Scottish Accused Witches

About the project

The core aim of the Data and VisualisationInternship at the University of Edinburgh was to geographically locate and visualise the different locations recorded with the Survey of Scottish Witchcraft Database. 

Teaching data science with 'real-world' datasets 

During the 2017/2018 and 2018/2019 course programme, the University of Edinburgh’s Wikimedian in Residence, Ewan McAndrew, supported Design Informatics MA/MFA students to surface selected data from the original MS Access database to Wikipedia’s sister project, Wikidata, as structured, machine-readable, linked open data. The success of this project and the engaging visualisations created as a result made the case that an internship dedicated to geographically locating the places recorded in the database as linked open data would be the next logical step.

Emma Carroll, a Geology and Physical Geography undergraduate student, was recruited in May 2019 as the new Data and Visualisation intern, or ‘Witchfinder General’, as part of a three month long Equate Scotland internship.

The 'Witchfinder General' internship

Running from June to September 2019, Emma geographically located the residence location of these accused witches. The locations for 3141 different accused witches and then 822 different place names were recorded.

The places of residence which were correctly identified were to be recorded onto each accused witches’ Wikidata page. By adding the place of residence to the accused witches’ Wikidata page, it would allow for these places to later be queried using the Wikidata Query Service and then downloaded in different formats to then be visualised.

You can see Emma's work here on the website where there are now a variety of map visualisations and weekly blog articles on the whole process.

'The wicked Wikidata tale of how the 3,141 accused witches were placed on the map' 

A presentation by University of Edinburgh student Emma Carrol on the interactive witchcraft map with the Science Museum.

© Ewan McAndrew and Hannah Rothmann, University of Edinburgh, 2020, CC BY-SA 4.0, unless otherwise indicated.