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This study aims to explore the implementation of artificial intelligence (AI) in archival practice by presenting the thoughts and opinions of working archival practitioners. It contributes to the extant literature with a fresh perspective, expanding the discussion on AI adoption by investigating how it influences the perceptions of digital archival expertise.

In this study a two-phase data collection consisting of four online focus groups was held to gather the opinions of international archives and digital preservation professionals (n = 16), that participated on a volunteer basis. The qualitative analysis of the transcripts was performed using template analysis, a style of thematic analysis.

Four main themes were identified: fitting AI into day to day practice; the responsible use of (AI) technology; managing expectations (about AI adoption) and bias associated with the use of AI. The analysis suggests that AI adoption combined with hindsight about digitisation as a disruptive technology might provide archival practitioners with a framework for re-defining, advocating and outlining digital archival expertise.

The volunteer basis of this study meant that the sample was not representative or generalisable.

Although the results of this research are not generalisable, they shed light on the challenges prospected by the implementation of AI in the archives and for the digital curation professionals dealing with this change. The evolution of the characterisation of digital archival expertise is a topic reserved for future research.

Maintaining infrastructures such as roads, bridges, railways and other civil constructions requires long term documentation that ideally should comprise a reliable reflection of the physical structures. However, the Swedish Transport Administration (TRA) states that its documentation is currently inadequate and that new working method are needed. The purpose of this paper is to study how the agency is working to improve their recordkeeping, by taking a closer look at two new positions that now coordinate the delivery of documentation from the building process teams to the agency. What is their role and what challenges do they face with regard to creating, sharing and preserving records with other areas across the TRA? The study’s purpose is also to discuss the concept of the archive in the current environment and how existing archival theory can be applied to long term documentation.

The study used a case study method, as the aim was to explore and understand recordkeeping practices and theoretical implications, without seeking to generalize the findings outside the Swedish Government. Two positions – the delivering coordinator and the receiving coordinator – were chosen as relevant focuses, due to their function as links between departments in which it was previously indicated that creating and maintaining reliable recordkeeping was difficult and where organizational structure might challenge the traditional archival theory. Documents and reports from the agency were used as research material through documentary analysis and a questionnaire consisting of 10 questions was used to conduct semi-structured interviews with 10 coordinators at the agency.

Obtaining the correct documentation at the right time and of appropriate quality from contractors and entrepreneurs was difficult, despite detailed contractual rules and regulations identifying what should be delivered. The work of the coordinators was formally connected to the important tasks of creating, sharing and preserving records with other areas within the TRA, but in reality, the coordinators faced several difficulties due to expectations of their professional role, practices in information management between different departments and archives creation at the entire agency. The interviewees therefore had differing perceptions of what was meant by TRA’s “archive”: it was variously perceived as only including the registry; comprising only the records preserved by the archives department or encompassing only those records in the registry or in the agency’s business system/s. Findings indicate that the concepts of multiple provenances and the recordkeeping “single mind” might provide insights to better inform the recordkeeping principles needed to improve the current environment.

The study was limited to the 10 interviewees in 2 roles, although there are more positions involved in handling records. Future studies may solidify or contest the different themes identified in the present paper, through interviews of those additional roles at the agency. This paper uses the Swedish concept of the archive as a point of departure in its analysis.

By increasing the knowledge about positions that are responsible for handling records at an agency, this paper can get a better understanding of how they affect the ultimate creation of archives. This will give Swedish public agencies and other organizations, better results when they are creating strategies to preserve reliable records for the future.

Many libraries and archives maintain collections of research documents, such as administrative records, with paper-based formats that limit the documents' access to in-person use. Digitization transforms paper-based collections into more accessible and analyzable formats. As collections are digitized, there is an opportunity to incorporate deep learning techniques, such as Document Image Analysis (DIA), into workflows to increase the usability of information extracted from archival documents. This paper describes the authors' approach using digital scanning, optical character recognition (OCR) and deep learning to create a digital archive of administrative records related to the mortgage guarantee program of the Servicemen's Readjustment Act of 1944, also known as the G.I. Bill.

The authors used a collection of 25,744 semi-structured paper-based records from the administration of G.I. Bill Mortgages from 1946 to 1954 to develop a digitization and processing workflow. These records include the name and city of the mortgagor, the amount of the mortgage, the location of the Reconstruction Finance Corporation agent, one or more identification numbers and the name and location of the bank handling the loan. The authors extracted structured information from these scanned historical records in order to create a tabular data file and link them to other authoritative individual-level data sources.

The authors compared the flexible character accuracy of five OCR methods. The authors then compared the character error rate (CER) of three text extraction approaches (regular expressions, DIA and named entity recognition (NER)). The authors were able to obtain the highest quality structured text output using DIA with the Layout Parser toolkit by post-processing with regular expressions. Through this project, the authors demonstrate how DIA can improve the digitization of administrative records to automatically produce a structured data resource for researchers and the public.

The authors' workflow is readily transferable to other archival digitization projects. Through the use of digital scanning, OCR and DIA processes, the authors created the first digital microdata file of administrative records related to the G.I. Bill mortgage guarantee program available to researchers and the general public. These records offer research insights into the lives of veterans who benefited from loans, the impacts on the communities built by the loans and the institutions that implemented them.