Class Information Visualisation and Representation

The course unit Information Visualisation and Representation is part of the Master's in Teaching Informatics, within the scientific area coded AD, taught in the 2nd semester. It aims to equip future Informatics teachers with the theoretical foundations and good practices of information visualisation and digital data representation. It focuses on selecting and using computational visualisation tools (RAWGraphs, Flourish, Datawrapper, Tableau, Power BI, Gephi, D3.js), designing interactive and static visualisations, critically and ethically evaluating visualisations, and applying visualisation strategies to teaching and scientific communication. Taught in the 2nd semester, it complements students' technical training in data science, equipping them with visual-communication skills relevant to teaching practice and academic publishing.

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CP1 - Fundamentals of visualisation: concepts, purposes and visual encoding. CP2 - Introduction to visualisation tools and platforms: web-based tools (RAWGraphs, Flourish, Datawrapper), desktop tools (Tableau Public, Power BI, Gephi) and open-source libraries (Chart.js, D3.js, introductory level). CP3 - Choosing visual forms: matching data types to graph types. CP4 - Data preparation and transformation (spreadsheets, CSV, JSON). CP5 - Creating static, interactive and animated visualisations. CP6 - Using visualisations in research presentations and teaching materials. CP7 - Responsible visualisation: bias, misrepresentation and accessibility. CP8 - Final challenge: building a visualisation portfolio focused on an academic or research context.

ME1 - Dialogic lectures, fostering systematic transmission of key concepts and classroom debate (LO1). ME2 - Practical labs with tools, enabling experimentation with real or simulated datasets (LO2). ME3 - Collaborative planning and constructive-critique sessions, encouraging the exchange of ideas on visualisation strategies (LO3). ME4 - Collaborative planning and critique sessions with individual mini-projects, enabling critical analysis of products (LO4). ME5 - Collaborative sessions focused on communication strategies, fostering the communicational effectiveness of proposed designs (LO5).

Cairo (2016). The Truthful Art: Data, Charts, and Maps for Communication. New Riders. Kirk (2016). Data Visualisation: A Handbook for Data Driven Design. Sage. Munzner (2014). Visualization Analysis and Design. CRC Press. Healy (2018). Data Visualization: A Practical Introduction. Princeton University Press. Meirelles (2013). Design for Information. Rockport Publishers. Börner (2015). Atlas of Knowledge. MIT Press. Evergreen (2016). Effective Data Visualization. Sage Publications. Schwabish (2021). Better Data Visualizations. Columbia University Press.