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When I was working at the Connecticut Democratic Party last year we used algorithms to help us decide what voters to reach out to. I wanted to learn more about these algorithms, how they worked, and how they were made. Fortunately I discovered John Foreman’s Data Smart. Over the past few months I have set aside time to work through the examples and finally finished it last night. If you are interested in diving into the world of data science with little background, I strongly recommend this as an introduction.

In the cubicles of Silicon Valley companies like Google have departments dedicated to user experience, often abbreviated UX. Google believes that this field is so important that they developed the following video that explains what they do:

Lawrence H. Summers, the former Treasury secretary, recently said that he no longer believed that automation would always create new jobs. “This isn’t some hypothetical future possibility,” he said. “This is something that’s emerging before us right now.”

Today I watched this video by Tim Davies at the Berkman Center on open data in government and thought it was worth sharing. In the video Davies outlines three important parts of open government data: proactive sharing, machine readability, and legal ability to use and share. It seems that we often end up with open data that only hits two of these three pillars. Also while watching the video I developed another idea for an open dataset to hack on that I submitted to the CT Open Data portal, so I wanted to encourage you to vote for it.

The other day I finally took the time to explore Connecticut’s Open Data portal in depth. While I was aware of the portal before I did not extensively use it. Like many members of the public I looked at a few of the interesting example data sets and moved on. My goal was to figure out if there are some interesting data sets that I can pull down and use with some of the new algorithms that I have been learning. However no specific data set stuck out to me.