Background

Rapidly growing quantities of well-available digital textual data are the basis for a scientific field that has developed in recent years - the digital humanities. As with all types of data in general, textual data should be carefully sourced, created and prepared. This course is for anyone who wants to approach the topic of textual data preparation and processing.

Learning contents

After an introduction to Digital Humanities, we will practice a generic "standard" workflow using free, generic software tools that are well applicable within a multidud of domains. The workflow includes these steps: Data Scraping/Web Scraping, Data Refinement using OpenRefine, and creating network visualizations using Gephi. If necessary or if there is still time, we write a few lines of Python code in Jupyter.

Learning objectives

• Recognize the power of automated data acquisition through an example of web scraping
• Gaining first proficiency applying the software tools OpenRefine, and Gephi
• Being able to write a few lines of Python code in Jupyter 

Prior knowledge

No specific requirements, a general interest in learning new tools.

Technical requirements

• Own laptop

• Connection to Wifi via eduroam or equivalent access (see: https://www.uni-bremen.de/en/zfn/wifi/overview-wifi)

• Installation of the latest versions of OpenRefine, and Gephi (participants will receive installation instructions prior to the workshop)
• If you do not have any programming environment (e.g. Python, R, Rstudio, etc.) installed on your computer, you can use web-based options: For example, participants with access to the Uni Bremen ZfN Services can use the Uni Bremen JupyterHub. Alternatively, participants from Germany can use the NFDI JupyterHub.

The Lecturer

Dr. Manfred Nölte Digital Humanities Advisor and Subject Librarian for Mathematics and Computer Science at the State and University Library Bremen

Find out more about the Data Train lectures on our website.

This event is organized by