Strategy for Obtaining Neighborhood Data

Hi Calvin,

I drafted this but did not send it, however half of the point of writing it is to document and share methods.

I’ve been interested in this web application from the County property assessor’s office for a while:

That’s the assessor’s record for my house.

If you take a look at the floor plan down in the lower left, click the right arrow and you get an exterior shot.

I’ve always thought the photo could be used as an objective record of blight, with a ranking based on a subjective evaluation of certain characteristics.

Anyway, this will be a much faster way to obtain the data needed than by accessing KGIS.

You can also get a quick view of certain property owners.

For example it caught my eye that "ABBOTT-MARTIN PROPERTIES LLC" owns a few properties in the historic district.

I typed that into the search lookup here:

And got three properties.

"HODGE FRANK E HODGE LINDA J" returned 87 properties. The small thumbnail photos give a good overview of the condition.

The database does appear to respond to "Wildcard" search terms:

"17* Jefferson Ave" returns 23 records compared to the 200+ returned by simply "Jefferson Ave"

So it looks like it’s possible to systematically go block-by-block and harvest the property details report and lot / parcel number.

There’s a browser extension (LinkClump) that allows you go copy URLs from a selection on the screen, so I’ll probably do that for the historic district properties.

I haven’t gotten far into this, I’ve worked on the new web pages instead.

Meanwhile, here is some data I found for "Census Tract 67," I believe the source was the 2010 American Community Survey.

Census tract 67 is our neighborhood plus some of the other side of Cherry Street. So, Tract 67 data is a bit "off" as it pertains to the Parkridge Community, but it is still potentially useful.

Particularly interesting numbers from the American Community Survey data for Tract 67:

Total vacant housing units is 381.

"For Rent" accounts for 163 of the vacancies;

49 "For Sale"

151 "All Other Vacants" which I assume includes "neglected" properties.

There are more "renter occupied" housing units than homeowners (455 versus 899).

The "rental" vacancy rate is higher than the "owner" vacancy rate.

Total Housing Units 1735
Occupied Housing Units 1354
Vacant Housing Units 381
For Rent 163
Rented, Not Occupied 4
For Sale Only 49
Sold, Not Occupied 12
Seasona/Recreational 2
All Other Vacants 151
Vacancy Rate (Percent) 9.50000000000
Rental Vacancy Rent (Percent) 15.30000000000
Total Occupied Housing Units 1354
Owner Occupied 455
Renter Occupied 899

These metrics are preserved in the "tract 67" layer of a rough "atlas" I’ve been working on for the web page:


About Tanner Jessel

I am a recent M.S. in Information Science graduate from the University of Tennessee School of Information Science. I was formerly a graduate research assistant funded by DataONE (Data Observation Network for Earth). Prior, I worked for four years as a content lead and biodiversity scientist with the U.S. Geological Survey's Biodiversity Informatics Program. Building on my work experience in biodiversity and environmental informatics, my work with DataONE focused on exploring the nature of scientific collaborations necessary for scientific inquiry. I also conducted research concerning user experience and usability, and assisted in development of member nodes with an emphasis on spatial data and infrastructure. I assisted with research designed to understand sociocultural issues within collaborative research communities. Through August 1, 2014, I was based at the Center for Information and Communication Studies at the University of Tennessee School of Information Science in Knoxville, Tennessee.

Posted on October 15, 2015, in Uncategorized. Bookmark the permalink. Leave a comment.

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