Today’s mapping experience is brought to you by the short ‘course’, Mapping with Google. And it’s only day one but it’s already pretty clear that this ‘certificate course’ is more of a product overview of Google’s mapping products rather than a course on mapping concepts.
It’s also oddly timed. The first lessons in Unit 1 are built around the ‘new google maps’ which are still being rolled out on an request access basis. So I put in my request for the new maps (which while being problematic they are also pretty much inevitable) and continued the lesson using Google Maps on my Android.
While I don’t think I’m going to learn much about Google Maps, I am looking forward to the introductions to Google Earth and Google Map Engine Lite.
I was going to go into some detail about my experiences with the course, but I’ve opted for some vague generalizations instead.
First off, I’m still having difficulty finding a good use case for Google Earth. I guess if I wanted to go hiking in the mountains, I might want to use it to share trails but this use-case scenario from the course isn’t very captivating for someone like myself who lives in the flatlands.
Google Map Engine Lite is a much more compelling platform for data journalism than plain old Google Maps as it allows the user to select for a variety of features and the creator has a larger set of stylings to work with. And, like Google Fusion Tables, it allows for datasets to be imported in csv format. I know it can take in latitude and longitude – and I’m curious what other data formats it can accept – and it geocodes them into Google’s map projection.
I had a twitter conversation earlier this week with someone who was looking for such a resource : something simple that needed no scripting but allowed regular uploads of lat and long data. I suggested Google Fusion tables and my friend reported back that it worked well up to a point: he couldn’t export the geocoded data in any other form but KML: an open standard for ‘geobrowsers‘ like Google Earth. Hmm.