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The study aims to shed light on the current state of “Dataset repositories” indexed in Directory of Open Access Repositories (OpenDOAR).

From each repository/record information, the Open-Access Policies, Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH), year of creation and the number of data sets archived in the repositories were manually searched, documented and analyzed.

Developed countries like the United Kingdom and the USA are primarily involved in the development of institutional open-access repositories comprising significant components of OpenDOAR. The most extensively used software is DSpace. Most data set archives are OAI-PMH compliant but do not follow open-access rules. The study also highlights the sites’ embrace of Web 2.0 capabilities and discovers really simple syndication feeds and Atom integration. The use of social media has made its presence known. Furthermore, the study concludes that the number of data sets kept in repositories is insufficient, although the expansion of such repositories has been consistent over the years.

The work has the potential to benefit both researchers in general and policymakers in particular. Scholars interested in research data, data sharing and data reuse can learn about the present state of repositories that preserve data sets in OpenDOAR. At the same time, policymakers can develop recommendations and policies to assist in the construction and maintenance of repositories for data sets.

According to the literature, there have been numerous studies on open-access repositories and OpenDOAR internationally, but no research has focused on repositories preserving content-type data sets. As a result, the study attempts to uncover various characteristics of OpenDOAR Data set repositories.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.

The purpose of this study was to understand the landscape of Indian research data repositories (RDRs) indexed in the re3data.org. The study analysed the metadata elements of Indian RDRs to identify their disciplinary orientations, typology, standards adopted, foreign collaborations, etc. The study ascertained the current status of the Indian RDRs by visiting their respective websites and tried to identify and map the exact disciplinary orientation of each RDR.

The study used “content analysis” of the metadata elements extracted from re3data.org along with the information analysis of the respective websites of the registered RDRs.

The study identified that only 80% of the Indian RDRs listed by the re3data.org is currently active. Most of the Indian RDRs are hosted by the central and state governments and are almost equally distributed among Life Sciences, Natural Sciences and Social Sciences domains. The data provided by the re3data.org for the Indian RDRs are not complete and up-to-date.

The findings indicate the presence of a good number of inactive RDRs in the re3data.org. The study suggests using a revised version of the DFG subject classification scheme or considering a standard classification scheme for subject indexing.

To the best of the authors’ knowledge, this study is the first of its kind that critically analysed the metadata values extracted and moved further to identify the current status of Indian RDRs.

This study aims to identify the readiness of institutional repositories in Indonesia to implement digital humanities (DH) data curation. Data curation is a method of managing research data that maintains the data’s accuracy and makes it available for reuse. It requires controlled data management.

The study uses a qualitative approach. Data collection was carried out through a focus group discussion in September–October 2022, interviews and document analysis. The informants came from four institutions in Indonesia.

The findings reveal that the national research repository has implemented data curation, albeit not optimally. Within the case study, one of the university repositories diligently curates its humanities data and has established networks extending to various ASEAN countries. Both the national archive repository and the other university repository have implemented rudimentary data curation practices but have not prioritized them. In conclusion, the readiness of the national research repository and the university repository stand at the high-capacity stage, while the national archive repository and the other university repository are at the established and early stages of data curation, respectively.

This study examined only four repositories due to time constraints. Nonetheless, the four institutions were able to provide a comprehensive picture of their readiness for DH data curation management.

This study provides insight into strategies for developing DH data curation activities in institutional repositories. It also highlights the need for professional development for curators so they can devise and implement stronger ownership policies and data privacy to support a data-driven research agenda.

This study describes the preparations that must be considered by institutional repositories in the development of DH data curation activities.

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 study investigates differences and commonalities in data production, sharing and reuse across the widest range of disciplines yet and identifies types of improvements needed to promote data sharing and reuse.

The first authors of randomly selected publications from 2018 to 2019 in 20 Scopus disciplines were surveyed for their beliefs and experiences about data sharing and reuse.

From the 3,257 survey responses, data sharing and reuse are still increasing but not ubiquitous in any subject area and are more common among experienced researchers. Researchers with previous data reuse experience were more likely to share data than others. Types of data produced and systematic online data sharing varied substantially between subject areas. Although the use of institutional and journal-supported repositories for sharing data is increasing, personal websites are still frequently used. Combining multiple existing datasets to answer new research questions was the most common use. Proper documentation, openness and information on the usability of data continue to be important when searching for existing datasets. However, researchers in most disciplines struggled to find datasets to reuse. Researchers' feedback suggested 23 recommendations to promote data sharing and reuse, including improved data access and usability, formal data citations, new search features and cultural and policy-related disciplinary changes to increase awareness and acceptance.

This study is the first to explore data sharing and reuse practices across the full range of academic discipline types. It expands and updates previous data sharing surveys and suggests new areas of improvement in terms of policy, guidance and training programs.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2021-0423.

This paper aims to analyze open access (OA) scholarly publishing patterns as well as OA policies and mandates across European countries.

The study is based on a descriptive research approach using data from Web resources, directories and bibliographic and citation databases, namely, DOAJ, OpenDOAR, SCImago journal and Country Ranking portal, ROARMAP and Web of Science.

The findings indicate that the initiatives and measures in Europe that promote OA are adequate. OA journals and digital repositories have progressively increased over the past two decades. Of the total journals (n = 25,231) published worldwide and indexed in Scopus, 53% are published in European countries, with 23.7% being OA journals. In total, 34% of the OA repositories (n = 5,714) are in European countries. The proportion of OA journal papers has grown significantly in all European countries, with a 14.3% annual growth rate. The average proportion of OA publications in European countries is significantly higher (39.07%) than the world average (30.16%), with a clear inclination for making research literature openly accessible via the green OA route (79.41%) compared to the gold OA route (52.30%). Most European research funders and institutions have required researchers to make OA available for their research findings, either by publishing them in OA journals or depositing accepted manuscripts in repositories.

The study analyzed OA trends in Europe; other continents and countries were not included in the analysis. The study only described OA policies and mandates; the extent to which the OA policies and mandates were implemented was not studied. However, the results of the study may be helpful to policymakers, funders, research institutions and universities in other countries in adopting and implementing OA policies and mandates.

To the best of the authors’ knowledge, the study is the first that used multiple data sources for investigating different facets of OA publishing in European countries, including OA journals, digital repositories, research output, mandates and policies for publicly funded research. The findings will be helpful for researchers and policymakers interested in promoting OA adoption among researchers worldwide.

This study aims to analyze Open Access (OA) publishing trends and policy perspectives in India. Different aspects, such as the growth of OA journals digital repositories, the proportion of OA availability to research literature and the status of OA mandates and policies are studied.

Data for analyzing OA trends were gathered from multiple data sources, including Directory of Open Access Journals (DOAJ), OpenDOAR, SCImago and Web of Science (WoS) databases. DOAJ and OpenDOAR were used for extracting OA journals and digital repository data. SCImago Journal and Country ranking portal and WoS database were used to obtain Indian publication data for assessing the proportion of OA to research literature. ROARMAP was used to study OA mandates and policies adopted by universities, research institutions and research funders in India. OA mandates and policies of major regulatory bodies and funding agencies were also reviewed using secondary sources of information and related websites.

India ranks number 15 and 17 globally for OA journals and OA repositories, with 317 journals and 98 repositories. Although India’s proportion to OA publications is 23% (7% below the world average of 30%), the annual growth rate of OA publications is around 18%. Although the governing bodies and institutions have made efforts to mandate researchers to adopt OA publishing and self-archiving, its implementation is quite low among Indian researchers, as only three institutions (out of 18 listed in the ROARMAP) are defined the embargo period. Funding agencies in India do not provide financial assistance to authors for the payment of Article Processing Charges despite mandates that research is deposited in OA repositories. India lacks a national OA policy but plans to implement a “one nation one subscription” formula to provide OA to scientific literature to all its citizens.

The study has certain limitations. Because much of India’s research output is published in local journals that are not indexed in WoS, the study recommends conducting further analyses of publications using Scopus and other databases to understand the country’s OA publishing proportion better. A further study based on feedback from different stakeholders through a survey may be conducted for formulating a national OA policy.

The study is the first that used multiple data sources for investigating different facets of OA publishing in India, including OA journals, digital repositories, OA research output and OA mandates and policies for publicly funded research. The findings will be helpful for researchers and policymakers interested in promoting OA adoption among researchers worldwide.

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.

The purpose of the paper is to propose a semantic model for describing open source software (OSS) in a machine–human understandable format. The model is extracted to support source code reusing and revising as the two primary targets of OSS through a systematic review of related documents.

Conducting a systematic review, all the software reusing criteria are identified and introduced to the web of data by an ontology for OSS (O4OSS). The software semantic model introduced in this paper explores OSS through triple expressions in which the O4OSS properties are predicates.

This model improves the quality of web data by describing software in a structured machine–human readable profile, which is linked to the related data that was previously published on the web. Evaluating the OSS semantic model is accomplished through comparing it with previous approaches, comparing the software structured metadata with profile index of software in some well-known repositories, calculating the software retrieval rank and surveying domain experts.

Considering context-specific information and authority levels, the proposed software model would be applicable to any open and close software. Using this model to publish software provides an infrastructure of connected meaningful data and helps developers overcome some specific challenges. By navigating software data, many questions which can be answered only through reading multiple documents can be automatically responded on the web of data.