Search results

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.

The purpose of this study is to explore current practices, challenges and technological needs of different data repositories.

An online survey was designed for data repository managers, and contact information from the re3data, a data repository registry, was collected to disseminate the survey.

In total, 189 responses were received, including 47% discipline specific and 34% institutional data repositories. A total of 71% of the repositories reporting their software used bespoke technical frameworks, with DSpace, EPrint and Dataverse being commonly used by institutional repositories. Of repository managers, 32% reported tracking secondary data reuse while 50% would like to. Among data reuse metrics, citation counts were considered extremely important by the majority, followed by links to the data from other websites and download counts. Despite their perceived usefulness, repository managers struggle to track dataset citations. Most repository managers support dataset and metadata quality checks via librarians, subject specialists or information professionals. A lack of engagement from users and a lack of human resources are the top two challenges, and outreach is the most common motivator mentioned by repositories across all groups. Ensuring findable, accessible, interoperable and reusable (FAIR) data (49%), providing user support for research (36%) and developing best practices (29%) are the top three priorities for repository managers. The main recommendations for future repository systems are as follows: integration and interoperability between data and systems (30%), better research data management (RDM) tools (19%), tools that allow computation without downloading datasets (16%) and automated systems (16%).

This study identifies the current challenges and needs for improving data repository functionalities and user experiences.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0204

In developing and debating digital repositories, the digital library world has devoted more attention to their missions and roles in supporting access to and stewardship of academic research output than to discussing discipline, or domain, specific digital repositories. This is especially interesting, given that in social science these domain‐specific repositories have been in existence for many decades. The goal of this paper is to juxtapose these two kinds of repositories and to suggest ways that they can help build partnerships between themselves and with the research community.

The approach taken in the paper is based on the fundamental idea that all the parties involved share important goals, and that by working together these goals can be advanced successfully.

The key message is that by visualizing the role of repositories explicitly in the life cycle of the social science research enterprise, the ways that the partnerships work will be clear. These workings can be seen as a sequence of reciprocal information flows between parties to the process, triggers that signal that one party or another has a task to perform, and hand‐offs of information from one party to another that take place at crucial moments. This approach envisions both cooperation and specialization.

If followed, the recommendations offered in the paper will allow those implementing various kinds of repositories to work together with others in new ways, thus both enhancing the amount of information preserved and its value for the community.

This is one of the first times that the mutual possibilities of institutional and domain‐specific repositories have been brought together.

The purpose of this paper is to explore the breadth of the challenges and issues facing institutional repositories in academic libraries, based on a survey of academic librarians. Particularly, this study covers the challenges and barriers related to data management facing institutional repositories.

The study uses a survey method to identify the relative significance of major challenges facing institutional repositories across six dimensions, including: data, metadata, technological requirements, user needs, ethical concerns and administrative challenges.

The results of the survey reveal that academic librarians identify limited resources, including insufficient budget and staff, as the major factor preventing the development and/or deployment of services in institutional repositories. The study also highlights crucial challenges in different dimensions of institutional repositories, including the sheer amount of data, institutional support for metadata creation and the sensitivity of data.

This study is one of a few studies that comprehensively identified the variety of challenges that institutional repositories face in operating academic libraries with a focus on data management in institutional repositories. In this study, 37 types of challenges were identified in six dimensions of institutional repositories. More importantly, the significance of those challenges was assessed from the perspective of academic librarians involved in institutional repository services.

This study aims to highlight the challenges and opportunities of using GitHub as a data source in both research and programming education.

This study provides general overview of the challenges and opportunities faced while conducting empirical research using GitHub as a data source. The challenges and opportunities are framed using the input–process–output model of open-source software.

GitHub data accessed from the application programming interface (API) can have several limitations, which can be overcome by Web scraping and using external data repositories such as GHArchive and GHTorrent. There are also several idiosyncrasies about GitHub that researchers need to be aware of to be able to use the data effectively, which can represent an opportunity for research. The challenges and opportunities are summarized for the licenses, community, development process and product of free/libra and open-source software communities hosted on GitHub.

This study provides a summary of GitHub-related challenges and opportunities that researchers can leverage to improve their empirical research. Furthermore, this summary can be a valuable resource for instructors that plan to use GitHub as a data source in their data-focused programming courses.

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.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

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.