Last week, we sent out a newsletter to registrants of the Open Data Bootcamp. I included some great resources sent to us by ESRI that support the city’s new open data portal. I encouraged registrants to review the resources and start thinking about projects for the bootcamp. Since the bootcamp really only offers about 2.5 hours of “hacking” time, a part of me worried about how much could actually get done in this time. So, I decided to take a bit of my own advice and dig into the resources and try to come up with something.
In less than two hours, I iterated on other’s work to come up with this slick webtool that helps you find bike racks in Charlottesville. By no means is this a fully baked project, but it was inspiring to see how easy the new portal made my development (especially in conjunction with those great minds who originally built and shared this code on Github). Most importantly, it was an exciting and hands-on way to get more familiar with the city’s new portal.
I share this as a means of inspiring other civic innovators. The new open data portal offers some great geocoded data that is machine-readable and accessible via API. I’ll share some ruminations about this work below, including resources, and I hope it inspires you.
- Smarter people than I have created resources that are relatively simple to build off. Here are a few…Using the portal’s API – http://opendata.dc.gov/pages/using-apis
Connecting web services to the portal – http://opendata.dc.gov/pages/connect-web-services
Data tutorials (Excel, Python, R) – http://data.syrgov.net/pages/tutorial
Open Data DC Github Starter Kit – https://github.com/DCgov/opendatadc-starterkit
- With the preprocessed geocoding and open source resources this took very little time to customize
- My knowledge is only slightly above novice, if I can do it, you can do it. For inspiration from other non-coding/data professionals see our story on the Rivanna Trails App
- City staff were very helpful – Barton Pfautz, GIS specialist in NDS, helped me clean-up one piece of nonsense data to help get this working.
The growth areas
- This dataset managed by the city really needs some TLC, it definitely wasn’t the best example in terms of data quality. I would love to see the city partner with a bicycle non-profit organization or data group to improve the set, it could be very useful.
- We have a long way to go locally in terms of creating tutorials and resources for the portal. That said, there is no need to reinvent the wheel, good stuff exists, it may just be about curating these resources!
- Technical note: This tool was built using Mapbox‘s location data platform technology. For some reason, this software does not ignore “null” values from GeoJSON feeds. While the feeds probably shouldn’t contain null values, it seems like it should be able to parse around them (the city removed the null value/nonsense data and we got it working).
- Given this was spun up in less than 2 hours, there remain areas where we could improve the UI.
- Some of the code in the original project was left without getting fully cleaned up (i.e. there is a search helper that I started adjusting absent-mindedly before I realized it wasn’t necessary for our deployment).