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The Birth of Urban Data Science

There has been an explosion of interests in data science over the past several years. Indeed, data scientist has suddenly become the sexiest job. So, what is data science and what does data scientist do? And what does it mean to do "Urban" data science? In general, data science is a marriage between computer science and statistics. It's basically a statistician becoming a programmer; or a programmer becoming a statistician. The two fields were very close in the past, but the time has come that they needed to marry, and the honeymoon has begun. So one might ask.. why did the two fields converge in the first place? Well.. I would say it has something to do with big data phenomenon. Traditionally, statisticians used to work with large data sets, and computer scientists employed some statistical methods to solve their problems. With big data, statisticians need someone to process and manage the data as they cannot possibly handle the data that big efficiently. Computer scientists, too, need someone to make good use of the data that they are producing and managing. Otherwise, the data are just being produced and sitting there for no reason.


Let's take a look at a more formal definition of data science (diagram above) and how media portrays data science. Data science has three components: computer science and statistics. And there is one more thing, subject matter expertise! What this means is that you need not be a jack-of-all-trades, but you'd better be someone who knows the context and can find some meanings or values out of data. There is an unprecedented expansion of data in both volume and variety. And most importantly, data is coming from every where -- it comes not only from a digital world, but also from a physical world, thanks to ubiquitous sensing technology and Internet of Things (IoT). I will spare some time to talk about IoT in the future. So hang in there... So, what's happening now? Data are becoming ubiquitous and cheap, and those who can make good use of data are the ones who will flourish. Hal Varian, the chief economist at Google, once said that data is getting ubiquitous and cheap, so the values lie in finding the meaning.


So, there you have it. Urban data scientist is basically a statistical programmer who has a subject matter expertise in urban studies. In other words, in the age of big data, programming skills and statistical knowledge serve as an important tool to find meanings about urban "stuff". This urban "stuff" can mean anything from urban theory and philosophy to practical applications to resolve various conflicts occurring in urban context. Let me finish this posting with my own (and hopefully reasonable) definition of urban data science. Urban Data Science is an interdisciplinary study of applying computer science and statistical tools to understand urban issues and to inform urban decision making. And the corollary to this definition is that urban data science as a field emerged from the need to make use of new technologies, such as big data, IoT, and Artificial Intelligence, to solve various urban problems. So, the field of urban data science is continuously growing as we speak, and its definition is likely to change with technological advances.

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