Data Science, Linked Data and Historical Social Research (online)



Organised by:

The University of Edinburgh


Dr Richard L. Zijdeman, Senior Researcher, Chief Data Officer, International Institute of Social History, Amsterdam, The Netherlands


Intermediate (some prior knowledge)


Laura Marshall (Monday-Wednesday)

video conference logo

Venue: Online


The great thing about pies is that they can be reproduced over and over because of their recipes. Research results on the other hand are seldomly reproduceable, because rarely proper ‘recipes’ describing data gathering, cleaning, linking, and analysis are provided. This course aims for you to learn how to create recipes for your (quantitative) research and allow others to build on your efforts.

The course sets out with a basic introduction of the data based research workflow. For each step, it will provide more detailed insights, such as the FAIR principles for data, and give pointers for pragmatic decisions to be applied to your project. In addition, the course will show how the Semantic Web or Linked Open Data is of great benefit to your data gathering efforts as well as communicating your results via the Web. The course heavily draws on examples from social science and history data, bringing interesting use cases for heterogeneous (long tail) data and dealing with GDPR as a researcher.

This course will be delivered Online using zoom.

Course Timings: 10:00 - 16:00

Target Audience: This course is suitable for any researchers that would like to better understand how approaches, protocols and techniques in data science can be incorporated into historical social research.


The fee per teaching day is: • £30 per day for UK/EU registered students • £60 per day for staff at UK/EU academic institutions, UK/EU Research Councils researchers, UK/EU public sector staff and staff at UK/EU registered charity organisations and recognised UK/EU research institutions. • £100 per day for all other participants. Cancellation Policy: Please be reminded that you will be charged the full registration fee if you cancel your place within 4 weeks before the training delivery date or you fail to attend.

Website and registration:




Historical comparative research, Digital Social Research, Interdisciplinary and Multidisciplinary Research, Data Management , Linked Open Data, Semantic Web, FAIR data

Related publications and presentations:

Historical comparative research
Digital Social Research
Interdisciplinary and Multidisciplinary Research
Data Management

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