Case study: The National Archives (UK)

With this chapter on The National Archives UK (TNA), we have two main objectives. Our first objective is to raise greater awareness of current work on Artificial Intelligence (AI) applied to archives and to encourage further collaborations with other institutions on both sides of the Atlantic. TNA’s projects have been developed in response to key challenges brought about by born-digital and digitised records. They range from testing existing AI-powered tools, to developing new approaches, such as using topic modelling to discover the latent or underlying topics of texts across a corpus. Here we examine a selection of TNA’s AI projects and others from across the globe that are addressing similar challenges. Our second objective is to bring a critical perspective, from the viewpoint of Digital Humanities and Computer Science. The chapter is written by a team composed of two digital humanists (Lise Jaillant and Katherine Aske) and one computer scientist (Annalina Caputo). Drawing on this cross-disciplinary expertise, we reviewed TNA’s projects and, when appropriate, formed comparisons with projects conducted by other cultural institutions.<p></p>

Publication Details

Journal
Figshare
Published
2024-12-31
Primary Topic
Phytochemistry and Biological Activities
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Case study: The National Archives (UK)

Figshare
Phytochemistry and Biological Activities
article

Case study: The National Archives (UK)

article en

Abstract

With this chapter on The National Archives UK (TNA), we have two main objectives. Our first objective is to raise greater awareness of current work on Artificial Intelligence (AI) applied to archives and to encourage further collaborations with other institutions on both sides of the Atlantic. TNA’s projects have been developed in response to key challenges brought about by born-digital and digitised records. They range from testing existing AI-powered tools, to developing new approaches, such as using topic modelling to discover the latent or underlying topics of texts across a corpus. Here we examine a selection of TNA’s AI projects and others from across the globe that are addressing similar challenges. Our second objective is to bring a critical perspective, from the viewpoint of Digital Humanities and Computer Science. The chapter is written by a team composed of two digital humanists (Lise Jaillant and Katherine Aske) and one computer scientist (Annalina Caputo). Drawing on this cross-disciplinary expertise, we reviewed TNA’s projects and, when appropriate, formed comparisons with projects conducted by other cultural institutions.<p></p>

Figshare
Openalex Percentile: Top 28%
Phytochemistry and Biological Activities
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.