Geocoding

The OpenBlock geocoder is powerful and robust. It uses PostGIS for spacial queries, can extract addresses from bodies of text, and can understand block and intersection notation. We've run into a few issues with it, however, including a low geocoding success rate. This is a tough problem to solve and depends on a lot of factors (the extent of street and block data in OpenBlock, format of the street addresses, etc.), so your mileage may vary. Below I constructed a simple test using Google's Geocoding API to have as an alternative.

This is the second post in our OpenRural series reviewing OpenBlock and it's geocoder. OpenBlock Geocoder, Part 1: Data Model and Geocoding covers the internals of the OpenBlock geocoder and it's geocoding capabilities. As this posts builds upon topics covered there, you may wish to read Part 1 before proceeding. In this post we step back from the internals of the geocoder and explore how to use it along with other OpenBlock tools to parse unstructured text.

As Tobias mentioned in Scraping Data and Web Standards, Caktus is collaborating with the UNC School of Journalism to help develop Open Rural (the code is on GitHub). Open Rural hopes to help rural newspapers in North Carolina leverage OpenBlock. This blog post is the first of several covering the internals of OpenBlock and, specifically, the geocoder.