Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view.
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Session Overview |
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WORKSHOP: GLAM LABS & JUPYTER NOTEBOOKS [PART 1]
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Explore the use of the GLAM Labs Checklist, Datasheets, and Jupyter Notebooks for digitized and born-digital collections 1British Library; 2University of Alicante, Spain; 3National Library of Norway; 4International Internet Preservation Consortium; 5National Library of New Zealand There are often significant barriers to accessing and using collections as data in the GLAM sector, often demanding technical expertise and suitable IT infrastructure. Although training in digital research skills is becoming more widespread, GLAM institutions still face the challenge of determining how best to provide access to their digital collections in ways that encourage the use of these skills. Jupyter Notebooks are an increasingly popular form of hybrid tooling that combines data and code to make digital collections more accessible, particularly for less technical users. GLAM institutions have started to employ Jupyter Notebooks as a new approach to demonstrate how users can access and experiment with datasets derived from their collections [1]. Projects like the GLAM Workbench [2] illustrate their utility across various types of collections, including both digitized collections and web archives. They offer interactive and reproducible environments[3] for exploring and analyzing collections of data. This workshop will help participants explore digitised and born-digital collections using reproducible code and Jupyter Notebooks. These collections will be placed in the context of “datasheets for datasets,” which provide structured documentation about how a dataset was created. Notebooks and datasheets are two key steps in the “Checklist to Publish Collections as Data in GLAM Institutions” (glamlabs.io/checklist). Expert facilitators will help users explore the possibilities of Notebooks, focusing on three areas: 1) working on one specific topic using data from digitised and born-digital collections (e.g. news), 2) using and creating reproducible notebooks, and 3) understanding existing infrastructures, cloud services, and workflows for publishing computationally ready datasets. Use cases and discussion will also address preservation challenges and future reuse of notebooks and datasheets. Format The workshop will begin with short presentations on the GLAM Labs Checklist, datasheets for data sets, and the framework for creating a collection of Jupyter Notebooks [3]. These will include examples based on digitized and born-digital collections, and guidance on how to get started using a Jupyter Notebook. The main part of the workshop will involve participants using and exploring the datasets with one or more of the available Jupyter Notebooks. Data research infrastructures and cloud services to run Jupyter Notebooks will be presented. The session will wrap up with a discussion on the preservation challenges of the notebooks and datasheets. Learning Outcomes The workshop aims to provide the following outcomes:
References
Acknowledgments This workshop builds on the work of the GLAM Labs community and the Web Archives as Data workshops delivered at various conferences, most recently at the Digital Humanities in the Nordic and Baltic Countries (DHNB) 2025 Conference in Reykjavík and the Web Archiving Conference (WAC) in Oslo. | ||