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I wrote the blog posted called Why open source needs Captain Kirk to comment on the strength of open source leadership. Interestingly, my idea to relate open source to Star Trek to make a point was not unique. It was pre-dated by Captain Kirk Was Right!
It's a different take on Star Trek and open source however I like the ideas behind it. In particular, if you can get a commodity for free or close to it, isn't that a good thing? I see few people complaining about cheap gas, water, power, bread, milk, eggs, clothing, etc.
Related to this... read on.
I enjoyed the FLOSS Weekly episode on OpenStreetMap - FLOSS Weekly 81: OpenStreetMap.org. Steve Coast, founder of OpenStreetMap is interviewed and does a fantastic job explaining why OpenSteetMap exists and why it is very much needed. I highly recommend listening if you have time.If you enjoy it, we have a related video called Introduction to OpenStreetMap.
For those that don't have time to listen, the key message I'd like to share is that map data is owned by a few companies such as Nokia (ne: Navteq) and TeleAtlas. The tremendous cost of producing the maps necessitates that these firms have very restrictive licenses to protect their business models selling the data. As a result, there are many things you can't do with the data.
I'd like to emphasize something as this is a good case of a theoretical concept I'd covered in Linux will never rule the desktop. The reason why OpenStreetMap will win in the end and likely obviate the need for commercial map data is that the costs and risks associated with mapping are shared. Conversely, for Navteq and TeleAtlas, the costs born by these companies are passed on to their customers. Once their customers discover OpenStreetMap data is in some cases superior, or more importantly - they can contribute to it and the license allows them to use the data for nearly any purpose - map data then becomes commodity.
Getting back to Captain Kirk - once map data is commodity, money will be spent on innovative applications rather than acquiring data. This was something I touched on in Geospatial Primer: in Search of the Next "Killer App". It also relates to my work at Ingres.