Migration, adaptation to climate change, radicalisation in groups or individuals, inequality and unemployment, freedom of movement of people and goods: these are some of the themes that shake the global public opinion – and influence our opinion as well. Orienting and acting in the complexity of these themes is extremely difficult: the huge amount of data and information produced online, the wide- spread availability of documents, articles, opinions and comments can create more confusion than clarity. Losing in the (over) abundance of this information, or – if you are active in the debate – sticking to your “filter bubble” losing sight of other positions or entities involved is a common experience.

If the web did not help to make the controver- sial issues more understandable, however, it made their complexity evident: these issues do not have clear and unambiguous solutions and generate a dense debate that interweaves alliances and oppo- sitions involving many different actors through digital conversations. At a first analysis the situa- tion stalls: complexity, by definition, is impossible to reduce without losing its wealth; At the same time, it remains incomprehensible without its simplification.

As communication designers we can not avoid contributing to understanding these phenomena and orientating possible actions. As complex and controversial problems can’t be faced by a single actor, we can represent and share the debate that defines and nourishes them so that any stakeholder can find its own position and say “I am here”.

The lab is developed in three phases, on a path that explores the many dimensions of data analysis and communication. The three phases of the lab require the appli- cation of different communication languages and tools, both digital and physical, to exploit their specific potential and to synthesize all the compe- tences acquired.

Transversally, the concepts of social complexity, the role of statistics tools and methods in the visualisation process, and the idea of visualisation as inter-semiotic translation – such as narrative and discourse – will be deepened. The “visual discourse” in its various forms of manifestation will then be considered as an argumentative strategy, in which narration and dramatisation complement the direct communication of data and information. Rhetorical-argumentative figures, in particular those based on analogy and metaphor, will be applied – consistently with the different design moments of the lab – as both knowledge tools and communicative devices, exploiting the potential for facilitating access to cognition.

Educational goals

At the end of the course, the students will have learned:

  • Knowledge in the data visualisation, information visualisation, information design disciplines, and the role of communication design;
  • Historical evolution and dynamics of convergence of the disciplines, scope of application;
  • Knowledge and use of the visual variables and application of communication design to visualisation of data and information;
  • Knowledge on tools for data manipulation (Excel, OpenRefine) and for the creation of visual structures (RAW, Gephi);
  • Knowledge on data harvesting/scraping (Web Scraper Chrome Extension) and data collection through APIs;
  • Understanding basic statistics and software for their application (R);
  • Knowledge of the rhetorical-argumentative figures (especially those based on analogy and metaphor).

Course structure

The course will be divided in three main phases in which students will be working in groups, supported by two individual assignments. In each phase, students will confront various sets of problems related with the information design field: picking sources, constructing a coherent narrative, dealing with unstructured data, designing for advocacy. The three phases have all a different output, giving students the chance to experiment on how to design visualisations for different kinds of publics.

The supporting themes, tackled from a different perspective in each phase, are: the role of the designer as an author, data handling and its implications, the rhetorical value of data visualisation. Each phase has a different output, giving the students the possibility to design visualisations for different types of public.

Results

• Phase 01

Phase 02

Phase 03