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Open Access
Article
Publication date: 20 February 2024

Alenka Kavčič Čolić and Andreja Hari

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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

Originality/value

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.

Details

Digital Library Perspectives, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2059-5816

Keywords

Article
Publication date: 11 September 2023

Ying Gao, Qiang Zhang, Xiaoran Wang, Yanmei Huang, Fanshuang Meng and Wan Tao

Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between…

Abstract

Purpose

Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between resources. Therefore, this study aims to propose a multidimensional knowledge discovery solution for Tang tomb mural cultural relic resources.

Design/methodology/approach

Taking the Tang tomb murals collected by the Shaanxi History Museum as an example, based on clarifying the relevant concepts of Tang tomb mural resources and considering both dynamic and static dimensions, a top-down approach was adopted to first construct an ontology model of Tang tomb mural type cultural relics resources. Then, the actual case data was imported into the Neo4J graph database according to the defined pattern hierarchy to complete the static organization of knowledge, and presented in a multimodal form in knowledge reasoning and retrieval. In addition, geographic information system (GIS) technology is used to dynamically display the spatiotemporal distribution of Tang tomb mural resources, and the distribution trend is analysed from a digital humanistic perspective.

Findings

The multi-dimensional knowledge discovery of Tang tomb mural cultural relics resources can help establish the correlation and spatiotemporal relationship between resources, providing support for semantic retrieval and navigation, knowledge discovery and visualization and so on.

Originality/value

This study takes the murals in the collection of the Shaanxi History Museum as an example, revealing potential knowledge associations in a static and intelligent way, achieving knowledge discovery and management of Tang tomb murals, and dynamically presents the spatial distribution of Tang tomb murals through GIS technology, meeting the knowledge presentation needs of different users and opening up new ideas for the study of Tang tomb murals.

Details

The Electronic Library , vol. 42 no. 1
Type: Research Article
ISSN: 0264-0473

Keywords

Open Access
Article
Publication date: 31 July 2023

Sara Lafia, David A. Bleckley and J. Trent Alexander

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Journal of Documentation, vol. 79 no. 7
Type: Research Article
ISSN: 0022-0418

Keywords

Open Access
Article
Publication date: 23 May 2023

Kimmo Kettunen, Heikki Keskustalo, Sanna Kumpulainen, Tuula Pääkkönen and Juha Rautiainen

This study aims to identify user perception of different qualities of optical character recognition (OCR) in texts. The purpose of this paper is to study the effect of different…

Abstract

Purpose

This study aims to identify user perception of different qualities of optical character recognition (OCR) in texts. The purpose of this paper is to study the effect of different quality OCR on users' subjective perception through an interactive information retrieval task with a collection of one digitized historical Finnish newspaper.

Design/methodology/approach

This study is based on the simulated work task model used in interactive information retrieval. Thirty-two users made searches to an article collection of Finnish newspaper Uusi Suometar 1869–1918 which consists of ca. 1.45 million autosegmented articles. The article search database had two versions of each article with different quality OCR. Each user performed six pre-formulated and six self-formulated short queries and evaluated subjectively the top 10 results using a graded relevance scale of 0–3. Users were not informed about the OCR quality differences of the otherwise identical articles.

Findings

The main result of the study is that improved OCR quality affects subjective user perception of historical newspaper articles positively: higher relevance scores are given to better-quality texts.

Originality/value

To the best of the authors’ knowledge, this simulated interactive work task experiment is the first one showing empirically that users' subjective relevance assessments are affected by a change in the quality of an optically read text.

Details

Journal of Documentation, vol. 79 no. 7
Type: Research Article
ISSN: 0022-0418

Keywords

Article
Publication date: 14 November 2023

Shaodan Sun, Jun Deng and Xugong Qin

This paper aims to amplify the retrieval and utilization of historical newspapers through the application of semantic organization, all from the vantage point of a fine-grained…

Abstract

Purpose

This paper aims to amplify the retrieval and utilization of historical newspapers through the application of semantic organization, all from the vantage point of a fine-grained knowledge element perspective. This endeavor seeks to unlock the latent value embedded within newspaper contents while simultaneously furnishing invaluable guidance within methodological paradigms for research in the humanities domain.

Design/methodology/approach

According to the semantic organization process and knowledge element concept, this study proposes a holistic framework, including four pivotal stages: knowledge element description, extraction, association and application. Initially, a semantic description model dedicated to knowledge elements is devised. Subsequently, harnessing the advanced deep learning techniques, the study delves into the realm of entity recognition and relationship extraction. These techniques are instrumental in identifying entities within the historical newspaper contents and capturing the interdependencies that exist among them. Finally, an online platform based on Flask is developed to enable the recognition of entities and relationships within historical newspapers.

Findings

This article utilized the Shengjing Times·Changchun Compilation as the datasets for describing, extracting, associating and applying newspapers contents. Regarding knowledge element extraction, the BERT + BS consistently outperforms Bi-LSTM, CRF++ and even BERT in terms of Recall and F1 scores, making it a favorable choice for entity recognition in this context. Particularly noteworthy is the Bi-LSTM-Pro model, which stands out with the highest scores across all metrics, notably achieving an exceptional F1 score in knowledge element relationship recognition.

Originality/value

Historical newspapers transcend their status as mere artifacts, evolving into invaluable reservoirs safeguarding the societal and historical memory. Through semantic organization from a fine-grained knowledge element perspective, it can facilitate semantic retrieval, semantic association, information visualization and knowledge discovery services for historical newspapers. In practice, it can empower researchers to unearth profound insights within the historical and cultural context, broadening the landscape of digital humanities research and practical applications.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 10 April 2023

Evagelos Varthis and Marios Poulos

This study aims to present metaGraphos, a crowdsourcing system that aids in the transcription and semantic enhancement of scanned documents by using a pool of volunteers or people…

Abstract

Purpose

This study aims to present metaGraphos, a crowdsourcing system that aids in the transcription and semantic enhancement of scanned documents by using a pool of volunteers or people willing to participate in exchange for a financial reward.

Design/methodology/approach

The metaGraphos can be used in circumstances where optical character recognition fails to produce satisfactory results, semantic tagging or assigning thematic headings to texts is considered necessary or even when ground-truth data has to be collected in raw form.

Findings

The system automatically provides a Web-based interface comprising a static HTML page and JavaScript code that displays the scanned images of the document, coupled with the corresponding incomplete texts side by side, allowing users to correct or complete the texts in parallel.

Social implications

By assisting the parallel transcription and the semantic enhancement of difficult scanned documents, the system further reveals the hidden cultural wealth and aids in knowledge dissemination, a fact that contributes significantly to the academic-scientific dialog and feedback.

Originality/value

Individual researchers, libraries and organizations in general may benefit from the system because it is cost-effective, practical and simple to set up client–server architecture that provides a reliable way to transcribe texts or revise transcriptions on a large scale.

Details

Collection and Curation, vol. 42 no. 4
Type: Research Article
ISSN: 2514-9326

Keywords

Content available
Article
Publication date: 13 November 2023

Sheuli Paul

This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this…

Abstract

Purpose

This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.

Design/methodology/approach

This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.

Findings

Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.

Research limitations/implications

Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.

Practical implications

A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.

Social implications

Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.

Originality/value

The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.

Article
Publication date: 27 February 2024

Alan S. Marcus, Katherine A. Griffith and Francis Gary Powers Jr

In this article, we use the film Bridge of Spies – which depicts the case of U-2 spy pilot Francis Gary Powers – and relevant primary sources, particularly Powers' letters from…

Abstract

Purpose

In this article, we use the film Bridge of Spies – which depicts the case of U-2 spy pilot Francis Gary Powers – and relevant primary sources, particularly Powers' letters from prison, to provide teachers with a case that can engage students with the complexity of the Cold War. Understanding USA–Russia relations is as important today as ever as we watch the tragedy unfold in Ukraine. Using primary sources to reflect on the Cold War can help secondary students understand the historical context of the war in Ukraine as well as how to evaluate and critique sources of information about the war.

Design/methodology/approach

The film and personal letters provide insights often not available or obvious when we focus on the political or military history of an event or time period. The Cold War is frequently defined by the rhetoric of the USA and Union of Soviet Socialist Republics (USSR) governments – but everyday people and citizens had a wider range of views and experiences. The film and letters bring out the humanity of the Cold War.

Findings

This article supports secondary teachers in incorporating film and primary sources as teaching tools to study the Cold War while more broadly thinking about these sources as ways to understand the past. The letters used, including those from U-2 spy pilot Francis Gary Powers, help us understand his time in a Soviet prison as well as the behind-the-scenes work to free him as part of a prisoner exchange.

Originality/value

The U-2 Incident and other events of the Cold War provide important context for understanding the Cold War-like tensions between the USA and Russia today. The distrust between these countries has a long history. However, documents like the film and letters discussed here show that there is much more to the bluster of political leaders and the military chess game. There is an important human element to these events and an impact on individuals who are much more than pawns in international diplomacy.

Details

Social Studies Research and Practice, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1933-5415

Keywords

Article
Publication date: 25 January 2024

Yaolin Zhou, Zhaoyang Zhang, Xiaoyu Wang, Quanzheng Sheng and Rongying Zhao

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 10 April 2023

Santosh Abaji Kharat, Shubhada Nagarkar and Bhausaheb Panage

The purpose of this research is to introduce the Layar augmented reality (AR) application among library users and to understand the user’s satisfaction towards the information…

Abstract

Purpose

The purpose of this research is to introduce the Layar augmented reality (AR) application among library users and to understand the user’s satisfaction towards the information services provided by the Layar application with the help of the structural equation model (SEM).

Design/methodology/approach

According to Thomas (2016), action research is mainly undertaken to develop new skills or new approaches and to solve issues and problems with direct application to any applied setting. The present study helps to develop new skills and approaches to repackaging information using AR applications. Researchers have identified the question of what could be done to increase the awareness of Layar AR applications among students. Because the Layar augmented application is one of the new tools for an academic library to repackage information for mass accessibility. Therefore, in the present action research approach, researchers encompass two activities action and research. Researchers have used participatory action research methods by collecting data from 17 MBA institute libraries affiliated with Savitribai Phule Pune University. Researchers have systematically used the Layar application in the library by obtaining permission from each higher authority. Researchers have designed a Layar satisfaction model using the SEM with AMOS and SPSS.

Findings

The researcher found that the relationship between experience, performance and service quality is positively significant. The user’s experience is satisfied with the Layar application, but users are not satisfied with the service quality and performance of the Layar application.

Research limitations/implications

This study tested Layar AR application in MBA libraries affiliated with Savitribai Phule Pune University in the Pune and Pimpri Chinchwad areas.

Practical implications

The Layar app helps the academic library to convert selected print collections into an AR feel for library users. This is an additional method of providing information services to users through mobile devices. A total of 157 students downloaded the Layar application from their handsets and provided feedback through a questionnaire. Researchers have found that the relationships between users and Layar experience, performance and service quality are positively significant. The user experience is satisfied with the Layar application, but users are not satisfied with the service quality and performance of the Layar application.

Originality/value

This study examined the performance, service quality and user experience of Layar applications. Structural equation and Modelling theories were used to examine the relationship between user satisfaction and information services using the Layar application.

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