Dialogues in Human Geography· 2013Q1
Big data, smart cities and city planning
- 1,068citations
- Q1SCImago
- 2013year
Short summary
Urban big data, primarily from sensors and tagged to space/time, is shifting city planning from long-term strategy to short-term management and operational focus.
AI-generated from the title and abstract; the full text is not read.
Key points
- Urban big data is characterized by its spatial and temporal tagging, often streamed from sensors.
- The growth of big data is prioritizing short-term city management over long-term strategic planning.
- Smart travel card data from London's public transport is presented as an example for analysis.
- New theoretical frameworks are needed to analyze this evolving data landscape.
AI-generated from the title and abstract; the full text is not read.
Abstract
I define big data with respect to its size but pay particular attention to the fact that the data I am referring to is urban data, that is, data for cities that are invariably tagged to space and time. I argue that this sort of data are largely being streamed from sensors, and this represents a sea change in the kinds of data that we have about what happens where and when in cities. I describe how the growth of big data is shifting the emphasis from longer term strategic planning to short-term thinking about how cities function and can be managed, although with the possibility that over much longer periods of time, this kind of big data will become a source for information about every time horizon. By way of conclusion, I illustrate the need for new theory and analysis with respect to 6 months of smart travel card data of individual trips on Greater London's public transport systems.
The authors' abstract, as published at the source. Dialogues in Human Geography, 2013 · DOI ↗
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Field: Transportation
TransportationSocial Sciences