Advanced Module
Public Session
20/5/2019 | 21/5/2019 | 22/5/2019 |
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08.30 - 09.30 Registration | ||
09.30 - 10.00 | 09.00 - 10.00 Registration | 09.00 - 10.00 Registration |
10.00 - 10.45 10.45 - 11.00 Coffee Break | 10.00 - 10.45 10.45 - 11.00 Coffee Break | 10.00 - 10.45 10.45 - 11.00 Coffee Break |
11.00 - 12.00 | 11.00 - 12.00 | 11.00 - 12.00 |
Restricted Session
20/5/2019 | 21/5/2019 | 22/5/2019 |
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12.00 - 13.30 Working Lunch | 12.00 - 13.30 Working Lunch | |
13.30 - 16.00 | 13.30 - 16.00 |
Monday, 20 May 2019
Welcome and Opening
Enrico Gobbetti and Francesco Mola
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Modelling and Predicting Human Behaviour and Social Dynamics for Urban Data Science
Mirco Musolesi
Abstract: In these lectures I will introduce some key topics related to the analysis and prediction of human behaviour and social dynamics for urban data science. In particular, I will present two different types of approaches: first of all, I will discuss how it is possible to use the digital traces (mobile data, social media, etc.) that we leave in our online and offline daily lives in order to model human behaviour at a scale and granularity that were not possible just a few decades ago. In the second part of the lecture, I will give an overview of the emerging computational paradigms based on Machine Learning (in particular Reinforcement Learning) for modelling individual responses and understanding key emerging aspects of social behaviour such as cooperation and coordination. I will discuss some case studies with a focus on urban data science. I will give an overview of the open challenges in this fascinating area.

Tuesday, 21 May 2019
Using spatial big data to investigate urban dynamics and mobility patterns in cities
Patrizia Sulis and Kira Kempinska
Abstract: Measuring dynamics and phenomena occurring in urban space is a fundamental step in the process of understanding cities. The recent availability of large amounts of urban data (also known as ‘big data’), often containing human mobility information at a higher spatiotemporal resolution, represents an unprecedented opportunity for urban researchers of exploring and unveiling new characteristics of urban space, quantitatively validating established theories, and ultimately strengthening the overall understanding of spatial dynamics happening in cities. Numerous studies have explored and employed these data, applying multiple analysis techniques adopted from quantitative methods and data science to different urban contexts and obtaining a variety of outcomes. This talk presents an overview of current research related to urban analysis and urban computing: it introduces and discusses the definition of big data, presents the most common types of data employed in the literature, and illustrates the applications of these data sets and techniques to a number of different case studies across cities. It also discusses the limitations present in current research, particularly in terms of data representativeness and determinism, and the advantages and opportunities that exploiting these data represent for enhancing the understanding of cities and improving future urban developments.

Wednesday, 22 May 2019
Smart cities and GDPR compliance: mission (im)possible?
Giovanni Battista Gallus
Abstract: Smart cities rely on many different data sources. Several of these data can however be considered as personal data, because they are related to an identified or identifiable natural person. It is therefore fundamental, in the development of any smart cities service or device, to apply the principles of EU Regulation 2016/679 (General Data Protection Regulation - GDPR) from the very start. Data protection issues cannot be an afterthought, but they have to be integrated by design, as art. 25 of the GDPR clearly states. The talk will therefore summarize the key points of the EU General Data Protection Regulation, with regard to smart cities.

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Scalable urban computing systems
Enrico Gobbetti and Gianluigi Zanetti
Abstract: Urban computing systems must acquire, integrate, analyze, and present big and heterogeneous data generated by a diversity of sources in urban spaces. In this talk, we will describe the design of such a system using open standards. Examples of practical realizations in the context of the TDM project will be discussed.

