Digital archives are transforming the Humanities and the Sciences. Digitized collections of newspapers and books have pushed scholars to develop new, data-rich methods. Born-digital archives are now better preserved and managed thanks to the development of open-access and commercial software. Digital Humanities have moved from the fringe to the center of academia. Yet, the path from the appraisal of records to their analysis is far from smooth. This book explores crossovers between various disciplines to improve the discoverability, accessibility, and use of born-digital archives and other cultural assets.
Price: $55.00
Pages: 224
Publisher: transcript publishing
Imprint: Bielefeld University Press
Series: Digital Humanities Research
Publication Date:
27 June 2022
Trim Size: 8.86 X 5.83 in
ISBN: 9783837655841
Format: Paperback
BISACs:
SOCIAL SCIENCE / Media Studies, ART / History / General, LITERARY CRITICISM / General
Lise Jaillant has a background in publishing history and digital humanities. She is an expert on issues of Open Access and privacy with a focus on archives of digital information. She was the first researcher to access the emails of the writer Ian McEwan at the Harry Ransom Center in Texas. Her work has been recognised by a British Academy Rising Star award. She is currently leading two externally-funded international networks on artificial intelligence applied to digital archives: the UK/Irish network AURA (www.aura-network.net) and the UK/US network AEOLIAN (www.aeolian-network.net). For more information, see: www.lisejaillant.com.
Frontmatter 1
Contents 5
Introduction 7
Chapter 1: Artificial Intelligence and Discovering the Digitized Photoarchive 29
Chapter 2: Web Archives and the Problem of Access: Prototyping a Researcher Dashboard for the UK Government Web Archive 61
Chapter 3: Design Thinking, UX and Born-digital Archives: Solving the Problem of Dark Archives Closed to Users 83
Chapter 4: Towards Critically Addressable Data for Digital Library User Studies 109
Chapter 5: Reviewing the Reviewers: Training Neural Networks to Read Peer Review Reports 131
Chapter 6: Supervised and Unsupervised: Approaches to Machine Learning for Textual Entities 157
Chapter 7: Inviting AI into the Archives: The Reception of Handwritten Recognition Technology into Historical Manuscript Transcription 179
AFTERWORD: Towards a new Discipline of Computational Archival Science (CAS) 205
Authors (by order of appearance in the volume) 219
