CODE 90529 ACADEMIC YEAR 2024/2025 CREDITS 6 cfu anno 2 COMPUTER SCIENCE 10852 (LM-18) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR INF/01 LANGUAGE English TEACHING LOCATION GENOVA SEMESTER 1° Semester TEACHING MATERIALS AULAWEB OVERVIEW This course provides an introduction to information visualization. Students will learn the principles to design a visualization applicaiton, and they will experience advanced programming tools to develop such applications in practice. The course consists of both theoretical lectures in class and practical experiences both in class and through autonomous work of students. AIMS AND CONTENT LEARNING OUTCOMES Learning basic principles from vision and human perception. Learning principles, methods, and techniques for effective visual analysis of data, including techniques for visualizing spatial, non-spatial, and temporal data. PREREQUISITES Basics of web development (HTML, CSS, JavaScript) Basic notions of statistics TEACHING METHODS This course uses the method of flipped classroom: students are expected to read course material before it is presented in class. Class lectures are for intrudicing theory and design principles. Practice consists in simple data visualization tasks implemented individually by students Homework will be assigned. Class attendance may affect the final assessment. SYLLABUS/CONTENT This course will make use of elementary client-side web programming; students are expected to have some backgound on HTML5, CSS, and Javascript. Visual perception Data abstraction Marks and channels Task abstraction Visualization of categorical data Visualization of temporal data Visualization of correlations Visualization of geographic data Technical tools: D3.j RECOMMENDED READING/BIBLIOGRAPHY Scott Murray. Interactive Data Visualization for the Web. O’Reilly, 2013 Jonathan Schwabish. Better Data Visualizations. Columbia University Press, 2021 Koponen, Juuso, and Jonatan Hildén. Data visualization handbook. Aalto korkeakoulusäätiö, 2019. Tamara Munzner.VisualizationAnalysis and Design.AK PetersVisualization Series. CRC Press, 2014 Amelia Wattemberger. Fullstack D3 and Data Visualization: Build beautiful data visualizations with D3 TEACHERS AND EXAM BOARD ANNALISA BARLA Ricevimento: ANNALISA BARLA: on demand, upon explicit request by email Exam Board ANNALISA BARLA (President) CLAUDIO MANCINELLI ENRICO PUPPO (President Substitute) LESSONS LESSONS START In agreement with the calendar approved by the Degree Program Board of Computer Science. Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION Attendance Quiz during class - Class attendance Homework [20%] About four assigned along the course - small effort, strict deadlines Project [50%] Assigned during the course - big work, completed by the end of the course Oral [30%] After submitting the project By appointment for groups of students Depth of oral exam proportional to attendance. The score of quizzes+homework will guide the selection of the topics during the oral exam