Based on a recent report from the United Nations, more than 50% of the world's population currently lives in cities. This percentage is projected to increase to 70% by the year 2050. As massive amounts of people move to urban areas there is a need for cities to be run more eciently, while at the same time improving the quality of life of their dwellers. Nevertheless, the exact same force that sets the above requirement, i.e., the proliferation of urbanization levels, makes this task much harder and challenging, especially in megacities. Despite the aforementioned con icting dynamics, many city management operations can be facilitated by appropriate exploitation of the unprecedented amount of data that can be made available to authorities from a variety of sources. In the era of big data and ubiquitous and pervasive mobile computing, different types of sensors such as parking meters, weather sensors, trac sensors, pipe sensors, public transportation ticket readers and even human sensors (e.g., through web technologies, social media or cell phone usage data) can assist in these efforts. Furthermore, civic applications can exploit web and mobile technologies to deliver a livable, sustainable and resilient environment to the citizens. Harnessing these information streams and technologies presents many challenges that are in the epicenter of this tutorial. In this tutorial we will present the current practices and methods in the emerging field of urban informatics as well as the open challenges. The topics to be covered in this tutorial are structured in three sessions: (i) introduction to urban studies and urban informatics, (ii) civic data and technologies for urban sensing and (iii) analytical techniques used for urban data analysis. Finally, we will also provide concrete examples of urban informatics applications.
In the first part of the tutorial Daniele, covers urban and social theories developed in the past 50 years including the gravity model, phsycological maps and the notion of aesthetic capital. He furhter presents an application of each theory and ways that we can utilize Web technologies to validate these theories and further exploit them for applications such as navigation algorithms target happy pedestrian routes.
Presentation slides: (pdf)
In the second part of the tutorial, Kostas covers basic techniques useful for analyzing the highly heterogenous urban data that originate from a variety of data sources. The focus is on matrix and tensor factorization techniques that can provide infromation for latent urban activity patterns. He further discusses the new and rich source of open data that becomes prevalent in many cities around the world.
Presentation slides: (pdf)