Academic Year 2019-2020



Federico Pepe
Unit Credits
Teaching Period
Second Period
Course Type
Prerequisites. Although this course will cover the concepts of programming from the beginning; a basic knowledge/experience with coding is advisable. A previous experience with Java or, in general, with other object-oriented programming language is an advantage.
Teaching Methods. The course will be divided in theoretical and practical lessons. Learners’ projects as well as renowned projects/case studies will be analyzed and discussed in class.
Verification of Learning. The exam will be an oral discussion of a chosen project developed by the learner. It will very important to demonstrate a thorough understanding of all the notions given during the course and the ability to apply those notions/skills in a creative and meaningful way.
More Information. Different resources will be used throughout the course such as slides (powerpoint/keynote). Processing examples will be provided with source code.
The aim of the course is to enable the learners to research, analyze and represent complex data systems through visual techniques and languages. Processing, a programming language developed for enabling artists and designer to build prototypes in a quick, easy and creative way, will be taught and used throughout the course.

The course is divided in two main parts: the first one, which will be more theoretical, will enable the learners to understand how to find, analyze and represent data set. In the second one, which will be more practical, the students will apply the concepts learned and develop a visual representation of a chosen data set with Processing. The course will also have a focus on ethical discussions about how data is gathered and to truthfully represent them.

Course Outcomes:

– Knowledge and understanding:

– know/be able to use the basic functions and structures of Processing.

– understand/be able to use the basic concepts of object oriented programming

– be able to research, acquire, and analyze datasets.

– know the best practices on how to represent data

– be able to create an infographic (static or interactive).

– Applying knowledge and understanding

– be able to create a visual representation of a dataset with Processing.

– be able to identify the best practices/tools to visualize a chosen dataset

Soft skills:

– Making judgements

– Be able to chose independently the right tools and techniques to realize a chosen project.

– Communication

– Be able to explain technical issues about the chosen project.

– Be able to represent visually a complex dataset.

– Lifelong learning skills

– Learn a programming language and how to code.

– Carry out an in-depth investigation independently

This course aims to provide knowledge and advanced skills in the representation of complex systems of data with one of the most popular programming language used worldwide for this task. Learners will gain a working methodology that can be used in different contexts regardless of the tools available.

Course program:

1. Introduction to the course and to Processing: basic programming concepts and main functions to work with data.

2. The seven stages of data visualization: acquire, parse, filter, mine, represent, refine, interact.

3. Working with data: finding data, analyze data sets and develop a visualization system to represent the data.

4. Data ethics: critical analysis of the data set (how the data was collected) and the representation methods.

5. Analysis/case studies of published works.

6. Develop a visualization system to represent complex data in an easy way.

[1] Ben F., Visualizing Data – Exploring and Explaining Data with the Processing Environment, O’Reilly Media, 2008

[2] Casey R., Ben F., Processing – A Programming Handbook for Visual Designers and Artists, 2nd Edition, MIT Press, 2014

[3] Tufte E. – The Visual Display of Quantitative Information, 2nd Edition, 2001

[4] Cairo A. – The Truthful Art: Data, Charts, and Maps for Communication, New Riders Pub, 2016

[5] Cairo A. – The Functional Art: An introduction to information graphics and visualization, New Riders Pub, 2012