Humanities Data and Mapping Environments

Spatial Humanities are increasingly practised every day by researchers, journalists, and other experts in various fields. This discipline involves the use of many different tools. The main objective of this workshop is to introduce participants to the vast world of spatial humanities through a general overview of the methodological approaches and tools needed for such research. This workshop is designed for the total beginner who would like to explore how a spatial dimension can enrich humanities and interdisciplinary research projects and who would also like to learn basic skills for collecting and organizing data in order to integrate such methods into their research workflows.

  • The workshop lasts a total of 36 hours, divided into two weeks of 18 contact hours. The objectives of this workshop are:
  • To learn the technical basics of a digital Spatial Humanities environment: formats, applications, software, and programming languages.
  • To understand how to structure data in order to create a dataset suitable for a spatial humanities search.
  • To manage some of the most important applications and software for spatial data visualization.
  • To approach the creation of maps through programming languages.

In the first part of the course we conduct a critical review of a range of projects in the spatial humanities, examining their scope and the rhetorical strategies they employ for spatial storytelling and argument. What we propose is an interdisciplinary approach to spatial analysis that can be adapted to the research of each of the course participants. We will introduce digital tools that allow each of the participants to frame their own research within a spatial data visualization system.

We will therefore begin with the basics necessary for digital cartography: creation of a dataset, georeferencing of data, and visualization in a digital environment. Students will be introduced to normalization and wrangling techniques and will contrast the manual, slow creation of data with more automated forms.

In the second part of the course, the participants will learn some web development skills so that they can do some basic web mapping. We will explore some of the most popular opensource georeferenced data processing software, such as: QGIS, or Gephi. We’ll tackle an introduction to mapping through the use of programming languages (JavaScript or Python or R). The goal is not to teach how to program but to know how to move within a code by searching for the necessary information and modifying it according to the research needs of each participant.

Students will be encouraged to present their individual research on the last day of both weeks.