|6 Mar 2023||13:00 - 17:00||IT Training Room, University Library|
Convenor: Orla Delaney (CDH Methods Fellow)
Bookings will open soon!
What does it mean to prioritise small data over big data?
Cultural heritage datasets, such as museum databases and digital archives, seem to resist the quantitative methods we usually associate with data science work, asking to be read and explored rather than aggregated and analysed. This workshop provides participants with a non-statistical toolkit that will enable them to approach, critique, and tell the story of a cultural heritage dataset.
Together we will consider approaches to the database from the history of science and technology, media archaeology, and digital ethnography. This will be done alongside an overview of practical considerations relevant to databasing in the sector, such as standards like FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective Benefit, Authority to Control, Responsibility, Ethics), specific technologies like linked data, and the results of recent projects aiming to criticise and diversify the underpinning technologies of cultural heritage databases. This workshop is aimed both at cultural heritage professionals and students, and at data science researchers interested in introducing a qualitative approach to their work.
Workshop requirements: This workshop will be no-code but some proficiency with Excel will be helpful.
Target audience: CDH Methods Workshops are open to staff and graduate students who want to learn and apply digital methods and use digital tools in their research. Participants are requested to complete this simple information questionnaire before the event.
About the convenor:
Orla Delaney is a second-year PhD student in the Faculty of English at Cambridge; she holds an undergraduate degree in English Literature and German from Trinity College Dublin and an MSc in Digital Humanities from UCL. Orla’s MSc research focused on the Galton Collection of materials from UCL’s historic eugenics lab, using creative technological intervention to re-narrate that collection’s harmful histories. She has previously worked as a data scientist in the sports and marketing industries, and as a Research Fellow at the National Gallery, working on increasing the FAIR-ness of Gallery datasets by expressing them using CIDOC-CRM.