Book Review: Urban Informatics

There is a fantastic book on Urban Informatics titled, well, Urban Informatics. Its publishing was supported by the Hong Kong Polytechnic University. Its list of authors and editors is very impressive—all of whom I will absolutely keep track of as my career grows into this exciting field.

The list includes, but isn't limited to: Wenzhong Shi, Michael F. Goodchild, Michael Batty, Mei-Po Kwan, and Anshu Zhang. The book is licensed under the terms of the Creative Commons Attribution, which means it's entirely free to access, making it the perfect resource to introduce myself to the world of Urban Informatics.

The copy I have been reviewing is a staggering 940 pages long, excluding the prefaces and acknowledgements. I imagine this is going to be a long and incredibly rewarding read based on the authors and the direction the textbook is taking so far. In just the first three chapters, I have learned tons about the overall state and history of Urban Informatics. In this blog, I'm simply going to review everything covered—at least everything that stood out to me—in these introductory chapters.

Overview

First of all, defining Urban Informatics is given a ton of attention in the first chapter.

"Urban informatics is an interdisciplinary approach to understanding, managing, and designing the city using systematic theories and methods based on new information technologies, and grounded in contemporary developments of computers and communications."

This definition is long, reflecting the various aspects that go into the field. The growth of information technology is what has led this to become a field requiring specialists, but the groundwork is undoubtedly in the understanding of cities; technology is simply a lens through which insights can be found. While defining Urban Informatics in section 1.1, the authors mention how time is one of the new additions being considered much more with the increasing computing power available. Prior to continuous streams of data, there was a heavy emphasis on spatial analysis rather than considering what role time plays in the way a city can be interpreted. I can imagine as technology (construction, sensors, and compute) continues its rapid growth, there will be even more change happening over shorter intervals. The ability to incorporate time as a variable will be vital to any urban model being developed.

Data

The rapid development of this field has led to universities implementing Urban Informatics and related categories into their selection of majors for undergrad and post-grad students. I especially love the addition of this sentence, as it's incredibly inspiring what the Hong Kong Polytechnic University did to attain this goal:

"There is an urgent need to edit and publish such books to equip the current and next-generation workforce with the knowledge to tackle the challenges that cities are facing. Our contribution here is to address this urgent need."

Big data plays a significant role in Urban Informatics as a field, as do many fields within Computer Science. Data analysis that is able to manage the massive increase in information available from an entire urban area is a goal that's still in progress. As urban scientists find new ways to utilize and handle data, newer methods to collect data emerge that could be usable. This cycle is in its early stages, as Urban Informatics and Big data are both young sciences. The key takeaway regarding the 'Big Data' available is thus:

"...we need new and different techniques to explore [big data], that is, to find the pattern in such data."

Patterns define Urban Informatics, and the next chapter goes into detail on how difficult it is to find realistic patterns in data coming from thousands to millions of individual agents.

Morphology

The first part of the book largely covers the morphology aspect of Urban Informatics—morphology being the size, scale, and shape of a city, as well as how those factors can be manipulated to make the city 'better'.

The notion that a city can be regarded as a system is older than the field of Urban Informatics; for the most part, this was how people viewed urban science until quite recently. The models reflecting this viewpoint use very static, formula-driven ideas to establish patterns of how cities may change in size or function. However, as the author puts it in section 3.3:

"...these kinds of application do not embrace the fundamentals of urban dynamics, and other models which are essentially temporal have been adopted. Many of these models articulate the city not as a mechanism but as an organism, evolving like a biological system rather than being manufactured like a machine."

This shift in how the inner workings of cities are viewed by scientists is significant, and it is really enabled by the vast computational power now available. Now that we're able to model at the individual citizen level, or at least approach that point, it's much easier to see and utilize patterns that form at this cellular level (hence the reference to an organism).

This section also briefly gets into the psychology involved in this field. Citizens act rationally (at least the vast majority of them), and with that information, many models make assumptions. However, strange, irrational patterns still emerge among groups of individually rational agents. I find this fascinating, and the example mentioned was eye-opening. I look forward to Chapter 5 as it gets into 'Urban Human Dynamics'.

Conclusion

This has been a vast simplification of all that I gathered from these first three chapters, however, I think it's a solid overview and, if nothing else, a good ad for this fantastic open-access textbook. I don't have many applicable takeaways from this text yet, I think I'm still a bit far off from usable theories or models but I do think I have strengthened my understanding of the field I plan on making a career out of and I can't ask for much more than that.