Search results

The current predominant delivery format resulting from digitization is PDF, which is not appropriate for the blind, partially sighted and people who read on mobile devices. To meet the needs of both communities, as well as broader ones, alternative file formats are required. With the findings of the eBooks-On-Demand-Network Opening Publications for European Netizens project research, this study aims to improve access to digitized content for these communities.

In 2022, the authors conducted research on the digitization experiences of 13 EODOPEN partners at their organizations. The authors distributed the same sample of scans in English with different characteristics, and in accordance with Web content accessibility guidelines, the authors created 24 criteria to analyze their digitization workflows, output formats and optical character recognition (OCR) quality.

In this contribution, the authors present the results of a trial implementation among EODOPEN partners regarding their digitization workflows, used delivery file formats and the resulting quality of OCR results, depending on the type of digitization output file format. It was shown that partners using the OCR tool ABBYY FineReader Professional and producing scanning outputs in tagged PDF and PDF/UA formats achieved better results according to set criteria.

The trial implementations were limited to 13 project partners’ organizations only.

This research paper can be a valuable contribution to the field of massive digitization practices, particularly in terms of improving the accessibility of the output delivery file formats.

The purpose of this study is to highlight the indigenous knowledge systems (IKS) preservation efforts in South Africa, with a focus on the National Recordal System and the Indigenous Knowledge Systems Documentation Centres (IKSDCs) across South Africa.

Anchored in the interpretivist paradigm, the qualitative research approach was adopted to explore the objectives of the study. The multiple case study method was considered appropriate and adopted for the study. The data for this study was collected through comprehensive face-to-face interviews and Web content analysis. The population of the study consisted of the staff at the IKSDCs in the selected academic institutions. The purposive sampling technique was used to select the following set of participants in each academic institution: IKS managers/coordinators, digitization officers and online collection administrators.

The findings provide an in-depth understanding of the IKS landscape in South Africa. The findings and recommendations of this paper would be useful to researchers who wish to know more about digitization efforts in South Africa. It would also be useful to all stakeholders and policymakers.

The paper brings to the fore the efforts of the South African government in preserving IKS through documentation and digitization. The paper highlights the sources of indigenous knowledge, types of indigenous knowledge captured, how the indigenous knowledge is ingested in the repositories and how the data is captured. Generally, the roles of the IKSDCs in the capture and preservation of IKS are highlighted.

The objective of this study is to establish the current state of library and information science (LIS) scholarship pertaining to anti-racism, equity, inclusion and social justice initiatives.

Using comprehensive search strategies, three LIS databases were searched for relevant literature published in the last 10 years and results were exported and de-duplicated using Endnote. Citations were screened by two blinded, independent reviewers based on pre-defined eligibility criteria. Citations in the final data set were then hand coded by three reviewers using deductive coding. Subject terms for all citations were categorized and consolidated to identify major themes across the corpus of included publications. Results were analyzed using bibliometrics and thematic analysis.

A total of 691 unique citations were included in this analysis based on inclusion criteria. Publication productivity has generally increased from 2011 to 2020; findings show publications from 170 source titles and 944 authors representing 33 countries. Prevalent themes included access to information, multiculturalism and social justice. Various populations groups, areas of LIS practice, library types and social justice topics have been addressed in the literature. Over 15% of citations focused on anti-racism efforts in LIS.

This study applied both bibliometric and thematic approaches to analyzing LIS literature at macro and micro levels regarding anti-racism, equity, inclusion and social justice.

Ghanaian public universities have fully embraced the concept of open access. This is evident in the increasing numbers of institutional repositories (IRs) by universities in Ghana. However, to ensure the sustainability of these IRs, it is vital the current IR infrastructure is capable of responding to current and future demands. The purpose of this study is to investigate the sustainability of the current IR infrastructure of public universities in Ghana.

The convergent parallel mixed methods design was adopted. A total of 830 respondents comprising IR managers, library staff (digitisation and e-resources units), postgraduate students, lecturers and university librarians from five public universities in Ghana were sampled for this study. A questionnaire and a semi-structured interview guide were the main instruments used for data collection.

The findings of this study revealed that the IR infrastructure of public universities in Ghana is robust and has the capacity to expand when the need arises. However, funding, cost of internet connectivity, personnel and erratic power supply were identified as major challenges confronting IRs in Ghana.

This study highlighted Ghana's existing IR infrastructure situation. This study is a significant contribution to the literature from West Africa because there is not much research on IR infrastructure from this part of the world.

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.

The purpose of this study is to investigate artificial intelligence (AI) as enabler of future library services, with consideration to how prepared are librarians in African university libraries.

This study applied the interpretive content/document analysis of literature harvested from different databases of Scopus and Web of Science. AI could be used to perform daily routines in circulation, serial, reference and selective dissemination of information among others. It could also be applied to the provision of innovative services of recognition of library activities such as answering research quarries, cataloguing and classification of library materials and management of library system software of different databases within the library systems.

It could be deduced from the study that AI would continue to serve as a panacea to future library services irrespective of its geographical context. Due to the evolving nature of knowledge growth, AI having its roots in the field of engineering has been found useful to support future library services. The support accrued from library service delivery in the library profession has made librarians continue to interact with other intelligent machines that can demonstrate human behaviour even though they are not real human beings. The behaviour of machines and AI where human beings play a significant role has brought many renovations in the management of complex tasks of processing, communication, knowledge representation, decision making and suggestions, on potentials of diverse work operations.

The understanding that the present paper portrays in the context of future library services is that there is no way the AI could function without a human interaction perspective when drawing an analogy from computer science, information science and information systems fields of study.

The interest of users across their background would be strengthen if AI advances transformed the handling complex tasks of processing, communication, knowledge representation, decision-making and giving suggestions, among other things. The possibilities of diverse work operations from empirical evidence of studies consulted in recent times gave the authors the impetus to consider AI as the enabler of future library services.

The increasing demands from library patrons have prompted librarians to adapt their methods of delivering services. These emerging technologies have also brought about shifts in approaches to teaching and learning. Consequently, the recent surge in digital technology-driven service innovations has ushered in a fresh paradigm for education and research. In response to these changes, librarians are actively seeking novel and innovative technologies to enhance user experiences within their libraries. They serve as catalysts for introducing modern and advanced technologies, consistently adapting to contemporary tools that enhance their offerings.

Client-led service innovation has gained currency in academic libraries owing to ever-shifting client preferences. Library clients are interested in determining which services libraries should offer to meet their information needs. Several studies have investigated service innovation or improvement in libraries with an emphasis on client involvement. However, it is not clear whether the reward culture influences client-focused service innovation in the context of Uganda.

This multiple-case study triangulated data from a survey of 80 staff members, three semi-structured interviews conducted with three library heads, and data from institutional documents. Data were analysed quantitatively and qualitatively.

The results indicated that the financial reward culture did not influence client-led service innovation in any way; instead, non-financial rewards had an impact. Therefore, library managers need to appreciate that clients are no longer interested in financial rewards, but rather in non-financial rewards that have enduring value.

The study underscores the importance of client-led services in an information environment that has been invaded by industry 4.0 and calls upon librarians to use the opportunity to provide innovative services.

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.

The purpose of this paper is to highlight the initial top-level findings of a year-long comprehensive needs assessment, conducted with the digital library community, to reveal reuse assessment practices and requirements for digital assets held by cultural heritage and research organizations. The type of assessment examined is in contrast to traditional library analytics, and does not focus on access statistics, but rather on how users utilize and transform unique materials from digital collections.

This paper takes a variety of investigative approaches to explore the current landscape, and future needs, of digital library reuse assessment. This includes the development and analysis of pre- and post-study surveys, in-person and virtual focus group sessions, a literature review, and the incorporation of community and advisory board feedback.

The digital library community is searching for ways to better understand how materials are reused and repurposed. This paper shares the initial quantitative and qualitative analysis and results of a community needs assessment conducted in 2017 and 2018 that illuminates the current and hoped for landscape of digital library reuse assessment, its strengths, weaknesses and community applications.

In so far as the authors are aware, this is the first paper to examine with a broad lens the reuse assessment needs of the digital library community. The preliminary analysis and initial findings have not been previously published.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.