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Triggered by the advancement of information and communications technology, open access repositories (a variant of digital libraries) is one of the important changes impacting library services. In the context of openness to a wider community to access free resources, Wawasan Open University Library initiated a research project to build open access repositories on open educational resources. Open educational resources (OER) is an area of a multifaceted open movement in education. The purpose of this paper is to show how two web portal repositories on OER materials were developed adopting a Japanese open source software, called WEKO.

The design approach is based on a pull to push strategy whereby metadata of scholarly open access materials kept within the institution and network communities’ digital databases were harvested using the Open Archives Initiatives Protocol for Metadata Harvesting method into another open knowledge platform for discovery by other users.

Positive results emanating from the university open access repositories development showed how it strengthen the role of the librarian as manager of institutional assets and successfully making the content freely available from this open knowledge platform for reuse in learning and teaching.

Developing further programmes to encourage, influence faculty members and prospective stakeholders to use and contribute content to the valuable repositories is indeed a challenging task.

This paper provides insight for academic libraries on how open access repositories development and metadata analysis can enhance new professional challenges for information professionals in the field of data management, data quality and intricacies of supporting data repositories and build new open models of collaboration across institutions and libraries. This paper also describes future collaboration work with institutions in sharing their open access resources.

Ghanaian public universities have fully embraced the concept of open access. This is evident in the increasing numbers of institutional repositories (IRs) by universities in Ghana. However, to ensure the sustainability of these IRs, it is vital the current IR infrastructure is capable of responding to current and future demands. The purpose of this study is to investigate the sustainability of the current IR infrastructure of public universities in Ghana.

The convergent parallel mixed methods design was adopted. A total of 830 respondents comprising IR managers, library staff (digitisation and e-resources units), postgraduate students, lecturers and university librarians from five public universities in Ghana were sampled for this study. A questionnaire and a semi-structured interview guide were the main instruments used for data collection.

The findings of this study revealed that the IR infrastructure of public universities in Ghana is robust and has the capacity to expand when the need arises. However, funding, cost of internet connectivity, personnel and erratic power supply were identified as major challenges confronting IRs in Ghana.

This study highlighted Ghana's existing IR infrastructure situation. This study is a significant contribution to the literature from West Africa because there is not much research on IR infrastructure from this part of the world.

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 purpose of this study is to promote mobile-responsive and agile institutional open-access digital repositories. This paper provided an x-ray of the tilted research approach to open access (OA). Most underlying causes that inhibit OA, such as lack of mobile-friendly user interfaces, infrastructure development and digital divides, are not sufficiently addressed. This paper also indicated that academic libraries over-relied on open-source software and institutional repository, but most institutional repositories are merely “dumping sites” due to how information is classified and indexed.

This paper adopted meta-analysis by mining data sets from databases and provided thematic clustering of its content analysis through network visualisation to juxtapose the existing research gaps and lack of mobile-first insights needed to provide open-access information to the library’s users to consume information via mobile platforms. The retrieved dataset was discussed in tandem with the literature and the author’s insights into systems librarianship knowledge.

The library and information science (LIS) has not addressed how the academics could escape the pay-for-play cost, which was an exclusion tactic to disenfranchise emerging scholars and those without sufficient financial resources to choose between visibility, citation or publishing their outputs in journals without the possibility of citations, which is very important to their academic advancements. The LIS must shift its paradigm from mere talking about OA by producing graduates with the requisite skill to design, develop and host platforms that could enhance indexing and citations and import references. The current design of the institutional repository could be enhanced and promote easy navigation through mobile devices. Thereby taking into accounts internet bandwidth and digital divide, which still hinders accessibility of online resources.

This paper covered research within the LIS fields, and other outputs from other disciplines on OA were not included.

This paper showed the gaps that existed within the LIS campaign on OA, the research focuses of the LIS scholars/research librarians and the needed practical solution for the academic libraries to move beyond OA campaign and reconfigure institutional repository, not as dumping sites, but as infrastructure to host peer-reviewed journals.

Academic libraries institutional repositories can play vital roles in competing with major journal publishers to break their charges monopoly while providing platforms for scholars to make their outputs available freely.

The paper argued that the mobile-first approach to OA is a solution and advocated for mobile application development designed to promote OA resources through mobile-friendly interfaces.

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.

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 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.

Multiple disciplines such as finance, management and economics have contributed to governance research over time. However, the full intellectual structure of the governance “field” including the exchange of knowledge across disciplines and the large variety of governance topics remains to be uncovered. To appreciate the breadth of corporate governance research, it is necessary to understand the disciplinary sources from which the research stems. This manuscript focuses on the interdisciplinary underpinnings of corporate governance research.

This paper employs bibliometric analysis to trace the evolution of corporate governance using articles included in the ISI Web of Science database between 1990 and 2015. Journals included in these categories encompass a full range of business disciplines and provide evidence of the multi-disciplinary nature of corporate governance. It also uncovers the topics treated by disciplines under the governance umbrella using a machine learning method called latent Dirichtlet allocation (LDA).

Corporate governance research deals with a number of strategy-related topics. Unlike strategy topics that reside in a single discipline, corporate governance crosses disciplinary boundaries and includes contributions from accounting, finance, economics, law and management. Our analysis shows that over 80% of corporate governance articles come from outside the field of management. Our LDA solution indicates that the major topics in governance research include corporate governance theory, control of family firms, executive compensation and audit committees.

The results illustrate that corporate governance is far more interdisciplinary than previously thought. This is an important insight for corporate governance academics and may lead to collaborative research. More importantly, this research illustrates the usefulness of LDA for investigating interdisciplinary fields. This method is easily transferable to other interdisciplinary fields and it provides a powerful alternative to existing bibliometric methods. We suggest a number of topic areas within library and information science where this method may be applied, including collection development, support for interdisciplinary faculty and basic research into emerging interdisciplinary areas.

User-generated social media comments can be a useful source of information for understanding online corporate reputation. However, the manual classification of these comments is challenging due to their high volume and unstructured nature. The purpose of this paper is to develop a classification framework and machine learning model to overcome these limitations.

The authors create a multi-dimensional classification framework for the online corporate reputation that includes six main dimensions synthesized from prior literature: quality, reliability, responsibility, successfulness, pleasantness and innovativeness. To evaluate the classification framework’s performance on real data, the authors retrieve 19,991 social media comments about two Finnish banks and use a convolutional neural network (CNN) to classify automatically the comments based on manually annotated training data.

After parameter optimization, the neural network achieves an accuracy between 52.7 and 65.2 percent on real-world data, which is reasonable given the high number of classes. The findings also indicate that prior work has not captured all the facets of online corporate reputation.

For practical purposes, the authors provide a comprehensive classification framework for online corporate reputation, which companies and organizations operating in various domains can use. Moreover, the authors demonstrate that using a limited amount of training data can yield a satisfactory multiclass classifier when using CNN.

This is the first attempt at automatically classifying online corporate reputation using an online-specific classification framework.