It’s time again to revisit my periodic look at GIS StackExchange (GISSE) and what it may or may not tell us about the state of things geospatial. By now, the process is fairly routine. I have single Python script that gets tag data and parses it to CSV. I then hand-edit categories into the data for grouping purpose. While it’s perfectly valid to quibble with individual category assignments, I’m fairly consistent with it at this point, using previous data sets as a guide. Compared to last year, the all-time look hasn’t changed much. Open-source and “general topics” have switched places, but there were no great shifts that I could see. The roughly 4% increase in open-source topics could be a result of QGIS support moving to GISSE.
I read with great interest today’s announcement that AppGeo is no longer an Esri Business Partner. I find the announcement significant for a number of reasons, which I will explore shortly. I have always respected AppGeo’s work. As a small business that does geospatial consulting, they have foregone the “grow at all costs” approach that is seen all too often in the consulting world. They generally stuck to what they do well and branched out conservatively in ways that tie logically back to their core business.
This post describes the construction of a simple, lightweight geospatial data service using Node.JS, PostGIS and Amazon RDS. It is somewhat lengthy and includes a number of code snippets. The post is primarily targeted at users who may be interested in alternative strategies for publishing geospatial data but may not be familiar with the tools discussed here. This effort is ongoing and follow-up posts can be expected.
When I was in college, I had a psychology professor who posited that you could train a cat (a dodgy proposition at best) to take a circuitous route to its food bowl by only rewarding that behavior. He was clearly a behaviorist and was convinced that you could completely condition the instinct to go straight to the food bowl out of the cat. To my knowledge, this professor did not own a cat and never attempted to test his assertion.
I was reminded of this after reading my friend Atanas Entchev’s post in reaction to the PostGISDay hangout panel discussion. In his post, Atanas describes difficulty in convincing customers to consider open-source geospatial tools. These customers and prospects are comfortable with their proprietary tools and associated workflows and are reluctant to consider switching. I have encountered this attitude many times myself so I take no issue with the observation. Barriers to exit are real considerations, regardless of the new technology being considered. Organizations align themselves around their tools to achieve maximum efficiency with them. I discussed these issues at a talk I gave last year to the New Jersey Geospatial Forum about how organizations can extend their existing geospatial technology investments with open-source technologies. These issues are very real for any organization with a mature, extended investment in a particular technology stack.
This past week, I got an e-mail from Jim Cannistra, Director of Data Planning Services and the Maryland Department of Planning (MDP), alerting me to a new product available from MDP called FINDER Quantum. This product bundles Maryland property data and related products with QGIS software to provide users with a fully-functional, free-standing system for interacting with the data. It is designed to replace an older, custom software product, capitalizing on an industry-standard open-source system.
From the MDP site, the bundled data includes:
With the release of ArcGIS 10.2, Esri quietly added support for SQLite as a geodatabase container. This is big news as the community has been looking for such support for some time. An open-source RDBMS originally designed for embedded systems, SQLite has a very small footprint and is arguably the most widely deployed RDBMS in the world. (Thanks, in part, to the fact that it is embedded into Adobe Reader and other commonly used software.) Over the years numerous strategies for storing spatial data in SQLite have been developed, ranging from simply storing WKT or WKB geometries in a column up to full extensions like SpatiaLite, which adds OGC-compliant data types and methods. SQLite is also the engine that drives the popular MBTiles implementation used by TileMill and MapBox.
Thanks to LinkedIn, I saw that Dr. Art Lembo of Salisbury (Maryland) University is leading an “Open Source/Enterprise GIS Summer Bootcamp” at the university from June 3 – 7, 2013. All of the salient details, including contact information, can be found here (PDF).