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Information Visualization and the Humanities


Admission requirements

For any questions regarding the admission requirements, please contact the lecturer.

Staff and Graduate students are welcome to audit (parts of) the course, if space permits.
Please note Students of the Minor Digital Humanities have priority. Students from other programmes can only be admitted if there are places left. Students from other programmes interested in taking this course are kindly requested to contact the Coordinator of Studies and the Lecturer, if you are interested in taking this course but NOT a student of the minor Digital Humanities. See also under registration below.


While attention spans seem to grow shorter, information is growing in quantity and complexity. This is why clarity in communication and the creation of compelling visualizations is more important than ever, regardless of your disciplinal background. At the same time, it is equally important to understand the visual rhetoric and data processing that underlie common information visualizations. This course offers the technical and critical skills needed to read, collect and visualize the types of data that is central to a range of humanity studies, with a specific focus on network and spatial (GIS) approaches.
Students will be introduced to the software tools and best practices for creating, organizing, and managing quantitative and qualitative data and the strategies for creating visualizations and digital presentations that effectively convey complex issues. Readings are drawn from fields such as digital humanities, info, network, and spatial visualization, cognitive psychology, and media studies.

Course objectives

At the end of this course, you will:

  • Be able to articulate how to leverage info visualization to provide an edge in a range of situations, including academic research as well as non-academic professions.

  • Be able to critically reflect on a range of visualizations, with a specific focus on network and spatial data.

  • Know where to find some of the inspiring visualizations, thinkers, and designers in this field.

  • Be able to discuss your views on information visualization with peers as well as give and receive feedback.

  • Be able to use a number of information visualization tools, including network analytic and GIS software


Zie Rooster

Mode of instruction


Course Load

Total course load 5 EC x 28 hours = 140 hours

  • Seminar: 13 x 2 (26 hours)

  • Study of literature and online learning: (34 hours)

  • Assignment(s): (30 hours)

  • Peer Feedback: (10 hours)

  • Final project/paper: (40 hours)

Assessment method


  • Assignments: 30 percent

  • Course reading and discussion of literature: 15 percent

  • Class Participation & Peer Feedback: 15 percent

  • Final project: 40 percent

Final mark for the course is established by determining the weighted average.


Students who have scored an overall insufficient grade for the course may take a resit for the assignments and the final project, in the form of a comprehensive take-home test (in place of assignment) and a project assigned by the lecturer.

Exam review

How and when an exam review will take place will be disclosed together with the publication of the exam results at the latest. If a student requests a review within 30 days after publication of the exam results, an exam review will have to be organized.


Yes, Blackboard will be used for general course announcements and the distribution of some of the literature.
The full syllabus of the course can be found at

Reading list

The reading and other resources for this course can be found at


Enrolment through uSis is mandatory.
General information about uSis is available on the website

Registration Studeren à la carte and Contractonderwijs

Registration Studeren à la carte
Registration Contractonderwijs


Angus A. A. Mol