Using linked open data to put accused witches on the map – The wicked findings of the Witchfi Home : ALT Annual Conference 2019

Using linked open data to put accused witches on the map – The wicked findings of the Witchfi

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Tue, Sep 3 2019, 4:15pm – 5:00pm

Authors: Ewan McAndrew, and Emma Carroll

Room: McEwan Hall

Theme: Learning Technology for wider impact

Type: Poster + Gasta (5min)

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Session Description

Submitted on behalf of Equate Intern (the lead author):

“If people asked you ‘What happened to the semantic web?’ You say: ‘it took point at schema’ and point to the linked-open data cloud” (“Sir Tim Berners-Lee 2016 ACM A.M. Turing Lecture, May 29, 2018”, 2018)

The pressing need for implementing data literacy in the curriculum to produce a workforce equipped with the data skills necessary to meet the needs of Scotland’s growing digital economy presents a massive opportunity for educators, researchers, data scientists, repository managers and student learners alike.

Our university’s mission is to “discover, develop and share knowledge”. This mission links with the non-profit Wikimedia Foundation’s vision “to empower and engage people around the world to collect and develop educational content under a free license or in the public domain, and to disseminate it effectively and globally”.

Working with our ‘Wikimedian-in-Residence’, our Equate ‘Data and Visualisation’ Intern (or ‘Witchfinder General’) worked with a much-loved but static resource, the Survey of Scottish Witchcraft database, and applied the principles of open scholarship over a 3 month placement (June to September 2019) by reusing open licensed content from cultural institutions whilst collaborating with a diverse online community.

This presentation will provide an example of real-world application of teaching and learning and how an Equate Student Intern was employed to work with Wikipedia’s sister project, Wikidata, to build on the successful project work of student volunteers from the Data Science for Design MSc.

“A common critique of data science classes is that examples are static and student group work is embedded in an ‘artiﬁcial’ and ‘academic’ context. We look at how we can make teaching data science classes more relevant to real-world problems. Student engagement with real problems—and not just ‘real-world data sets’—has the potential to stimulate learning, exchange, and serendipity on all sides, and on different levels: noticing unexpected things in the data, developing surprising skills, ﬁnding new ways to communicate, and, lastly, in the development of new strategies for teaching, learning and practice.” (Corneli, Murray-Rust & Bach, 2018)

Over two years, student volunteers were intrinsically motivated to surface the information from the Survey of Scottish Witchcraft database in order to enable further insights and research through adding information to the Linked Data Cloud as 5-star linked open data.

Following this, the Equate intern was tasked to:

• Re-use pre-existing data and generate new data which allows geographical mapping of parts of the dataset.
• Develop other visualisations of the data which allow new, previously unknown, patterns in the data to be extracted and new stories and hypotheses about the data to be developed.
• Document processes and write regular blog posts to update the community on their progress.

This presentation will outline the methodology employed, the challenges experienced and the end of project conclusions & visualisations. All with a view to aiding students’ understanding of data literacy and to help shed new light on a little understood period of Scottish history. This, in turn, may help fuel discoveries by dint of surfacing this data and linking it with other related datasets.

References

Corneli, J., Murray-Rust, D., & Bach, B. (2018). Towards Open-World Scenarios: Teaching the Social Side of Data Science. In Cybernetic Serendipity Reimagined Symposium, Proc. Annual Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour

City Region Deal secured | The City of Edinburgh Council. (2017). Retrieved from https://www.edinburgh.gov.uk/news/article/2329/city_region_deal_secured

Goodare, J., Martin, L., Miller, J., and Yeoman, L., ‘The Survey of Scottish Witchcraft’, http://www.shca.ed.ac.uk/witches/ (archived January 2003, accessed ’13 March 2019′).

Sir Tim Berners-Lee 2016 ACM A.M. Turing Lecture, May 29, 2018. (2018). Retrieved from https://www.youtube.com/watch?v=BaMa4u4Fio4

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