Search results

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.

This study aims to explore the applications of natural language processing (NLP) and data analytics in understanding large-scale digital collections in oral history archives.

NLP and data analytics were used to analyse the oral interview transcripts of 904 survivors of the Japanese American incarceration camps collected from Densho Digital Repository, relying specifically on descriptive analysis, keyword extraction, topic modelling and sentiment analysis (SA).

The researchers found multiple geographic areas of large residential communities of ethnic Japanese people and the place names of the concentration camps. The keywords and topics extracted reflect the deplorable conditions and militaristic nature of the camps and the forced labour of the internees. When remembering history, the main focus for the narrators remains the redress and reparation movement to obtain the restitution of their civil rights. SA further found that the forcible removal and incarceration of Japanese Americans during Second World War negatively impacted and brought deep trauma to the narrators.

This case study demonstrated how NLP and data analytics could be applied to analyse oral history archives and open avenues for discovery. Archival researchers and the general public may benefit from this type of analysis in making connections between temporal, spatial and emotional elements, which will contribute to a holistic understanding of individuals and communities in terms of their collective memory.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

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.

Despite being an authentic carrier of various cultural practices, the human body is often underutilised to access the knowledge of human body. Digital inventions today have created new avenues to open up cultural data resources, yet mainly as apparatuses for well-annotated and object-based collections. Hence, there is a pressing need for empowering the representation of intangible expressions, particularly embodied knowledge within its cultural context. To address this issue, the authors propose to inspect the potential of machine learning methods to enhance archival knowledge interaction with intangible cultural heritage (ICH) materials.

This research adopts a novel approach by combining movement computing with knowledge-specific modelling to support retrieving through embodied cues, which is applied to a multimodal archive documenting the cultural heritage (CH) of Southern Chinese martial arts.

Through experimenting with a retrieval engine implemented using the Hong Kong Martial Arts Living Archive (HKMALA) datasets, this work validated the effectiveness of the developed approach in multimodal content retrieval and highlighted the potential for the multimodal's application in facilitating archival exploration and knowledge discoverability.

This work takes a knowledge-specific approach to invent an intelligent encoding approach through a deep-learning workflow. This article underlines that the convergence of algorithmic reckoning and content-centred design holds promise for transforming the paradigm of archival interaction, thereby augmenting knowledge transmission via more accessible CH materials.

This paper aims to explore the role played by the National Archives of South Africa in human rights promotion and protection. The study examined the challenges that archivists encounter when undertaking archival functions, such as acquisition, appraisal and access provision, that contribute to forming documentary archives crucial for human rights promotion and protection.

A review of literature dealing with acquisition, appraisal and access was used in this research. It was supplemented with interviews.

This paper provides recommendations of benefits in the field of archives management with a focus on the areas of acquisition, appraisal and access. The transformational discourse in the jurisdiction of archives management challenges archival institutions to be active players in selecting historical and cultural archives’ significance that is significant in human rights protections. However, despite judicial requirements that recommend the importance of archives, there is evidence that archival functions such as appraisal, acquisition and access are not being fully used, resulting in national archives institutions that are subject to irregularities that contribute to an unbalanced archives collection.

The paper was limited only to the National Archives of South Africa.

The paper makes practical implications concerning the acquisition, appraisal and providing access to human rights records.

Sufficient funding resource allocation ought to be provided to advance human rights promotion.

This paper offers informed recommendations to address the challenges of acquisition, appraisal and access provision of archive materials. The availability of archives materials reinforces the community by aiding to protect legal rights and prevent human rights violations. It was, thus, necessary to establish whether the National Archives of South Africa is actively building the archives collections that are important for human rights promotion and protection.

The purpose of this article is to share this study’s efforts to foster belonging in special collections public service spaces, as Black and Latina practitioners of color, while navigating known systemic professional barriers to inclusivity in the library information profession.

In this conceptual essay, frameworks from Black and Chicana feminist theories are applied which resonate deeply with this study’s practices but are not often encountered in library spaces, namely intersectional nepantla, which is used to situate the positionality within special collections.

Fostering belonging in special collections environments is an ongoing effort, but this study offers reflections in solidarity with all who seek to increase inclusivity and equity in their spaces. It is believed that the cumulative impact of many small actions implemented from the ground up can potentially be as significant as top-down, administrative charges.

This article's originality stems from both its authors and the methodology. As BIPOC practitioners, to the authors emphasize the authentic, day-to-day interactions that are essential to developing inclusivity and equity in special collections and archival spaces. Special collections reference workers have limited time off desk to collaborate and conduct research.

Despite ongoing research into archival metadata standards, digital archives are unable to effectively represent records in their appropriate contexts. This study aims to propose a knowledge graph that depicts the diverse relationships between heterogeneous digital archive entities.

This study introduces and describes a method for applying knowledge graphs to digital archives in a step-by-step manner. It examines archival metadata standards, such as Records in Context Ontology (RiC-O), for characterising digital records; explains the process of data refinement, enrichment and reconciliation with examples; and demonstrates the use of knowledge graphs constructed using semantic queries.

This study introduced the 97imf.kr archive as a knowledge graph, enabling meaningful exploration of relationships within the archive’s records. This approach facilitated comprehensive record descriptions about different record entities. Applying archival ontologies with general-purpose vocabularies to digital records was advised to enhance metadata coherence and semantic search.

Most digital archives serviced in Korea are limited in the proper use of archival metadata standards. The contribution of this study is to propose a practical application of knowledge graph technology for linking and exploring digital records. This study details the process of collecting raw data on archives, data preprocessing and data enrichment, and demonstrates how to build a knowledge graph connected to external data. In particular, the knowledge graph of RiC-O vocabulary, Wikidata and Schema.org vocabulary and the semantic query using it can be applied to supplement keyword search in conventional digital archives.

The purpose of the study is to assess the role of political power and politics in selecting, creating and preserving Liberation Movement archives in South Africa.

A review of literature focusing on liberations archives was carried out.

Politics and the associated power play an essential role in the selection, creation and preservation of liberation movement archives. The study found out that the African National Congress (ANC) selected the University of Fort Hare as the center to preserve liberation movements repatriated from all over the world to South Africa. The National Archives of South Africa did not play a role in the preservation of liberation movement archives. The study also noted that there existed an ineffective collaboration between the ANC and the National Archives of South Africa regarding the preservation of liberation movements archives.

The study focused on the liberation movement archives created by the ANC of South Africa only.

The establishment of liberation archives may promote social cohesion.

The liberation movement archives are a part of the history of South Africa and present perspectives on the history of the liberation of South Africa. This study, which builds on the post-colonial scholarship on liberation movement archives, discussed the significance of liberation archives.

Social media posts have been an integral part of our society’s communication and serve purposes from the personal to the national, from the mundane to the silly to the momentous. This study aims to examine social media posts as records, discussing how social media technology serves, perhaps unexpectedly, to reinforce traditional archival understandings of issues such as provenance, custody, access, disposition and preservation.

This study follows a four-step methodology. First, this study analyzes literature for a matching definition of the social media record. In the second step, we appraise three social media postings previously curated and cited in news articles by journalists to determine their characteristics – Are these social media posts “records?” Third, this study evaluates the sample records against two dominant theoretical record models, the life cycle and the continuum and attempt to apply the model specifications to the data samples. Finally, this study proposes appropriate records management solutions to address governance issues from the study findings in the conclusion section.

This study shows that, even by the most traditional of definitions, social media posts are records. The paper also demonstrates that platform mediation transforms simple narrative documents into records whose provenance, custody and control are dictated by platform logics and governance, outside of the control of their creators. Through appraisal of a small sample of “important” social media posts, this study illustrates that, rather than obsolete, traditional records management concepts and approaches are necessary to ensuring the ongoing accessibility, usability and evidentiary character of social media posts in the broader “platformized” context.

This is exploratory, theoretical work. In future works, this study plans to expand and validate aspects of this study.

This paper tests existing theoretical frameworks, namely, the Records Life cycle and the Records Continuum for applicability to the social media record. The paper also offers a view of the potential for traditional archival and records management concepts in service of a just and inclusive recordkeeping, because such concepts allow us to demonstrate the centralized, elite-serving, bureaucratic structures which underpin social media records are obscured by the seemingly decentralized, participatory nature of social media.