Location: Hotel Giardino sul Mare, Via Maddalena -LIPARI-
Free registration by email: email@example.com
The recent technological advances on telecommunications create a new reality on mobility sensing. Nowadays, we live in an era where ubiquitous digital devices are able to broadcast rich information about human mobility in real-time and at a high rate. Such fact exponentially increased the availability of large-scale mobility data which has been popularized in the media as the new currency, fueling the future vision of our smart cities that will transform our lives. The reality is that we just began to recognize significant research challenges across a spectrum of topics. Consequently, there is an increasing interest among different research communities (ranging from civil engineering to computer science) and industrial stakeholders on build knowledge discovery pipelines over such data sources. However, such availability also raise privacy issues that must be considered by both industrial and academic stakeholders on using these resources. The Workshop has the aim in presenting some emergent studies in mobility data analysis and complex systems in order to raise the interests in the field.
Roberto Trasarti: Opening
Fosca Giannotti: SoBigData Project
Mark Cotè: A Techno-Cultural Approach to the City of Citizens
Our cities are increasingly built on data producing, collecting, and monitoring technologies. But to make our cities ‘smarter’ requires that more of our everyday lives be datafied in increasingly intimate and ubiquitous ways. This talk will outline a ‘techno-cultural’ approach to studying this phenomenon. By foregrounding the constitutive relationship between the human and technology, we will consider the social and cultural dimensions of the data-citizens of the city.
Angelo Facchini: The road to sustainability for megacities
Aim of this talk is to show the urban metabolism method (i.e. the assessment of energy and material flows) as a mean for assessing and comparing urban sustainability. As case study we show the results of a research involving 30 of the world's megacities, discussing the links of UM with UN Sustainable Development Goals (SDG) and presenting a set of Key Performance Indicators to measure urban sustainability. Finally policy implications and the role of utilities in driving the sustainability transition of megacities is discussed.
Mirco Nanni: Integrated mobility data management and mining for smart city services
In this talk we will discuss a mobility data analysis platform employed to transform several city-related data sources into mobility services for the citizens and the public administration. Some representative services will be shown, that exploit the rich mobility knowledge yielded by sophisticated data analysis technologies.
Giuseppe Manco: Survival Factorization for Topical Cascades on Diffusion Networks
The availability of large-scale, time-resolved cascade data on the social Web allows us to study their structure and properties. Recent models assume that the speed of the diffusion can depend on elicitation processes which involve users, based on their mutual connection strength. A different line of research explains information propagation in terms authoritativeness and susceptibility. In this talk, we investigate how the two lines of research can be combined and the speed of the diffusion process can be explained in terms of authoritativeness and susceptibility.
Fellow of Jesus College and Faculty Fellow of the Alan Turing Institute for Data Science in London she is an expert in mobile and sensor systems, mobility modelling, mobile applications, mobile data analysis.
Fosca Giannotti is a senior researcher at the Information Science and Technology Institute of the National Research Council at Pisa, Italy, where she leads the Knowledge Discovery and Data Mining Laboratory – KDD LAB. Her current research interests include data mining query languages, knowledge discovery support environment, web-mining, spatio-temporal reasoning, spatio-temporal data mining, and privacy preserving data mining. She has been involved in several research projects both at national and international level, holding both management and research positions. Coordinator of the SoBigData project.
Dino Pedreschi is a Professor of Computer Science at the University of Pisa, and a pioneering scientist in mobility data mining, social network mining and privacy-preserving data mining. He co-leads with Fosca Giannotti the Pisa KDD Lab - Knowledge Discovery and DataMining Laboratory. His research focus is on big data analytics and mining and their impact on society. He is a founder of the Business Informatics MSc program at Univ. Pisa, a course targeted at the education of interdisciplinary data scientists.
Dirk Helbing is Professor of Computational Social Science at the Department of Humanities, Social and Political Sciences and affiliate of the Computer Science Department at ETH Zurich. His interests are: (1) bringing modeling and computer simulation of social processes and phenomena together with related empirical, experimental, and data-driven work, (2) combining perspectives of different scientific disciplines (e.g. socio-physics, social, computer and complexity science), (3) bridging between fundamental and applied work. The research focus has quickly moved from studying pedestrian crowds and vehicle traffic to studying social coordination, cooperation, norms, crime and conflict as well as collective opinion formation and the wisdom of crowds.
Mark is a Lecturer in Digital Culture and Society, leading development there in the analysis of big social data via an AHRC-funded research project. He is a member of both the Department of Digital Humanities and the Department of Culture, Media and Creative Industries. His research interests are: Big Data, Social Media, Media theory, Research and technology. Moreover he entails the materiality of the digital, namely in critically unpacking the mediating environment of cultural practices and political economic relations. He is also interested in the ontology of the digital human, especially as it relates to big data.
Roberto Trasarti: Wrap-up and Closing