HTR in the making : En studie av hur Handwritten Text Recognition görs vid tre svenska arkivverksamheter
(2023) ABMM34 20231Division of ALM and Digital Cultures
- Abstract
- In the current archival science paradigm, archives implement AI-technologies to provide content as structured, machine-readable data. One of these technologies is Handwritten Text recognition (HTR) which can transcribe handwritten text. Thus, HTR turn raw digitized archival documents into machine-readable format. Technology is not developed in a vacuum, but is shaped by heterogeneous factors, therefore it is relevant to shed light on how HTR technology is implemented in the Swedish archival sector. The purpose of this thesis is therefore to create an understanding of the relationship between Handwritten Text Recognition and archives by studying projects where this AI technology is being applied. By Actor-Network Theory the analysis is... (More)
- In the current archival science paradigm, archives implement AI-technologies to provide content as structured, machine-readable data. One of these technologies is Handwritten Text recognition (HTR) which can transcribe handwritten text. Thus, HTR turn raw digitized archival documents into machine-readable format. Technology is not developed in a vacuum, but is shaped by heterogeneous factors, therefore it is relevant to shed light on how HTR technology is implemented in the Swedish archival sector. The purpose of this thesis is therefore to create an understanding of the relationship between Handwritten Text Recognition and archives by studying projects where this AI technology is being applied. By Actor-Network Theory the analysis is looking for agencies, mediators, and translation within the shaping processes of the HTR technology. The material span three projects carried out by Swedish archives managements, at Uppsala University Library, the Swedish National Archives and the Swedish National Heritage Board. Data was collected by interviewing archivists involved in the projects and from qualitative document analysis of the projects’ descriptions. The analysis provides an indication that HTR is particularly valued for future data driven research and for the future archival users for whom HTR is seen as a prerequisite. Making HTR through citizen science and crowdsourcing is also understood as a central factor for how HTR is being made within the projects. Continually the results show that HTR is made nationally within Sweden and Finland, partly by the exchange of experiences and by the HTR infrastructure Transkribus. HTR is understood, not primarily as a tool to produce results, but as a methodological updating within the institutions, and a step towards future expectations. The conclusions can therefore in many ways be related to the archive-as-data paradigm where the archives studied take part in the ongoing discourse of change and with making themselves relevant for the future. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9117098
- author
- Schön, Camilla LU
- supervisor
- organization
- alternative title
- HTR in the making : How Handwritten Text Recognition is made within three Swedish archives managements
- course
- ABMM34 20231
- year
- 2023
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Archival science, Handwritten Text Recognition, Actor-Network Theory, artificial intelligence, The Swedish National Archives, Swedish National Heritage Board, Uppsala University Library
- language
- Swedish
- id
- 9117098
- date added to LUP
- 2023-06-20 13:50:36
- date last changed
- 2023-06-20 13:50:36
@misc{9117098, abstract = {{In the current archival science paradigm, archives implement AI-technologies to provide content as structured, machine-readable data. One of these technologies is Handwritten Text recognition (HTR) which can transcribe handwritten text. Thus, HTR turn raw digitized archival documents into machine-readable format. Technology is not developed in a vacuum, but is shaped by heterogeneous factors, therefore it is relevant to shed light on how HTR technology is implemented in the Swedish archival sector. The purpose of this thesis is therefore to create an understanding of the relationship between Handwritten Text Recognition and archives by studying projects where this AI technology is being applied. By Actor-Network Theory the analysis is looking for agencies, mediators, and translation within the shaping processes of the HTR technology. The material span three projects carried out by Swedish archives managements, at Uppsala University Library, the Swedish National Archives and the Swedish National Heritage Board. Data was collected by interviewing archivists involved in the projects and from qualitative document analysis of the projects’ descriptions. The analysis provides an indication that HTR is particularly valued for future data driven research and for the future archival users for whom HTR is seen as a prerequisite. Making HTR through citizen science and crowdsourcing is also understood as a central factor for how HTR is being made within the projects. Continually the results show that HTR is made nationally within Sweden and Finland, partly by the exchange of experiences and by the HTR infrastructure Transkribus. HTR is understood, not primarily as a tool to produce results, but as a methodological updating within the institutions, and a step towards future expectations. The conclusions can therefore in many ways be related to the archive-as-data paradigm where the archives studied take part in the ongoing discourse of change and with making themselves relevant for the future.}}, author = {{Schön, Camilla}}, language = {{swe}}, note = {{Student Paper}}, title = {{HTR in the making : En studie av hur Handwritten Text Recognition görs vid tre svenska arkivverksamheter}}, year = {{2023}}, }