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 data • 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 discussed.

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 

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