Archives, Access and Artificial Intelligence
Working with Born-Digital and Digitized Archival Collections
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.
Kapitel-Übersicht
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Frontmatter
Seiten 1 - 4 -
Contents
Seiten 5 - 6 -
Introduction
Seiten 7 - 28 -
Chapter 1: Artificial Intelligence and Discovering the Digitized Photoarchive
Seiten 29 - 60 -
Chapter 2: Web Archives and the Problem of Access: Prototyping a Researcher Dashboard for the UK Government Web Archive
Seiten 61 - 82 -
Chapter 3: Design Thinking, UX and Born-digital Archives: Solving the Problem of Dark Archives Closed to Users
Seiten 83 - 108 -
Chapter 4: Towards Critically Addressable Data for Digital Library User Studies
Seiten 109 - 130 -
Chapter 5: Reviewing the Reviewers: Training Neural Networks to Read Peer Review Reports
Seiten 131 - 156 -
Chapter 6: Supervised and Unsupervised: Approaches to Machine Learning for Textual Entities
Seiten 157 - 178 -
Chapter 7: Inviting AI into the Archives: The Reception of Handwritten Recognition Technology into Historical Manuscript Transcription
Seiten 179 - 204 -
AFTERWORD: Towards a new Discipline of Computational Archival Science (CAS)
Seiten 205 - 218 -
Authors (by order of appearance in the volume)
Seiten 219 - 224
21. Juni 2022, 224 Seiten
ISBN: 978-3-8376-5584-1
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