Explore the vast range of titles available.

To improve the quality and efficiency of research, groups within the scientific community seek to exploit the value of data sharing. Funders, institutions, and specialist organizations are developing and implementing strategies to encourage or mandate data sharing within and across disciplines, with varying degrees of success. Academic journals in ecology and evolution have adopted several types of public data archiving policies requiring authors to make data underlying scholarly manuscripts freely available. The effort to increase data sharing in the sciences is one part of a broader “data revolution” that has prompted discussion about a paradigm shift in scientific research. Yet anecdotes from the community and studies evaluating data availability suggest that these policies have not obtained the desired effects, both in terms of quantity and quality of available datasets. We conducted a qualitative, interview-based study with journal editorial staff and other stakeholders in the academic publishing process to examine how journals enforce data archiving policies. We specifically sought to establish who editors and other stakeholders perceive as responsible for ensuring data completeness and quality in the peer review process. Our analysis revealed little consensus with regard to how data archiving policies should be enforced and who should hold authors accountable for dataset submissions. Themes in interviewee responses included hopefulness that reviewers would take the initiative to review datasets and trust in authors to ensure the completeness and quality of their datasets. We highlight problematic aspects of these thematic responses and offer potential starting points for improvement of the public data archiving process.

Natural history collections (NHCs) are important resources for a diverse array of scientific fields. Recent digitization initiatives have broadened the user base of NHCs, and new technological innovations are using materials generated from collections to address novel scientific questions. Simultaneously, NHCs are increasingly imperiled by reductions in funding and resources. Ensuring that NHCs continue to serve as a valuable resource for future generations will require the scientific community to increase their contribution to and acknowledgement of collections. We provide recommendations and guidelines for scientists to support NHCs, focusing particularly on new users that may be unfamiliar with collections. We hope that this perspective will motivate debate on the future of NHCs and the role of the scientific community in maintaining and improving biological collections.

Open data facilitate reproducibility and accelerate scientific discovery but are hindered by perceptions that researchers bear costs and gain few benefits from publicly sharing their data, with limited empirical evidence to the contrary. We surveyed 140 faculty members working in ecology and evolution across Canada’s top 20 ranked universities and found that more researchers report benefits (47.9%) and neutral outcomes (43.6%) than costs (21.4%) from openly sharing data. The benefits were independent of career stage and gender, but men and early career researchers were more likely to report costs. We outline mechanisms proposed by the study participants to reduce the individual costs and increase the benefits of open data for faculty members.

Launched on 2 June 2003 and arriving at Mars on 25 December 2003 after a 7-month interplanetary cruise, Mars Express was the European Space Agency’s first mission to arrive at another planet. After more than 20 years in orbit, the spacecraft and science payload remain in good health and the mission has become the second oldest operational planetary orbiter after Mars Odyssey. This contribution summarizes the Mars Express mission operations, science planning and data archiving systems, processes, and teams that are necessary to run the mission, plan the scientific observations, and execute all necessary commands. It also describes the data download, the ground processing and distribution to the scientific community for the study and analysis of Mars sub-surface, surface, atmosphere, magnetosphere, and moons. This manuscript also describes the main challenges throughout the history of the mission, including several potentially mission-ending anomalies. We summarize the evolution of the ground segment to provide new capabilities not envisaged before launch, whilst simultaneously maintaining or even increasing the quality and quantity of scientific data generated.

Background. Attribution to the original contributor upon reuse of published data is important both as a reward for data creators and to document the provenance of research findings. Previous studies have found that papers with publicly available datasets receive a higher number of citations than similar studies without available data. However, few previous analyses have had the statistical power to control for the many variables known to predict citation rate, which has led to uncertain estimates of the \"citation benefit\". Furthermore, little is known about patterns in data reuse over time and across datasets. Method and Results. Here, we look at citation rates while controlling for many known citation predictors and investigate the variability of data reuse. In a multivariate regression on 10,555 studies that created gene expression microarray data, we found that studies that made data available in a public repository received 9% (95% confidence interval: 5% to 13%) more citations than similar studies for which the data was not made available. Date of publication, journal impact factor, open access status, number of authors, first and last author publication history, corresponding author country, institution citation history, and study topic were included as covariates. The citation benefit varied with date of dataset deposition: a citation benefit was most clear for papers published in 2004 and 2005, at about 30%. Authors published most papers using their own datasets within two years of their first publication on the dataset, whereas data reuse papers published by third-party investigators continued to accumulate for at least six years. To study patterns of data reuse directly, we compiled 9,724 instances of third party data reuse via mention of GEO or ArrayExpress accession numbers in the full text of papers. The level of third-party data use was high: for 100 datasets deposited in year 0, we estimated that 40 papers in PubMed reused a dataset by year 2, 100 by year 4, and more than 150 data reuse papers had been published by year 5. Data reuse was distributed across a broad base of datasets: a very conservative estimate found that 20% of the datasets deposited between 2003 and 2007 had been reused at least once by third parties. Conclusion. After accounting for other factors affecting citation rate, we find a robust citation benefit from open data, although a smaller one than previously reported. We conclude there is a direct effect of third-party data reuse that persists for years beyond the time when researchers have published most of the papers reusing their own data. Other factors that may also contribute to the citation benefit are considered. We further conclude that, at least for gene expression microarray data, a substantial fraction of archived datasets are reused, and that the intensity of dataset reuse has been steadily increasing since 2003.

In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for the deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and the resulting consensus recommendations. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.

Technological advances and the rise of collaborative, interdisciplinary approaches have changed the practice of research. The 21st century researcher not only faces the challenge of managing increasingly complex datasets, but also new data sharing requirements from funders and journals. Success in today’s research enterprise requires an understanding of how to work effectively with data, yet most researchers have never had any formal training in data management. Libraries have begun developing services and programs to help researchers meet the demands of the data-driven research enterprise, giving librarians exciting new opportunities to use their expertise and skills. The Medical Library Association Guide to Data Management for Librarians highlights the many ways that librarians are addressing researchers’ changing needs at a variety of institutions, including academic, hospital, and government libraries. Each chapter ends with “pearls of wisdom,” a bulleted list of 5-10 takeaway messages from the chapter that will help readers quickly put the ideas from the chapter into practice. From theoretical foundations to practical applications, this book provides a background for librarians who are new to data management as well as new ideas and approaches for experienced data librarians.

Abstract Data are one of the primary outputs of science. Although certain subdisciplines of biology have pioneered efforts to ensure their long-term preservation and facilitate collaborations, data continue to disappear, owing mostly to technological, regulatory, and ideological hurdles. In this article, we describe the important steps toward proper data management and archiving and provide a critical discussion on the importance of long-term data conservation. We then illustrate the rise in data archiving through the Joint Data Archiving Policy and the Dryad Digital Repository. In particular, we discuss data integration and how the limited availability of large-scale data sets can hinder new discoveries. Finally, we propose solutions to increase the rate of data preservation, for example by generating mechanisms insuring proper data management and archiving, by providing training in data management, and by transforming the traditional role of research institutions and libraries as data generators toward managers and archivers.

1. Public data archiving (PDA) is widely advocated as a means of achieving open data standards, leading to improved data preservation, increased scientific reproducibility, and transparency, as well as additional data use. 2. Public data archiving was primarily conceived to archive data from short-term, single-purpose scientific studies. It is now more widely applied, including to largescale citizen science biodiversity recording and monitoring schemes which combine the efforts of volunteers with professional scientists. 3. This may affect the financial security of such schemes by reducing income from data and analytical services. Communication between scheme organizers and researchers may be disrupted, reducing scientific quality and impeding scheme development. It may also have an impact on the participation of some volunteers. 4. Synthesis and applications. In response to the challenges of public data archiving for citizen science biodiversity recording and monitoring schemes, the archive function of scheme organizations should be better recognized by those promoting open data principles. Increased financial support from the public sector or from commercial or academic data users may offset financial risk. Those in favour of public data archiving should do more to facilitate communication between nonscheme users and the originating schemes, while a more flexible approach to data archiving may be required to address potential impacts on volunteer participation.

Drawing on the expertise of a diverse community of practitioners, this collection of case studies, original research, survey chapters, and theoretical explorations presents a wide-ranging look at the field of academic data librarianship.