[VAUD] Visual Analytics of Urban Data: spatio-temporal and Beyond! (R. Borgo)

Abstract: This module will offer an insight into some of the fundamentals and novel methodologies behind Urban Analytics, that is Visual Analytics + Urban Data. We will delve into known applications as well as “quirkier” case studies to question the common notion of data itself and challenge established assumptions on what it is the meaning of smart city. We hope the module will give students opportunities to develop  their skills in Analysis and Visualization of urban related data and to expand their realms of inquiry of what can be considered as urban data.

Speaker: Rita Borgo is Senior Lecturer in Data Visualization at the Informatics Department at King’s College London (KCL), Head of the Human Centred Computing research group and Deputy Director of the Centre for Urban Science and Progress (CUSP) – London. Her research focus is on Information Visualization and Visual Analytics with particular attention to the role of Human Factors in Visualization. Her research has followed an ambitious program of developing new data visualization techniques for interactive rendering and manipulation of large multi-dimensional and multivariate datasets. Her research has been awarded supports from Royal Society, EPSRC and EU. Applications have span the areas of Explainable AI, Urban Science and Big Data Analytics. She is currently championing the newly created Urban Living hub at KCL to increase impact of visualization within urban related challenges. 

[AUTP] Analysis of Urban Traffic Patterns from velocity data (M. Cogoni)

Abstract: The problem of urban traffic, particularly with respect to the transition from a free-flowing to a congested state, has been studied extensively in recent decades. A wide range of approaches has been employed, from analytical models to simulations using coarse-grained traffic descriptions. Recently, new solutions are emerging. These are made possible by the increasing availability of large databases of sensor data with dense spatio-temporal coverage. In this lecture, after an introductory part in which the problem will be framed and a summary of the state of the art will be presented,  a large-scale traffic data analysis will be presented as an example of how to use available open traffic data for large metropolitan areas. In particular, available data include the topology of the road network made available thanks to OpenStreetMap, and detailed velocity information made available by services such as UBER and distributed sensor networks, including the ones distributed on the territory of the Metropolitan City of Cagliari.. Here we present an innovative approach, based on the theory of critical percolation on the urban graph, which allows an analysis of network fragmentation: important geographical differences between different time slots emerge without resorting to high spatio-temporal resolution data. Moreover, this method makes accessible the direct study of densely populated areas of large size (on the order of tens of square kilometers) and with urban networks described by hundreds of thousands of nodes. The results obtainable with this approach make possible real-time traffic diagnosis and detailed planning of urban topology.

Speaker: Marco Cogoni: Degree in Physics at Università di Cagliari in 1999 with a dissertation on the chaotic behavior of spin glasses (with E. Marinari and later M. Mezard.) Ph.D in Physics obtained at Università di Cagliari with a dissertation on the creation and mobility of defects in crystalline semiconductors (with Luciano Colombo and Art Voter.) Post-doc researcher at Physics Department (Università di Cagliari) (2003-2005), Materials Science at Università di Milano Bicocca (with Leo Miglio) (2005-2007), CNRS Laboratoire de Mécanique de Lille and CEA Saclay (J.P. Laval, B. Dubrulle) (2007-2008). Since 2008 at CRS4, working on different projects related to concentrated solar power, crystalline structure of ice and, recently, network congestion analysis, feature extraction from biological signals and applications of network theory to social sciences. The research activity is characterized by the use and development of advanced numerical techniques such as Montecarlo methods, multi-objective optimization and statistical mechanics tools.

[FAIR] The FAIR Principles for research objects reuse (F. Frexia and A. Sulis)

Abstract: Our increasing ability to collect, store, and process an expanding volume of data has resulted in the opportunity and need to use large-scale data sets and analytics to address fundamental challenges in many research and application areas, including urban informatics. The need for transparency, reproducibility and sharing of resources generated by the scientific research process (data, algorithms, codes, documents, articles, etc.), as well as the development of methodologies and tools in line with the Open Science approach, has led to the formalization and dissemination of guidelines such as the FAIR Principles, which promote the creation of digital research objects that are Findable, Accessible, Interoperable and Re-usable. This lecture introduces, in the first part, the fundamental concepts behind the FAIR Principles, in the second part their application in practice and their current diffusion in various research fields, showing how they can support the effective re-use of quality results.

Speaker: Francesca Frexia is the leader of the Digital Health Research Program at CRS4. Her research activity spans the opportunities and problems arising from the application of computer science to medicine, working on interoperability, traceability, telemedicine and modelling of data and processes in the clinical context. She holds a Ph.D. in Innovation Sciences and Technologies from the University of Cagliari and a degree in Biomedical Engineering from the University of Genoa. Her present research interests are mainly focused on the modelling of biomedical data and processes, with a particular attention to interoperability, with specific attention to interoperability aspects through the development and application of open formats and standards in line with the FAIR Principles.

Speaker: Alessandro Sulis: Graduated in Electronic Engineering at the University of Cagliari in 2003, Alessandro Sulis successively took a II level Master in Information Technology, at the Center of Excellence CEFRIEL in Milan. He has a decade of experience in interoperability between clinical systems according to the main standards and best practices and actively collaborates with international reference organizations (IHE and HL7 International). In particular, since 2013 he has been Monitor at the IHE European Connectathon and since 2021 he has been Co-Chair of the Technical Committee of the IHE PaLM (Pathology and Laboratory Medicine) domain, where he is also the main editor of the SET Profile (Specimen Event Tracking), for sample traceability. His current research interests include the study and promotion of FAIR principles, in the context of projects related to FAIRification of data and metadata in the clinical domain.

[InfoVis] An Introduction to Information Visualization (E. Puppo)

Abstract: The course provides an introduction to general principles and techniques for the visualization of abstract information. After an initial overview, the main design paradigm what-why-how will be introduced: the what part is concerning abstraction on the input data, providing a formalism and a vocabulary to frame specific instances on the context of a general framework: likewise, the why part is concerning abstraction on the tasks and targets of a visualization app; while the how part provides a rich collection of idioms to manage the visual output and user interaction. Next the course will focus on geographic data, providing the basic techniques for their visualization. The last lecture will be dedicated to an exercise in class to visualize geographic data by means of  the D3 Javascript library.

Speaker: Enrico Puppo è professore ordinario di Informatica presso il Dipartimento di Informatica, Bioingegneria, Robotica e Ingegneria dei Sistemi (DIBRIS) dell’Università di Genova, di cui stato direttore da novembre 2014 a ottobre 2020. Enrico Puppo è autore o co-autore di oltre 120 pubblicazioni scientifiche su algoritmi e strutture dati per la gestione di dati spaziali, modellazione geometrica, geometria computazionale ed elaborazione di immagini. I suoi interessi di ricerca riguardano principalmente la modellazione geometrica, gli algoritmi e strutture dati geometriche e l’analisi di forme tridimensionali, con applicazioni in computer graphics, visualizzazione scientifica, e sistemi informativi territoriali. Enrico Puppo e’ stato responsabile di diversi progetti di ricerca internazionali e nazionali.

[IntVis] Interactive Visualizations (L. D. Spano)

Abstract: The course provides an introduction to the main principles for using the interaction as a way for managing the complexity of the displayed data. In particular, we will discuss the filtering (selectively hiding some data points), aggregation (showing visual representations of data subsets), focus+context (showing the whole details of a data item together with the overview of the surrounding elements), pan & zoom, animated transitions. We will show examples of such techniques using the D3.js library. 

Speaker: Davide Spano is an Associate Professor at the University of Cagliari, Italy. He got his PhD at the University of Pisa, Italy, in 2013. He previously worked in the HIIS lab at ISTI-CNR. His main research interest is Human-Computer Interaction (HCI), and he wrote several papers on novel interaction techniques and visualisations, gestural interaction, virtual and augmented reality applied on cultural heritage, mobile museum guides and end user development. He collaborated on different projects funded by the European Commission (IDEAS H2020, Serenoa FP7, ServFace FP7, Artemis Smarcos). He has been a member of the Model-Based User Interface Working Group of the World Wide Web Consortium (W3C). He currently teaches courses on HCI at the University of Cagliari.