Digitization: from Object to Data


Course Objective

At the end of this course the student is able to:
• Understand the complexity and challenges of (global) data developments
• Understand the relevance of data-oriented research for humanities and
social sciences
• Critically reflect on the implications of the selection, structuring
and manipulation of data for the outcome of their work
• Understand and handle the heterogeneity and diversity of humanities
• Have a basic knowledge of data formats and ontologies
• Apply various computational techniques for cleaning, parsing and
structuring / modelling of digital data

Course Content

The humanities and social sciences have more and more digital material
at their disposal. Increasingly literature, newspapers, archival sources
as well as library and museum catalogues become available in digital
formats. Meanwhile, digital born data from social media, news media
government bodies and all sorts of institutions allow scholars to work
with enormous amounts of new data on human behaviour and communication.
How can humanities researchers and social scientists use digital data to
support their research? What are the digital tools at their disposal and
how can these tools provide new perspectives and research questions?

A first step in data-oriented research is a critical understanding of
the providence, characteristics, shape and limits as well as the
potential of a given dataset. In this course, students will familiarize
with the ‘research data lifecycle’: Starting with the critical analysis
of how data are generated or how they are created through digitization
of original sources (objects), how data are formatted and structured,
how they can be cleaned and annotated, how they can be modelled and
analysed, and finally documented, stored and published. Practical
choices that are to be made in the course of this process have crucial
implications for the way data can be used in research. In class we will
discuss the use of ontologies and different data formats and data
models. Also practical problems like the heterogeneity of humanities
data, incompleteness, disambiguation, partiality and bias will be

This course is organized in close collaboration with the Huygens
Institute of the Royal Netherlands Academy of Arts and Sciences in
Amsterdam, a research institute that performs analytical research into
Dutch literature, history and the history of knowledge, using innovative
digital methods. Huygens Institute is one of the forerunners in the use
of digital research methodology and the building of digital
infrastructure for the humanities in the Netherlands.

Classes will consist or a combination of lectures, discussion and
hands-on practicals in which students will learn to work with a number
of tools. Students will apply their knowledge and skills by creating a
curated dataset and writing a short paper.

Teaching Methods

Lectures, seminars and hands-on tutorials combined in weekly sessions (1
x 3.45 hours)

Method of Assessment

Written assignment (30%), practical assignment (30%) and short final
paper (40%)


Workbench Digital Humanities VU: http://www2.fgw.vu.nl/dighum/
Further readings will be made available through CANVAS

Target Audience

Students who take the University Minor ‘Digital Humanities and Social
Analytics’. As long as there are available places, we welcome other
students of all disciplines, including international exchange students.
Please contact the coordinator in advance.

Additional Information

Part of the classes (4 out of 7) will take place at the Huygens
Institute, located in the centre of Amsterdam: Spinhuis, Oudezijds
Achterburgwal 185, 1012 DK AMSTERDAM

General Information

Course Code L_AABAALG070
Credits 6 EC
Period P1
Course Level 200
Language of Tuition English
Faculty Faculty of Humanities
Course Coordinator dr. H.M.E.P. Kuijpers
Examiner dr. H.M.E.P. Kuijpers
Teaching Staff dr. H.M.E.P. Kuijpers

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Seminar, Lecture
Target audiences

This course is also available as: