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Data sharing and reuse promise many benefits to science, but many researchers are reluctant to share and reuse data. Data papers, published as peer‐reviewed articles that provide descriptive information about specific datasets, are a potential solution as they may incentivize sharing by providing a mechanism for data producers to get citation credit and support reuse by providing contextual information about dataset production. Data papers can receive many citations. However, does citation of a data paper mean reuse of the underlying dataset? This paper presents preliminary findings from a content‐based citation analysis of data papers (n = 103) published in two specialized data journals, one in earth sciences and one in physical and chemical sciences. We conclude that while the genre of data papers facilitates some data sharing and reuse, they fail to live up to their full potential. Further, practices of reuse of datasets from data papers vary considerably between disciplines. We propose measures for academic publishers to enhance the data paper's role in scholarly communication to attract more attention from researchers and to inform discipline‐specific policy and practices related to data publication. [ABSTRACT FROM AUTHOR]

As a data intensive field that unites researchers from many disciplines, Earth System Science (ESS) is an ideal site for examining evolving cross‐disciplinary data practices. This paper reports on results from a survey examining data sharing, data reuse, and research reproducibility practices of ESS researchers, aimed at informing improvements in data services for interdisciplinary sciences. Data reuse was found to be very high for new and comparative analyses but very limited for reproducing research. Data sharing was also strong, mostly through supplements to published papers, with moderate use of open access repositories. At the same time, there was interesting variability in both data sharing and reuse among ESS disciplines. The most pronounced challenges to reuse and reproducibility stem from limited documentation on how data are collected and managed, practices that are poorly supported by institutions, funders, and publishers. A more refined approach to "reproducibility" is needed that aligns with priorities and practices within the research community. Just as importantly, advances in data service models for ESS and other interdisciplinary fields need to account for the diverse and distributed system of repositories and build a workforce with deeper knowledge of the complex data and methods that drive integrative systems science. [ABSTRACT FROM AUTHOR]

Research data sharing is embedded in policies, guidelines and requirements commonly promoted by research funding organizations that demand data to be "as open as possible, as closed as necessary" and FAIR. This paper discusses the challenges of balancing privacy protection with data sharing in a PhD project involving long‐tail, small‐sized qualitative human subjects' data. Based on experiences and feedback from project participants, we argue that privacy protection is about respecting the participants and their self‐image. This can be achieved through dialogue and involvement of the participants building on the principles of shared stewardship. Further, we suggest that de‐identification and plain language consent materials are better at protecting privacy than anonymisation, which in a digital data environment is difficult to achieve and not necessarily a sensible approach for qualitative data, where the gold is in the details. The literature indicates that it matters to participants whether data are reused for research or other purposes, and that they trust the institutions. This supports our claim that research data services must find better solutions for restricted sharing when necessary. [ABSTRACT FROM AUTHOR]

Data and how that data are organized, accessed, and used, remain central to the advancement of science, as evidenced through calls for reproducibility and demands to enable re‐use. Data management plans describe the roles, responsibilities, and activities for managing data during and after research. This paper presents the development of a data management plan scorecard. The assessment of data management plans provides one measure to evaluate how data are planned to be shared and a first step down the road towards shareable data. The scorecard provides a widely‐applicable, scalable, and simple tool to assess completeness and quality of 15 data elements commonly required in all data management plans. [ABSTRACT FROM AUTHOR]

This paper presents the results of our study of biological scientists' formation of research ethics for data sharing intentions. Based on consequential theorists' perspective of ethics, it examines what the main contributing factors affecting biological scientists' formation of research ethics for data sharing are. By analyzing an online survey with 577 respondents with SEM (Structural Equation Modeling) technique, the paper identifies the extent to which egoism factors and utilitarian factors influence their research ethics formation, which eventually leads to their data sharing intentions. [ABSTRACT FROM AUTHOR]

While the importance of open science is further highlighted during the pandemic, the challenges of managing and sharing individual participant data (IPD) derived from clinical studies never cease. The nature of IPD, e.g., confidentiality or sensitivity, makes it difficult to maintain a good balance between data sharing and individual privacy protection. To date, many access control mechanisms for IPD do exist, but conventional solutions and services are deemed scattered and still not in place. To gain a more comprehensive understanding of the IPD sharing tensions, we conducted a systematic literature review with 64 academic publications that discuss the access control mechanisms built for IPD in clinical studies. Via the knowledge infrastructure (KI) framework, we identified nine key aspects involved and the relationships between major stakeholders in the IPD access control ecosystem. Our results anticipate informing the future design of an IPD management checklist that data professionals can use to guide their clients when releasing sensitive biomedical data. [ABSTRACT FROM AUTHOR]

We describe a new vision for a Data Management Plan (DMP) that incorporates controlled vocabularies and semantic descriptions of the scholarly objects to be produced by the proposed project. We implement this vision in an open‐source web‐based DMP tool, called ezDMP, at ezdmp.org. The integrated use of structured information in ezDMP permits several important goals. First, with minimal additional effort, researchers can create DMPs with more complete information about the scholarly objects to be produced. Second, research funders can productively query this structured information to learn about repository use and other patterns of scholarly objects creation. Finally, ezDMP puts a structure in place that can support the integration of information about digital scholars objects, in an organized and systematic way, into research data management environments. [ABSTRACT FROM AUTHOR]

Data sharing has been emphasized in scientific research in the era of open science; however, the concept of data sharing is ambiguous, and the real situation of data sharing is unclear. One reason is that most studies focused on researchers' recognition, motivation, and other contributing factors and did not thoroughly discuss the actual practice of data sharing for preparing research articles. To explicitly understand the current status of data sharing, the authors considered and investigated primary reuse, data integration, and data release distinctively as the actual practices of data sharing. A total of 237 articles published in 2018 and registered in the Web of Science global citation database were manually checked. Unlike the scarcity of data reuse (8.0%) or data release (5.1%), existing data were most frequently reused in the form of data integration (20.7%). The result implies that further studies on detailed data reuse are required to clarify the concept of data sharing. [ABSTRACT FROM AUTHOR]

This research investigated how scientists' academic reputation, community trust, and norms regarding data sharing all influence their academic reciprocity in data sharing, which eventually leads to the scientists' data sharing intentions. This research employed Ostrom's (2003) theory of collective action to better understand scientists' data sharing behaviors from the perspective of cooperation in a community. This research empirically evaluated the research model and related hypotheses by using the Structural Equation Modeling (SEM) method on a total of 456 survey responses from biologists in the U.S. The results suggest that biologists' perceived academic reputation significantly increases their perceived community trust, norm of data sharing, and academic reciprocity. Along with perceived academic reputation, both perceived community trust and norms of data sharing also significantly increases biologists' academic reciprocity in data sharing. This research also found that biologists' academic reciprocity and norms of data sharing significantly affect their data sharing intentions. The results of this research show that the theory of collective action provides new insight to scientists' data sharing behaviors. These results suggest how we can facilitate scientists' data sharing behaviors within a research community by increasing academic reciprocity through the mechanisms of reputation, trust, and norm. [ABSTRACT FROM AUTHOR]

ABSTRACT Sharing and reuse of scientific data, which can enhance the transparency and reproducibility of research and lead to the creation of new knowledge from existing data, is both a growing scholarly communication practice and an expanding area of interest in information science. However, much of the literature to date has focused on the data practices of scientists working in academic environments, with less research done on understanding the practices of scientists working in other types of environments, such as government or industry. This poster presents the results of a study in which data from a worldwide survey of scientists were analyzed to determine if differences in data practices, perceptions, and access to resources for data sharing existed between scientists who reported their primary work sector as academic and those who reported a non-academic primary work sector. Researchers' perceptions of data sharing and reuse were generally positive and did not differ significantly by work sector. However, differences were found in actual reported data sharing practices, even when controlling for researchers' age, geographic location, and subject discipline. Researchers outside of academia had lesser odds of reporting sharing all their data. Differences were also found in reported barriers to data sharing, as well as in reported access to and use of data sharing resources, suggesting that data sharing challenges faced by scientists working outside of academia may differ from those faced by their academic peers. Implications for the adoption of data sharing practices and technologies, as well as for knowledge sharing and creation across work sectors, are discussed, and suggestions are offered for further research. [ABSTRACT FROM AUTHOR]

"Open data" is a popular phrase in research practice and science policy. While stakeholders agree on some aspects of this concept, many others remain hotly debated. As a means to identify the main themes and arguments surrounding open data, we analyzed highly cited publications from the last 10 years that address data sharing or open access to research data. We identify and synthesize eight components of open data that vary among policies, studies, and initiatives, and present problematic arguments worthy of further investigation. [ABSTRACT FROM AUTHOR]

As digital research data proliferate and expectations for sharing data escalate, the landscape of open data repositories is becoming more complex. Data sharing is especially important in the atmospheric and climate sciences, where data integration and reuse can have significant impact on the advancement of research on climate change. This study analyzed 38 open digital repositories in the atmospheric and climate sciences using 55 criteria to characterize the repositories based on content analysis of the repository websites. The resulting repository profiles offer systematic descriptions of capabilities, services, and other characteristics for identifying specific repository features and comparing them across repositories. The profiles are of value for data curation education, researchers in the geosciences, and librarians and others providing data services in the sciences. [ABSTRACT FROM AUTHOR]

ABSTRACT With the rapid development and increased use of information and communication technology (ICT), the demand for data sharing and reuse is growing even in developing countries. This study aims to contribute to the recently emerging discussions on data sharing in developing countries with a focus on the case of Uganda. The goal of this study is to uncover the current practices of and efforts for data sharing in the public sector in Uganda and to understand the relevant stakeholders' perceptions of data sharing and reuse practices/services. [ABSTRACT FROM AUTHOR]