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The purpose of this paper is to report a study of how research literature addresses researchers' attitudes toward data repository use. In particular, the authors are interested in how the term data sharing is defined, how data repository use is reported and whether there is need for greater clarity and specificity of terminology.

To study how the literature addresses researcher data repository use, relevant studies were identified by searching Library Information Science and Technology Abstracts, Library and Information Science Source, Thomas Reuters' Web of Science Core Collection and Scopus. A total of 62 studies were identified for inclusion in this meta-evaluation.

The study shows a need for greater clarity and consistency in the use of the term data sharing in future studies to better understand the phenomenon and allow for cross-study comparisons. Furthermore, most studies did not address data repository use specifically. In most analyzed studies, it was not possible to segregate results relating to sharing via public data repositories from other types of sharing. When sharing in public repositories was mentioned, the prevalence of repository use varied significantly.

Researchers' data sharing is of great interest to library and information science research and practice to inform academic libraries that are implementing data services to support these researchers. This study explores how the literature approaches this issue, especially the use of data repositories, the use of which is strongly encouraged. This paper identifies the potential for additional study focused on this area.

The purpose of this paper is to survey how research data are governed at repositories in Japan by deductively establishing a governance typology based on the concept of openness in the context of knowledge commons and empirically assessing the conformity of repositories to each type.

The fuzzy-set ideal type analysis (FSITA) was adopted. For data collection, a manual assessment was conducted with all Japanese research data repositories registered on re3data.org.

The typology constructed in this paper consists of three dimensions: openness to resources (here equal to research data), openness to a community and openness to infrastructure provision. This paper found that there is no case where all dimensions are open, and there are several cases where the resources are closed despite research data repositories being positioned as a basis for open science in Japanese science and technology policy.

This is likely the first construction of the typology and application of FSITA to the study of research data governance based on knowledge commons. The findings of this paper provide practitioners insight into how to govern research data at repositories. The typology serves as a first step for future research on knowledge commons, for example, as a criterion of case selection in conducting in-depth case studies.

The study aims to investigate the utilisation of open research data repositories (RDRs) for storing and sharing research data in higher learning institutions (HLIs) in Tanzania.

A survey research design was employed to collect data from postgraduate students at the Nelson Mandela African Institution of Science and Technology (NM-AIST) in Arusha, Tanzania. The data were collected and analysed quantitatively and qualitatively. A census sampling technique was employed to select the sample size for this study. The quantitative data were analysed using the Statistical Package for the Social Sciences (SPSS), whilst the qualitative data were analysed thematically.

Less than half of the respondents were aware of and were using open RDRs, including Zenodo, DataVerse, Dryad, OMERO, GitHub and Mendeley data repositories. More than half of the respondents were not willing to share research data and cited a lack of ownership after storing their research data in most of the open RDRs and data security. HILs need to conduct training on using trusted repositories and motivate postgraduate students to utilise open repositories (ORs). The challenges for underutilisation of open RDRs were a lack of policies governing the storage and sharing of research data and grant constraints.

Research data storage and sharing are of great interest to researchers in HILs to inform them to implement open RDRs to support these researchers. Open RDRs increase visibility within HILs and reduce research data loss, and research works will be cited and used publicly. This paper identifies the potential for additional studies focussed on this area.

This study aims to evaluate faculty research repositories used in higher education institutions, their different levels and functions with regard to research information management. This is revealed through the selected studies reviewed.

A systematic literature search of journal article studies on research repositories in higher education institutions was carried out on several databases, namely, Ebscohost, Emerald Insight, Science Direct, Sage, Google Scholar, SA e-Publications and citation databases such as Scopus and Web of Science. The systematic review was conducted in accordance with the preferred reporting items for systematic reviews and meta-analyses guidelines. The time frame for the analysis was 2015 to 2021.

The findings are presented on the motives for developing faculty research repositories the services provided and benefits derived from faculty research repositories and what is the utilization of faculty research repositories.

The results show that the development of research repositories at the faculty level enhances sharing, analysis, evaluation and preservation of scholarly research produced.

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.

Several online services offer functionalities to access information from “big research graphs” (e.g. Google Scholar, OpenAIRE, Microsoft Academic Graph), which correlate scholarly/scientific communication entities such as publications, authors, datasets, organizations, projects, funders, etc. Depending on the target users, access can vary from search and browse content to the consumption of statistics for monitoring and provision of feedback. Such graphs are populated over time as aggregations of multiple sources and therefore suffer from major entity-duplication problems. Although deduplication of graphs is a known and actual problem, existing solutions are dedicated to specific scenarios, operate on flat collections, local topology-drive challenges and cannot therefore be re-used in other contexts.

This work presents GDup, an integrated, scalable, general-purpose system that can be customized to address deduplication over arbitrary large information graphs. The paper presents its high-level architecture, its implementation as a service used within the OpenAIRE infrastructure system and reports numbers of real-case experiments.

GDup provides the functionalities required to deliver a fully-fledged entity deduplication workflow over a generic input graph. The system offers out-of-the-box Ground Truth management, acquisition of feedback from data curators and algorithms for identifying and merging duplicates, to obtain an output disambiguated graph.

To our knowledge GDup is the only system in the literature that offers an integrated and general-purpose solution for the deduplication graphs, while targeting big data scalability issues. GDup is today one of the key modules of the OpenAIRE infrastructure production system, which monitors Open Science trends on behalf of the European Commission, National funders and institutions.

A major development in academic libraries in the last decade has been recognition of the need to support research data management (RDM). The purpose of this paper is to capture how library research data services (RDS) have developed and to assess the impact of this on the nature of academic libraries.

Questionnaire responses from libraries in Australia, Canada, Germany, Ireland, the Netherlands, New Zealand, the UK and USA from 2018 are compared to a previous data set from 2014.

The evidence supports a picture of the spread of RDS, especially advisory ones. However, future ambitions do not seem to have seen much evolution. There is limited evidence of organisational change and skills shortages remain. Most service development can be explained as the extension of traditional library services to research data. Yet there remains the potential for transformational impacts, when combined with the demands implied by other new services such as around text and data mining, bibliometrics and artificial intelligence. A revised maturity model is presented that summarises typical stages of development of services, structures and skills.

The research models show how RDS are developing. It also reflects on the extent to which RDM represents a transformation of the role of academic libraries.

Practitioners working in the RDM arena can benchmark their current practices and future plans against wider patterns.

The study offers a clear picture of the evolution of research data services internationally and proposes a maturity model to capture typical stages of development. It contributes to the wider discussion of how the nature of academic libraries are changing.

The purpose of this paper is to present a case study of work performed at the London School of Hygiene and Tropical Medicine to set-up a Research Data Management Service and tailor it to the needs of health researchers.

The paper describes the motivations for establishing the RDM Service and outlines the three objectives that were set to improve data management practice within the institution. Each of the objectives are explored in turn, stating how they were addressed.

A university with limited resources can operate a RDM Service that pro-actively supports researchers wishing to manage research data by monitoring evolving support needs, identifying common trends and developing resources that will reduce the time investment needed. The institution-wide survey identified a need for guidance on developing data documentation and archiving research data following project completion. Analysis of ongoing support requests identifies a need for guidance on data management plans and complying with journal sharing requirements.

The paper provides a case study of a single institution. The results may not be generally applicable to universities that support other disciplines.

The case study may be helpful in helping other universities to establish an RDM Service using limited resources.

The paper outlines how the evolving data management needs of public health researchers can be identified and a strategy that can be adopted by an RDM Service to efficiently address these requirements.

The purpose of this paper is to report on how library and information science (LIS) as a field operationalizes the concept of organizational sustainability for managing digital resources, projects and infrastructures such as digital libraries and repositories over time. It introduces a nine dimensional framework for organizational sustainability in the digital cultural heritage community.

Content analysis of publications from three LIS databases (2000–2015).

Comparing the articles to the nine dimension framework shows that most LIS articles discuss technology, financial or management dimensions. Fewer articles describe disaster planning, assessment or policy dimensions.

Three LIS databases might not include all relevant journals, conferences, white papers and other materials. The data set also did not include books; library management textbooks might include useful material on organizational sustainability. Claims about the prevalence of themes are subject to methodological limits of content analysis.

Organizations that steward digital collections need to be clear about what they mean when they are referring to organizational sustainability so that they can make appropriate decisions for future-proofing their collections. The analysis would also suggest for a greater need to consider the full range of dimensions of organizational sustainability.

By introducing a new nine dimensional framework of organizational sustainability the authors hope to promote more and better conversations within the LIS community about organizational sustainability. The authors hope these conversations will lead to productive action and improvements in the arrangements of people and work necessary to keep digital projects and services going over time, given ongoing challenges.

Medical research requires biological material and data collected through biobanks in reliable processes with quality assurance. Medical studies based on data with unknown or questionable quality are useless or even dangerous, as evidenced by recent examples of withdrawn studies. Medical data sets consist of highly sensitive personal data, which has to be protected carefully and is available for research only after the approval of ethics committees. The purpose of this research is to propose an architecture to support researchers to efficiently and effectively identify relevant collections of material and data with documented quality for their research projects while observing strict privacy rules.

Following a design science approach, this paper develops a conceptual model for capturing and relating metadata of medical data in biobanks to support medical research.

This study describes the landscape of biobanks as federated medical data lakes such as the collections of samples and their annotations in the European federation of biobanks (Biobanking and Biomolecular Resources Research Infrastructure – European Research Infrastructure Consortium, BBMRI-ERIC) and develops a conceptual model capturing schema information with quality annotation. This paper discusses the quality dimensions for data sets for medical research in-depth and proposes representations of both the metadata and data quality documentation with the aim to support researchers to effectively and efficiently identify suitable data sets for medical studies.

This novel conceptual model for metadata for medical data lakes has a unique focus on the high privacy requirements of the data sets contained in medical data lakes and also stands out in the detailed representation of data quality and metadata quality of medical data sets.