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This MRes project is situated between informatics, data science and creative computing. The project will investigate the research question: “How can small GLAMs (Galleries, Libraries, Archives and Museums) make best use of data-driven tools and digital technology innovation to enhance their collections?”
The United Kingdom has many cultural institutions that exist with a mission to provide access to knowledge and for over a decade there has been increased digitisation of collections, but these are often underutilised (Hawkins, 2022) or have unforeseen constraints to prevent wider engagement (Baker, 2016). Many smaller institutions typically have highly specialised collections that include digital components (images, video, voice recordings, datasets) but often lack the skills or resources to enhance public awareness and engagement with these smaller collections. Research projects are often driven by technological trends and the advent of new technologies (Münster et al, 2021) but there is an abundance of data that is underutilised. This research project proposes a practice-based approach working with material available in the collections at Edinburgh Napier University (e.g. War Poets Collection, Edward Clark Collection, Mehew Robert Louis Stevenson or Jim Haynes Archive) to develop digital projects, that encourage thoughtful use and collaboration of materials for public engagement. Using available datasets, the project will explore the challenges of making data meaningful for more creative and engaging outputs (Istvandity et al, 2024). The project will explore how digital innovation can empower a range of activity relating to public engagement, content curation, digitisation, description and metadata creation, long-term file preservation, as well as access and discoverability to primary source material.
Discipline: User Experience Design, Informatics, Data Analysis, Data Science, Interaction Design, HCI
Academic qualifications:
A first degree (at least a 2.1) ideally in Creative Computing, Computer Science, HCI, or Applied Technology with a good fundamental knowledge of data science and design visualisation.
English Language Requirement:
IELTS score must be at least 6.5 (with no less than 6.0 in each of the four components), Other equivalent English language qualifications will be accepted. Full details of the University’s policy are available online.
Essential attributes:
Desirable attributes:
The application must include:
Applications can be submitted here. To be considered, the application must use:
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