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Science policy and practice for open access (OA) books is a rapidly evolving area in the scholarly domain. However, there is much that remains unknown, including how many OA books there are and to what degree they are included in preservation coverage. The purpose of this study is to contribute towards filling this knowledge gap in order to advance both research and practice in the domain of OA books.

This study utilized open bibliometric data sources to aggregate a harmonized dataset of metadata records for OA books (data sources: the Directory of Open Access Books, OpenAIRE, OpenAlex, Scielo Books, The Lens, and WorldCat). This dataset was then cross-matched based on unique identifiers and book titles to openly available content listings of trusted preservation services (data sources: Cariniana Network, CLOCKSS, Global LOCKSS Network, and Portico). The web domains of the OA books were determined by querying the web addresses or digital object identifiers provided in the metadata of the bibliometric database entries.

In total, 396,995 unique records were identified from the OA book bibliometric sources, of which 19% were found to be included in at least one of the preservation services. The results suggest reason for concern for the long tail of OA books distributed at thousands of different web domains as these include volatile cloud storage or sometimes no longer contained the files at all.

Data quality issues, varying definitions of OA across services and inconsistent implementation of unique identifiers were discovered as key challenges. The study includes recommendations for publishers, libraries, data providers and preservation services for improving monitoring and practices for OA book preservation.

This study provides methodological and empirical findings for advancing the practices of OA book publishing, preservation and research.

The data economy mainly relies on the surveillance capitalism business model, enabling companies to monetize their data. The surveillance allows for transforming private human experiences into behavioral data that can be harnessed in the marketing sphere. This study aims to focus on investigating the domain of data economy with the methodological lens of quantitative bibliometric analysis of published literature.

The bibliometric analysis seeks to unravel trends and timelines for the emergence of the data economy, its conceptualization, scientific progression and thematic synergy that could predict the future of the field. A total of 591 data between 2008 and June 2021 were used in the analysis with the Biblioshiny app on the web interfaced and VOSviewer version 1.6.16 to analyze data from Web of Science and Scopus.

This study combined findable, accessible, interoperable and reusable (FAIR) data and data economy and contributed to the literature on big data, information discovery and delivery by shedding light on the conceptual, intellectual and social structure of data economy and demonstrating data relevance as a key strategic asset for companies and academia now and in the future.

Findings from this study provide a steppingstone for researchers who may engage in further empirical and longitudinal studies by employing, for example, a quantitative and systematic review approach. In addition, future research could expand the scope of this study beyond FAIR data and data economy to examine aspects such as theories and show a plausible explanation of several phenomena in the emerging field.

The researchers can use the results of this study as a steppingstone for further empirical and longitudinal studies.

This study confirmed the relevance of data to society and revealed some gaps to be undertaken for the future.

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.

Budgeting data curation tasks in research projects is difficult. In this paper, we investigate the time spent on data curation, more specifically on cleaning and documenting quantitative data for data sharing. We develop recommendations on cost factors in research data management.

We make use of a pilot study conducted at the GESIS Data Archive for the Social Sciences in Germany between December 2016 and September 2017. During this period, data curators at GESIS - Leibniz Institute for the Social Sciences documented their working hours while cleaning and documenting data from ten quantitative survey studies. We analyse recorded times and discuss with the data curators involved in this work to identify and examine important cost factors in data curation, that is aspects that increase hours spent and factors that lead to a reduction of their work.

We identify two major drivers of time spent on data curation: The size of the data and personal information contained in the data. Learning effects can occur when data are similar, that is when they contain same variables. Important interdependencies exist between individual tasks in data curation and in connection with certain data characteristics.

The different tasks of data curation, time spent on them and interdependencies between individual steps in curation have so far not been analysed.

Because BIM adoption is still afflicted by various types of hurdles, a complete BIM implementation model is required to provide the necessary methods for driving BIM adoption. As a result, this study looked into the parts of the BIM implementation model that had the most impact on increasing the percentage of BIM adoption in South Africa.

This study developed a four-wheel model of BIM implementation based on implementation process theory, which includes BIM inspiration, BIM capacity development, BIM use and BIM commitment. To assess BIM capacity development, two sub-constructs (BIM learning process and BIM learning methodologies) were used. Two sub-constructs were used to assess BIM utilisation (efficient BIM application and effective BIM application). The sub-constructs employed to quantify BIM motivation were organisational competitiveness, societal conformity and contractual obligations. Incentives, investments and obligations were used to assess BIM commitment. The model was validated using four assumptions and maximum likelihood estimation – structural equation modelling (MLE-SEM).

The MLE-SEM results demonstrated unequivocally that all of the constructions are critical components of the BIM deployment paradigm in the South African construction industry. BIM motivation, as characterised by organisational competitiveness and social compliance, has the greatest impact. The findings on BIM motivation also revealed that the desire for technological sophistication, competitiveness and social acceptance by clients are encouraging construction organisations and professionals to embrace BIM adoption.

This study's findings have contributed to the increasing body of literature on BIM deployment. The study has significant implications for achieving BIM implementation in underdeveloped nations where BIM deployment is either non-existent or in its early stages. The theoretical component of the study serves as the foundation for further analysis of BIM deployment.

This research is important for identifying BIM goals, developing a BIM implementation framework, allocating resources for BIM implementation and defining key performance indicators for BIM implementation. The BIM implementation aspects outlined in this study will be effective in lowering BIM adoption hurdles.

This study makes a unique contribution to BIM research by providing theoretical and empirical analysis into the elements of the BIM implementation model in a developing country. The study offers an excellent opportunity to further our understanding of BIM application in underdeveloped nations.

It's hard to envision a system more global and more integrated than research. Many stakeholders affect and are affected by changes in the research ecosystem; the ecosystem differs in significant ways across the globe and between researchers, institutions and fields of study; and there are many questions that exclusive action can't address. There are also broad ecosystem-level questions that need answering. For these reasons alone, global approaches to reform are needed.

The first step in this exploration isn't to start looking for “solutions”, but to develop a better understanding of how our needs and interests overlap. By identifying the broad contours of common ground in this conversation, we can build the guardrails and mileposts for our collaborative efforts and then allow the finer-grained details of community-developed plans more flexibility and guidance to evolve over time.

What are these overlapping interests? First, the people in this community share a common motive – idealism – to make research better able to serve the public good. We also share a common desire to unleash the power of open to improve research and accelerate discovery; we are all willing to fix issues now instead of waiting for market forces or government intervention to do this for us; and we want to ensure that everyone everywhere has equitable access to knowledge.

There is also very broad agreement in this community about which specific problems in scholarly communication need to be fixed and why, and well as many overlapping beliefs in this community. OSI participants have concluded that four such beliefs best define our common ground: (1) research and society will benefit from open done right; (2) successful solutions will require broad collaboration; (3) connected issues need to be addressed, and (4) open isn't a single outcome, but a spectrum.

OSI has been observing and debating the activity in scholarly communication since late 2014 with regard to understanding possible global approaches and solutions for improving the future of open research. While the COVID-19 pandemic has made the importance of open science abundantly clear, the struggle to achieve this goal (not just for science but for all research) has been mired in a lack of clarity and urgency for over 20 years now, mostly stalling on the tension between wanting more openness but lacking realistic solutions for making this happen on a large scale with so many different stakeholders, needs and perspectives involved.

Underlying this tension is a fundamental difference in philosophy: whether the entire scholarly communication marketplace, driven by the needs and desires of researchers, should determine what kind of open it wants and needs; or whether this marketplace should be compelled to adopt open reform measures developed primarily by the scholarly communication system's main billpayers-funders and libraries. There is no widespread difference of opinion in the community whether open is worth pursuing. The debate is mostly over what specific open solutions are best, and at what pace open reforms should occur.

OSI has proposed a plan of action for working together to rebuild the future of scholarly communication on strong, common ground foundation. This plan – which we're referring to as Plan A – calls for joint action on studies, scholarly communication infrastructure improvement, and open outreach/education. Plan A also calls for working together with UNESCO to develop a unified global roadmap for the future of open, and for striving to ensure the community's work in this space is researcher-focused, collaborative, connected (addressing connected issues like peer review), diverse and flexible (no one-size-fits-all solutions), and beneficial to research. UNESCO's goal is to finish its roadmap proposal by early 2022.

For a full discussion of OSI's common ground recommendations, please see the Plan A website at http://plan-a.world.

How to obtain a list of the 100 largest scientific publishers sorted by journal count? Existing databases are unhelpful as each of them inhere biased omissions and data quality flaws. This paper tries to fill this gap with an alternative approach.

The content coverages of Scopus, Publons, DOAJ and SherpaRomeo were first used to extract a preliminary list of publishers that supposedly possess at least 15 journals. Second, the publishers' websites were scraped to fetch their portfolios and, thus, their “true” journal counts.

The outcome is a list of the 100 largest publishers comprising 28.060 scholarly journals, with the largest publishing 3.763 journals, and the smallest carrying 76 titles. The usual “oligopoly” of major publishing companies leads the list, but it also contains 17 university presses from the Global South, and, surprisingly, 30 predatory publishers that together publish 4.517 journals.

Additional data sources could be used to mitigate remaining biases; it is difficult to disambiguate publisher names and their imprints; and the dataset carries a non-uniform distribution, thus risking the omission of data points in the lower range.

The dataset can serve as a useful basis for comprehensive meta-scientific surveys on the publisher-level.

The catalogue can be deemed more inclusive and diverse than other ones because many of the publishers would have been overlooked if one had drawn from merely one or two sources. The list is freely accessible and invites regular updates. The approach used here (webscraping) has seldomly been used in meta-scientific surveys.

A direct correlation exists between waste disposal, disease spread and public health. This article systematically reviewed healthcare waste and its implication for public health. This review identified and described the associations and impact of waste disposal on public health.

This paper systematically reviewed the literature on waste disposal and its implications for public health by searching Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA), PubMed, Web of Science, Scopus and ScienceDirect databases. Of a total of 1,583 studies, 59 articles were selected and reviewed.

The review revealed the spread of infectious diseases and environmental degradation as the most typical implications of improper waste disposal to public health. The impact of waste includes infectious diseases such as cholera, Hepatitis B, respiratory problems, food and metal poisoning, skin infections, and bacteremia, and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife.

Infectious diseases such as cholera, hepatitis B, respiratory problems, food and metal poisoning, skin infections, bacteremia and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife are some of the public impacts of improper waste disposal.

Healthcare industry waste is a significant waste that can harm the environment and public health if not properly collected, stored, treated, managed and disposed of. There is a need for knowledge and skills applicable to proper healthcare waste disposal and management. Policies must be developed to implement appropriate waste management to prevent public health threats.

Cybersecurity attacks on critical infrastructures, businesses and nations are rising and have reached the interest of mainstream media and the public’s consciousness. Despite this increased awareness, humans are still considered the weakest link in the defense against an unknown attacker. Whatever the reason, naïve-, unintentional- or intentional behavior of a member of an organization, the result of an incident can have a considerable impact. A security policy with guidelines for best practices and rules should guide the behavior of the organization’s members. However, this is often not the case. This paper aims to provide answers to how cybersecurity-related behavior is assessed.

Research questions were formulated, and a systematic literature review (SLR) was performed by following the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. The SLR initially identified 2,153 articles, and the paper reviews and reports on 26 articles.

The assessment of cybersecurity-related behavior can be classified into three components, namely, data collection, measurement scale and analysis. The findings show that subjective measurements from self-assessment questionnaires are the most frequently used method. Measurement scales are often composed based on existing literature and adapted by the researchers. Partial least square analysis is the most frequently used analysis technique. Even though useful insight and noteworthy findings regarding possible differences between manager and employee behavior have appeared in some publications, conclusive answers to whether such differences exist cannot be drawn.

Research gaps have been identified, that indicate areas of interest for future work. These include the development and employment of methods for reducing subjectivity in the assessment of cybersecurity-related behavior.

To the best of the authors’ knowledge, this is the first SLR on how cybersecurity-related behavior can be assessed. The SLR analyzes relevant publications and identifies current practices as well as their shortcomings, and outlines gaps that future research may bridge.