Questioning what bigness means in terms of Big Data and the City is a key quest in understanding what the massive increase in data volumes means to understanding the urban challenges that lie ahead and our future planning of the city to alleviate the many problems that currently beset them. Kitchin, Lauriault, and McArdle’s book Data and the City is “…the first edited collection to provide an interdisciplinary analysis of how this new era of urban big data is reshaping how we come to know and govern cities, and the implications of such a transformation. This book looks at the creation of real-time cities and data-driven urbanism and considers the relationships at play. By taking a philosophical, political, practical and technical approach to urban data, the authors analyse the ways in which data is produced and framed within socio-technical systems. They then examine the constellation of existing and emerging urban data technologies. The volume concludes by considering the social and political ramifications of data-driven urbanism, questioning whom it serves and for what ends” (from the Routledge web site).
I have a paper in the book about big data: Batty, M. (2017) Data About Cities: Redefining Big, Recasting Small, in Kitchin, R., Lauriault, T. P., and MaArdle, G. (Editors) Data and the City, Routledge, London, 31-43, that you can download here in its original form.
In November 1986 I visited SunYatSen University and gave a public lecture about Urban Modelling. China was a very different world then, no cars, no computers, no email, barely functioning electricity. And of course it was before laptops, networks, hand-held devices and so on. The personal computer had only just been invented. The campus was more or less in the countryside. Despite China opening up in 1979, this was still the old China.
Fast forward 31 years to 2017. The University is now a power house, in the top 10 in China and advancing in the QS university rankings worldwide very rapidly. Since 1986, I have been there a number of times but I never gave any more public lectures until last Tuesday and Wednesday when I more or less repeated what I had talked about 31 years ago. Well not quite, of course; it was the same domain of interest and in the same lineage – but I talked about web-based, large-scale urban models, ideas about big data, smart cities and so on. A world away from those distant years but closely linked intellectually.
There are no faculty left still working in the School of Geography and Planning from those years but this is not unusual because there is no one left in any of the universities I have worked in before 1990. And it is a little sad that of those who were students then and now senior faculty there, none could remember attending my lecture and I am sure they did not know of it but there were about 130 in the room at the time. I found the building I had lectured in largely because of the poster above which was hand painted for my 1986 visit. Those of you who are Chinese will be able to read this.
Here are the pdfs of the presentations I gave:
Click on these and enjoy.
This great book edited by Jeffrey Johnson, Paul Ormerod, Bridget Rosewell, Andrzej Nowak, and Yi-Cheng Zhang brings together many contributions from an EU project which lead to several workshops and conferences about a new form of social science – out of equilibrium, far from equilibrium, in disequilibrium as the world always is. The book is open access and you can download it here.
Here is an explanation of what is contained within. Between 2011 and 2014 the European Non-Equilibrium Social Science Project (NESS) investigated the place of equilibrium in the social sciences and policy. Orthodox economics is based on an equilibrium view of how the economy functions and does not offer a complete description of how the world operates. However, mainstream economics is not an empty box. Its fundamental insight, that people respond to incentives, may be the only universal law of behaviour in the social sciences. Only economics has used equilibrium as a primary driver of system behaviour, but economics has become much more empirical at the microlevel over the past two decades. This is due to two factors: advances in statistical theory enabling better estimates of policy consequences at the microlevel, and the rise of behavioural economics which looks at how people, firms and governments really do behave in practice. In this context, this chapter briefly reviews the contributions of this book across the social sciences and ends with a discussion of the research themes that act as a roadmap for further research. These include: realistic models of agent behaviour; multilevel systems; policy informatics; narratives and decision making under uncertainty; and validation of agent-based complex systems models.
Here is my own chapter for your interest which is entitled Cities in Disequilibrium