WikiWicca: Teaching data literacy with the Survey of Scottish Witchcraft and enabling Open Science and Open Scholarship with Wikidata
“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.” – Towards Open-World Scenarios: Teaching the Social Side of Data Science (2018) by Dave Murray Rust, Joe Corneli and Benjamin Bach. 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 and repository managers alike. This presentation will provide an example of real-world application of teaching and learning as part of a Data Science for Design MSc and how working with Wikipedia’s newest sister project, Wikidata and its suite of tools, motivated students to help surface, preserve and enhance a much-loved repository of information, the Survey of Scottish Witchcraft. Importing from a static MS Access database as machine-readable, structured linked data allows for the direct and indirect relationships to be explored, enabling further insights and research. The students felt proud to take part and found the project “very meaningful”. “If people ask you 'What happened to the semantic web?' You say it took point at http://schema.org and point to the Linked Data Cloud" - Tim Berners-Lee, 29 May 2018. Wikidata features in the 2018 Linked Data Cloud as a massive dataset of over fifty million data items. The power of a centralised hub of linked open data to freely share and parse knowledge between different institutions, different research projects and different repositories, between geographically and culturally separated societies, and between languages instantly is an empowering thing; reclaiming the constructive heart of the open web as first envisaged. Sharing your data to Wikidata is also the most cost-effective way to surface your data, complementing it with knowledge from the largest reference work on the web and linked datasets from across the internet – providing information with a transparent, verifiable provenance. This presentation will also include a look at the ever-growing suite of easy-to-use tools available like OpenRefine’s Wikidata function – a one-stop shop for processing and exporting data - and the Source Metadata tool which scrapes from PMIDS, DOIs, and ORCID identifiers to build a bibliographic repository in Wikidata. Applications with user-friendly UIs can be built to read/write from Wikidata; like the Scholia Web service which creates on-the-fly scholarly profiles for researchers, organisations, journals, publishers, individual scholarly works, and research topics; enabling and empowering Open Science and Open Scholarship. All for free. All for furthering discovery and the sum of all human knowledge.
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