Welcome back to the round-up, an overview of the most interesting data science, statistics, and analytics articles of the past week. This week, we have 4 fascinating articles ranging in topics from collecting building data to treating Parkinson's. In this week's round-up:
- Statisticians: An Endangered Species?
- Washington DC Launches Real-time Building Energy Data Project
- Time Spent with Kirk Borne
- Michael J. Fox Foundation Points Big Data At Parkinson's
Our first piece this week is an interesting blog post on the Revolution Analytics blog about how statisticians are perceived and how that relates to data science. The post was inspired by an American Statistical Association Magazine article that portrayed statisticians as being left in the dust of the big data movement. The author goes on to talk about how he was surprised at how little mention there was of R in the article and how contributing to the statistical programming language may be a good way for statisticians to continue to play an important role in data science.
Our next piece is a GigaOM article about a project that launched last week called Build Smart DC. The project monitors energy data from city-owned buildings at 15 minute intervals to provide management with a much more granular view of energy use in the properties than ever before. This will allow them to monitor trends and make data-driven decisions that will lead to more efficient energy consumption. The article also goes on to talk about the startup that is driving this program and some other cities that have similar projects in place.
Our third piece is an interesting short interview with Kirk Borne. Kirk is a Professor of Astrophysics and Computational Science at George Mason University and has been one of the most influential Big Data advocates on Twitter in recent years. He talks to the interviewer about astrophysics, big data, and data science education.
Our final article this week is an InformationWeek piece about how the Michael J. Fox Foundation put on a Kaggle competition to see if data scientists could help identify patients that had Parkinson's and track increases and decreases in symptoms among patients that had the disease. The article highlights the winning team in the competition, some of the methods they used to generate their predictive models, and how they were about to acquire the domain knowledge that ultimately helped them win the competition.
That's it for this week. Make sure to come back next week when we’ll have some more interesting articles! If there's something we missed, feel free to let us know in the comments below.