Data Science has become a hot topic lately. As usual, there’s not a lot of agreement about what data science actually is. I was on a panel last week, and someone asked afterwards what the difference was between data mining, which we’ve been doing for 15 years, and data science.
It’s a good question. Data science is a new way of framing the scientific enterprise in which a priori hypothesis creation is replaced by inductive modelling; and this is exactly what data mining/knowledge discovery is about (as I’ve been telling my students for a decade).
What’s changed, perhaps, is that scientists in many different areas have realised the existence and potential of this approach, and are commandeering it for their own.
I’ve included the slides from a recent talk I gave on this subject (at the University of Technology Sydney).
And once again let me emphasise that the social sciences and humanities did not really have access to the Enlightenment model of doing science (because they couldn’t do controlled experiments), but they certainly do to the new model. So expect a huge development in data social science and data humanities as soon as research students with the required computational skills move into academia in quantity.
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