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Beginner’s Adventures in Geospatial Data – Part I – KML you are my first friend

Posted on 2015-11-092015-11-09 by Bianca

The day has come and I’m working my way through our City’s data portal. Starting point of the project has been to assess exactly what we’ve got on the City of Toronto data portal – how to summarize it and how to create a new data set of its metadata. More on that project here – feedback very welcome!

Last week, Andi and I had the huge pleasure of doing an open data workshop with the Toronto Public Library. As we were developing our presentation, we looked at open data that would be relevant to telling stories about the library system and our city. That led us to use a data file that lists our library branch data – in KML format.  Which was fantastic – I opened up my trial of CartoDB and in a few clicks had mapped the branches – Me: this is mapping? Amazing – I’m now going to go map all the things.

As any user of geospatial data may know, not sot fast – all other formats I found created an error upon connection. Reason: had to zip these files first. Why? Well, here we get into projections – and the advice I received from data journalist and open data ally though no relation to me William Wolfe-Wylie was excellent: “oh, and if it’s a new thing to you, probably good to read up on projections. Will save much head-desking later.”

I also had my first foray into batch geocoding. Which wasn’t too painful but involved getting a developer key for Bing. This was for a small project about mapping accessible meeting venues in the City.

So yeah – now reading up on projections and will post again soon on this adventure into maps. But the first thing I can say is that this feels like a great opportunity to create great getting from zero to one resources. If I had not had the luck of the library data file being KML I would have had a somewhat less “wow – I just used the data portal and made a map” experience. And taking street addresses and turning them into geospatial data is something that many non-mappers can do and get results with super quickly. The more of these “hey, I can do this with the data” experiences we can create, the more our portals will feel like real, accessible assets to us as residents.

 

 

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Posted in Civic Engagement, Data Sets, Mapping.
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