The Amateur Data Scientist and Her Projects by Vincent Granville.
From the post:
With so much data available for free everywhere, and so many open tools, I would expect to see the emergence of a new kind of analytic practitioner: the amateur data scientist.
Just like the amateur astronomer, the amateur data scientist will significantly contribute to the art and science, and will eventually solve mysteries. Could the Boston bomber be found thanks to thousands of amateurs analyzing publicly available data (images, videos, tweets, etc.) with open source tools? After all, amateur astronomers have been able to detect exoplanets and much more.
Also, just like the amateur astronomer only needs one expensive tool (a good telescope with data recording capabilities), the amateur data scientist only needs one expensive tool (a good laptop and possibly subscription to some cloud storage/computing services).
Amateur data scientists might earn money from winning Kaggle contests, working on problems such as identifying a Bonet, explaining the stock market flash crash, defeating Google page-ranking algorithms, helping find new complex molecules to fight cancer (analytical chemistry), predicting solar flares and their intensity. Interested in becoming an amateur data scientist? Here’s a first project for you, to get started:
Amateur data scientist, I rather like the sound of that.
And would be an intersection of interests and talents, just like professional data scientists.
Vincent’s example of posing entry level problems is a model I need to follow for topic maps.
Amateur topic map authors?