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.

Introduction; -- Artificial Intelligence and Discovering the Digitized Photoarchive; -- Web Archives and the Problem of Access: Prototyping a Researcher Dashboard for the UK Government Web Archive; -- Design Thinking, UX and Born-digital Archives: Solving the Problem of Dark Archives Closed to Users; -- Towards Critically Addressable Data for Digital Library User Studies; -- Reviewing the Reviewers: Training Neural Networks to Read Peer Review Reports; -- Supervised and Unsupervised: Approaches to Machine Learning for Textual Entities; -- Inviting AI into the Archives: The Reception of Handwritten Recognition Technology into Historical Manuscript Transcription; -- AFTERWORD: Towards a new Discipline of Computational Archival Science (CAS); -- Authors (by order of appearance in the volume).