootings happening in town. There is still a lot of work to do on the data driving the map, but with this being a big part of the conversation going on in the city, I wanted to go ahead and post the map in progress. In this static form it tells us three things. Shooting locations/approximate locations marked by dots, orange dots represent shootings resulting in injury, red resulting in death. The size of the dots corresponds to the number of incidents at that location. (This view focuses on the heart of the city and, therefore, does not include the Sanders Rd. incident.) Once the data is fine tuned and triple checked, there will be an interactive version of this map. As this is a work in progress, please let me know if you see any obvious errors on the map.

Reminder: This map represents three facts and does not represent any crime analysis or interpretation. Oh, and you should click it open to another tab to see if you haven't already.

Pointless and Bible Black

The other day I was looking at a map of Chattanooga that was color scaled to show the percentage of the population that met, or fell short of, some criteria or other. The polygons were, I believe, Census tracts. The color scale went as follows: yellow, green, dark green, blue, black. This is from lowest to highest percentage. The frustrating thing was, of course, that the details for the tracts in black were pretty much illegible. Decisions on cartographic color schemes can be tricky, luckily, there's an app for that....Color Brewer. I think the most important thing I learned from the site was making the color choice based on the function of the colors on the map, whether they represent sequential, diverging, or qualitative data. This might seem obvious, but many maps produced by professional GIS folks fall short. Color Brewer has become an indispensable tool in the Chattadata toolbox. Whether it is making ArcGIS default colors pretty or choosing a palette to use with R, Color Brewer delivers. (For some reason, I find myself using the first version of it more. You should look at both.) I used it tonight on a map, that will show up here once it is all growed up, and it made all the difference.