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Data sharing is increasingly being recognized as an essential component of scholarly research and publishing. Sharing data improves results and propels research and discovery forward. Given the importance of data sharing, the purpose of the study is to unveil the present scenario of research data repositories (RDR) and sheds light on strategies and tactics followed by different countries for efficient organization and optimal use of scientific literature.

The data for the study is collected from registry of RDR (re3data registry) (re3data.org), which covers RDR from different academic disciplines and provides filtration options “Search” and “Browse” to access the repositories. Using these filtration options, the researchers collected metadata of repositories i.e. country wise contribution, content-type data, repository language interface, software usage, metadata standards and data access type. Furthermore, the data was exported to Google Sheets for analysis and visualization.

The re3data registry holds a rich and diverse collection of data repositories from the majority of countries all over the world. It is revealed that English is the dominant language, and the most widely used software for the creation of data repositories are “DataVerse”, followed by “Dspace” and “MySQL”. The most frequently used metadata standards are “Dublin Core” and “Datacite metadata schema”. The majority of repositories are open, with more than half of the repositories being “disciplinary” in nature, and the most significant data sources include “scientific and statistical data” followed by “standard office documents”.

The main limitation of the study is that the findings are based on the data collected through a single registry of repositories, and only a few characteristic features were investigated.

The study will benefit all countries with a small number of data repositories or no repositories at all, with tools and techniques used by the top repositories to ensure long-term storage and accessibility to research data. In addition to this, the study provides a global overview of RDR and its characteristic features.

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.

The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale.

The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface.

The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool.

Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections.

As part of the EFOP-3.3.3-VEKOP-16–2016-00001 “Museum and Library Development for All” project, a national representative digital literacy survey was conducted in Hungary's public libraries at the end of 2019. The aim of the present study is to provide a deeper analysis of the data collected during the survey to answer the question of the role of gender and age in the development of digital skills amongst librarians working in public libraries. This study was designed to answer the following four research questions: Are there levels of proficiency defined by DigComp 2.1 that are more specific to men or more specific to women? Are there areas of competence and competences that are clearly perceived as stronger or weaker for men or women? Are there areas of competence that are clearly influenced by age and others that are not or only moderately influenced by age? Which competences are clearly age-related, and which are not or only slightly affected by age?

The main target group of the study were library professionals working in county libraries. The survey, based on the DigComp 2.1 (Gomez et al., 2017) framework, was conducted using an online questionnaire in the form of a self-assessment and explored four levels of digital literacy. A 30-question questionnaire was completed by 1,868 respondents. The sampling procedure was essentially stratified sampling. The large number of respondents and the sampling procedure combined with the representativeness of the sample meant that the results of the survey can be considered as generalisable to the whole Hungarian public library sector.

Of the five competency areas assessed by the DigComp framework, librarians were found to be most competent in information and data literacy, and least competent in content development, according to the proportion of those with basic skills. 32 percent of women and 22 percent of men working in libraries rated their digital skills as basic, and both groups were weak or less weak in the same skills, with a few exceptions. At the intermediate level, there is a predominance of women. In the information and communication competency areas and in the content development and integrating and re-elaborating digital content in the content creation area, a high proportion of women consider their digital skills to be medium. Relatively few men rate their own competence in these areas as average. They are most likely to have advanced and highly specialised skills. The advanced level in DigComp2.1 implies, in addition to strong digital skills, the willingness and ability to help others, while the highly specialised level requires innovative and creative use of digital technology and knowledge transfer. These top two skill levels are more common amongst men. 34 per cent of men and 27 per cent of women have advanced skills, while 13 per cent of men and 6 per cent of women have highly specialised’s level. The age of librarians has only a minimal influence in certain areas of competence and for certain competences. Skills in the information and data literacy competency area are less age sensitive. For the data management competency, which requires more technological skills, a stronger correlation between age and skill levels is observed, especially for basic and highly specialised skills. In the communication competence area, the youngest age group of librarians has the highest percentage of advanced and the lowest percentage of basic level. The proportion of advanced learners decreases steadily as age groups progress and the proportion of basic learners increases at a similar steady rate. The effect of age on the content creation is much more modest than expected. Age clearly has an impact on the safety competence area. As age increases, the proportion of those at advanced level decreases and the proportion at basic level increases. Age also has a significant effect on the problem-solving competence area. One in two librarians in the 50 and 60s have only basic level skills, compared to one in four in the youngest age group and one in three in the 40s.

Using the DigComp 2.1 framework, a digital competence survey of a whole professional group of library professionals working in public libraries in Hungary was carried out. The study provides new insights into the impact of gender and age as variables on digital competence.

The purpose of the paper is to analyze how the Neo-documentalist movement, initiated in 1996 by Michael Buckland, Boyd Rayward and Niels Lund, has evolved in its 27 years history, how the choice of documentation as name of the new program in Tromsø has made a difference in the LIS field and how different documentation scholars around the world has participated and approached the movement until now.

The paper has approached the “Neo-documentalist movement” in a historical perspective from 1996 to 2023 discussing what difference does the choice of a concept make, when the concept of documentation is chosen instead of information in the name of a program and for the general discussion of the object of an academic field like Library and Information Science.

The analysis shows that it did make a difference to choose the concept of documentation as name of the program in Tromsø and the Neo-documentalist movement contributed to a new focus and discussion of the informative objects, the documents and their creation, not only in Tromsø, but in different parts of the world across linguistic borders.

The paper is original by the fact that it is the first time that the neo documentalist movement has been reviewed on a global scale across linguistic barriers. It has value by a discussion of the ways in which a choice of concept matter in relation to defining a field and the research agenda.

The purpose of this study is to examine the quality of information in articles in the online encyclopedia, Wikipedia, as perceived by readers and content contributors. This study explored several dimensions and characteristics of information presented in Wikipedia by identifying new emerging dimensions in terms of readers’ perceptions of the quality of online information.

Two rounds of online surveys were conducted using a mixed-method approach. In the first survey, the authors conducted content analysis on 197 participants, and in the second survey, the authors conducted factor analysis on 107 study participants. The authors used Qualtrics Panel Services to recruit individuals who read and/or edited the English version of Wikipedia articles and resided in the United States.

The mixed-method approach employed in this study to explore the quality of online information had three core components: users’ perceptions of information quality, content analysis, and exploratory factor analysis of the perceived information quality structure. The study found a new information quality category, social aspect quality. Dimensions include fun, goodness, empowering and user generated.

The results demonstrate the emergence of novel quality attributes for information quality presented online, particularly in social media. Moreover, this study is one of the rare studies to employ a mixed-method approach that offers diverse but reliable perspectives on information quality as perceived by everyday users of Wikipedia.

Despite the widespread studies on the attitudes about OA, there exists little comparative evidence about the opinions of author and non-author parties at a global level in a social context. To bridge the gap, this study first investigated the opinions of the users who posted at least one tweet about OA in 2019. Then, it zoomed in to explore the views of the OA-interested tweeters, i.e. the users who have posted five or more tweets about OA.

Using a content analysis method, with an opinion-mining approach, this study examined a sample of 9,268 OA-related tweets posted by 5,227 tweeters in 2019. The sentiments were analyzed using SentiStrength. A threshold of at least five tweets was set to identify the OA-interested tweeters.

Academics and scholars, library and information professionals, and journals and publishers were the main OA-interested tweeters, implying that OA debates have not been widely propagated from its traditional audience to the general public. Despite an overall positive attitude, the tweeters showed negative perspectives about the gold and hybrid models, validity and quality, and costs and funds. The negativity depended on the OA features tweeted, the tweeters' occupations and gender, as well as the trends.

The low societal impact of the OA debates calls for solutions to attract the public's attention and to exploit their potential to achieve the OA ideals. The OA stakeholders' divergence necessitates finding solutions to remedy the pitfalls. It also underlines the need for scrutiny into social layers when studying society's opinions and behaviors in a social network.

This is the first study in estimating the extent of the societal impact of OA debates, comparing the social OA stakeholders' opinions and their dependence on the OA features tweeted, the tweeter roles and gender and the tweet trending status.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2022-0502

Technological change drives transformation in most sectors of the economy. Industry 4.0 technologies have been applied at different stages of a building’s lifecycle. However, limited studies exist on their application in real estate facilities management (REFM). This study aims to assess the existing knowledge on the topic to suggest further research directions.

Scopus-indexed literature from 2013 to 2023 was examined and visualised using VOSviewer software to output quantitative (descriptive) results. Content analysis was used to complement the quantitative findings.

Findings indicated a concentration of research in China, Norway and Italy. The knowledge areas included three clusters: lifecycle integration and management, data curation and management and organisational and management capabilities. The benefits, challenges and support strategies were highlighted.

More collaboration is needed across countries and territories on technology integration in REFM. Future research using alternative methodologies is recommended, with a focus on adopting and non-adopting REFM organisations. Further, implications for facility managers, employees, technology suppliers or vendors, training, organisations and management exist.

Further, implications for facility managers, employees, technology suppliers or vendors, training, organisations and management exist.

The study reveals the knowledge base on technology use in REFM. It adds to the evidence base on innovation and technology adoption in REFM.

The implementation of income-generating still faces problems, such as the lack of well-established internal control and differences in implementation in each unit. This study aims to analyze internal controls, financial viability (FV) and leadership qualities (LQ) in the implementation of income-generating in Indonesian higher education.

This study is quantitative and uses a causal approach. The population of this research is the unit leader and the person in charge of the activity that generates income, with a total sample of 111 people. The sampling technique used is simple random sampling. Data were analyzed using moderation regression analysis (MRA) with the WrapPLS (partial least square) analysis tool.

The results indicate that internal control and FV significantly affect the management of income-generating. The existence of LQ as a moderating variable can moderate and weaken the influence of internal controls and FV on the management of income-generating. In this finding, the unit leader and the person in charge of activities that generate income in higher education need to improve managerial skills, including ethics, uphold integrity, clear vision, quick adaption, honestly and trust so that the management of income-generating can achieve higher education goals more effectively and efficiently.

This research shows that universities need to create a good environment to build an ecosystem that can improve the management. The university encourages the good management by strengthening the leadership. However, the research has a limitation: the study was only conducted in one state university.

The implementation of income generation in the public financial management system of legal entity universities requires accountability for sources of income so that internal controls and the role of finance are needed to ensure the continuity of universities.