Water,Water, Everywhere: Defining and Assessing Data Sharing in Academia

Sharing of research data has begun to gain traction in many areas of the sciences in the past few years because of changing expectations from the scientific community, funding agencies, and academic journals. National Science Foundation (NSF) requirements for a data management plan (DMP) went into effect in 2011, with the intent of facilitating the dissemination and sharing of research results. Many projects that were funded during 2011 and 2012 should now have implemented the elements of the data management plans required for their grant proposals. In this paper we define ‘data sharing’ and present a protocol for assessing whether data have been shared and how effective the sharing was. We then evaluate the data sharing practices of researchers funded by the NSF at Oregon State University in two ways: by attempting to discover project-level research data using the associated DMP as a starting point, and by examining data sharing associated with journal articles that acknowledge NSF support. Sharing at both the project level and the journal article level was not carried out in the majority of cases, and when sharing was accomplished, the shared data were often of questionable usability due to access, documentation, and formatting issues. We close the article by offering recommendations for how data producers, journal publishers, data repositories, and funding agencies can facilitate the process of sharing data in a meaningful way.     

Codifying Collegiality: Recent Developments in Data Sharing Policy in the Life Sciences

Over the last decade, there have been significant changes in data sharing policies and in the data sharing environment faced by life science researchers. Using data from a 2013 survey of over 1600 life science researchers, we analyze the effects of sharing policies of funding agencies and journals. We also examine the effects of new sharing infrastructure and tools (i.e., third party repositories and online supplements). We find that recently enacted data sharing policies and new sharing infrastructure and tools have had a sizable effect on encouraging data sharing. In particular, third party repositories and online supplements as well as data sharing requirements of funding agencies, particularly the NIH and the National Human Genome Research Institute, were perceived by scientists to have had a large effect on facilitating data sharing. In addition, we found a high degree of compliance with these new policies, although noncompliance resulted in few formal or informal sanctions. Despite the overall effectiveness of data sharing policies, some significant gaps remain: about one third of grant reviewers placed no weight on data sharing plans in their reviews, and a similar percentage ignored the requirements of material transfer agreements. These patterns suggest that although most of these new policies have been effective, there is still room for policy improvement.     

Assessment of transparency indicators across the biomedical literature: How open is open?

Recent concerns about the reproducibility of science have led to several calls for more open and transparent research practices and for the monitoring of potential improvements over time. However, with tens of thousands of new biomedical articles published per week, manually mapping and monitoring changes in transparency is unrealistic. We present an open-source, automated approach to identify 5 indicators of transparency (data sharing, code sharing, conflicts of interest disclosures, funding disclosures, and protocol registration) and apply it across the entire open access biomedical literature of 2.75 million articles on PubMed Central (PMC). Our results indicate remarkable improvements in some (e.g., conflict of interest [COI] disclosures and funding disclosures), but not other (e.g., protocol registration and code sharing) areas of transparency over time, and map transparency across fields of science, countries, journals, and publishers. This work has enabled the creation of a large, integrated, and openly available database to expedite further efforts to monitor, understand, and promote transparency and reproducibility in science.

This study uses novel open source automated tools to monitor transparency across all 2.75 million open access articles on PubMed Central, discovering that different disciplines, journals and publishers abide by principles of transparency to varying degrees over time.     

The Leeds Evaluation of Efficacy of Detoxification Study (LEEDS) Prisons Project Study: protocol for a randomised controlled trial comparing methadone and buprenorphine for opiate detoxification

Many research-funding agencies now require open access to the results of research they have funded, and some also require that researchers make available the raw data generated from that research. Similarly, the journal Trials aims to address inadequate reporting in randomised controlled trials, and in order to fulfil this objective, the journal is working with the scientific and publishing communities to try to establish best practice for publishing raw data from clinical trials in peer-reviewed biomedical journals. Common issues encountered when considering raw data for publication include patient privacy – unless explicit consent for publication is obtained – and ownership, but agreed-upon policies for tackling these concerns do not appear to be addressed in the guidance or mandates currently established. Potential next steps for journal editors and publishers, ethics committees, research-funding agencies, and researchers are proposed, and alternatives to journal publication, such as restricted access repositories, are outlined.     

Open by default: a proposed copyright license and waiver agreement for open access research and data in peer-reviewed journals

ABSTRACT: Copyright and licensing of scientific data, internationally, are complex and present legal barriers to data sharing, integration and reuse, and therefore restrict the most efficient transfer and discovery of scientific knowledge. Much data are included within scientific journal articles, their published tables, additional files (supplementary material) and reference lists. However, these data are usually published under licenses which are not appropriate for data. Creative Commons CC0 is an appropriate and increasingly accepted method for dedicating data to the public domain, to enable data reuse with the minimum of restrictions. BioMed Central is committed to working towards implementation of open data-compliant licensing in its publications. Here we detail a protocol for implementing a combined Creative Commons Attribution license (for copyrightable material) and Creative Commons CC0 waiver (for data) agreement for content published in peer-reviewed open access journals. We explain the differences between legal requirements for attribution in copyright, and cultural requirements in scholarship for giving individuals credit for their work through citation. We argue that publishing data in scientific journals under CC0 will have numerous benefits for individuals and society, and yet will have minimal implications for authors and minimal impact on current publishing and research workflows. We provide practical examples and definitions of data types, such as XML and tabular data, and specific secondary use cases for published data, including text mining, reproducible research, and open bibliography. We believe this proposed change to the current copyright and licensing structure in science publishing will help clarify what users -- people and machines -- of the published literature can do, legally, with journal articles and make research using the published literature more efficient. We further believe this model could be adopted across multiple publishers, and invite comment on this article from all stakeholders in scientific research.     

Empirical Study of Data Sharing by Authors Publishing in PLoS Journals

Background

Many journals now require authors share their data with other investigators, either by depositing the data in a public repository or making it freely available upon request. These policies are explicit, but remain largely untested. We sought to determine how well authors comply with such policies by requesting data from authors who had published in one of two journals with clear data sharing policies.

Methods and Findings

We requested data from ten investigators who had published in either PLoS Medicine or PLoS Clinical Trials. All responses were carefully documented. In the event that we were refused data, we reminded authors of the journal''s data sharing guidelines. If we did not receive a response to our initial request, a second request was made. Following the ten requests for raw data, three investigators did not respond, four authors responded and refused to share their data, two email addresses were no longer valid, and one author requested further details. A reminder of PLoS''s explicit requirement that authors share data did not change the reply from the four authors who initially refused. Only one author sent an original data set.

Conclusions

We received only one of ten raw data sets requested. This suggests that journal policies requiring data sharing do not lead to authors making their data sets available to independent investigators.     

Dual-use review policies of biomedical research journals

To address biosecurity issues, government agencies, academic institutions, and professional societies have developed policies concerning the publication of "dual-use" biomedical research-that is, research that could be readily applied to cause significant harm to the public, the environment, or national security. We conducted an e-mail survey of life science journals to determine the percentage that have a dual-use policy. Of the 155 journals that responded to our survey (response rate 39%), only 7.7% stated that they had a written dual-use policy and only 5.8% said they had experience reviewing dual-use research in the past 5 years. Among the potential predictors we investigated, the one most highly associated with a journal having a written dual-use policy was membership in the Nature Publishing Group (positive association). When considered individually, both previous experience with reviewing dual-use research and the journal's impact factor appeared to be positively associated with having a written dual-use policy, but only the former remained significant after adjusting for publishing group. Although preventing the misuse of scientific research for terrorist or criminal purposes is an important concern, few biomedical journals have dual-use review policies. Journals that are likely to review research that raises potential dual-use concerns should consider developing dual-use policies.     

The Dawn of Open Access to Phylogenetic Data

The scientific enterprise depends critically on the preservation of and open access to published data. This basic tenet applies acutely to phylogenies (estimates of evolutionary relationships among species). Increasingly, phylogenies are estimated from increasingly large, genome-scale datasets using increasingly complex statistical methods that require increasing levels of expertise and computational investment. Moreover, the resulting phylogenetic data provide an explicit historical perspective that critically informs research in a vast and growing number of scientific disciplines. One such use is the study of changes in rates of lineage diversification (speciation – extinction) through time. As part of a meta-analysis in this area, we sought to collect phylogenetic data (comprising nucleotide sequence alignment and tree files) from 217 studies published in 46 journals over a 13-year period. We document our attempts to procure those data (from online archives and by direct request to corresponding authors), and report results of analyses (using Bayesian logistic regression) to assess the impact of various factors on the success of our efforts. Overall, complete phylogenetic data for of these studies are effectively lost to science. Our study indicates that phylogenetic data are more likely to be deposited in online archives and/or shared upon request when: (1) the publishing journal has a strong data-sharing policy; (2) the publishing journal has a higher impact factor, and; (3) the data are requested from faculty rather than students. Importantly, our survey spans recent policy initiatives and infrastructural changes; our analyses indicate that the positive impact of these community initiatives has been both dramatic and immediate. Although the results of our study indicate that the situation is dire, our findings also reveal tremendous recent progress in the sharing and preservation of phylogenetic data.     

Revenue management for outpatient appointments: joint capacity control and overbooking with class-dependent no-shows

Outpatient appointment scheduling balances efficiency with access to healthcare services, yet appointment no-shows, cancellations, and delay are significant barriers to effective healthcare delivery. Patients with longer appointment delay often waste appointments more frequently, prompting a need for greater flexibility in appointment allocation. We present a joint capacity control and overbooking model where a clinic maximizes profits by controlling bookings from two sequential patient classes with different no-show rates. When booking advance requests, the clinic must balance high no-show probability with the probability of subsequent requests at lower waste rates. We show the optimal policy is computationally intensive to derive; therefore, we develop bounds and approximations which we compare via numerical study with the optimal policy as well as policies from practice and previous literature. We find the optimal policy increases profits 17.8% over first-come-first-serve allocation. We develop a simple policy which performs 0.3% below optimal on average. While pure open access can achieve optimality, it performs 23.0% below optimal on average.     

Misconduct Policies in High-Impact Biomedical Journals

Background

It is not clear which research misconduct policies are adopted by biomedical journals. This study assessed the prevalence and content policies of the most influential biomedical journals on misconduct and procedures for handling and responding to allegations of misconduct.

Methods

We conducted a cross-sectional study of misconduct policies of 399 high-impact biomedical journals in 27 biomedical categories of the Journal Citation Reports in December 2011. Journal websites were reviewed for information relevant to misconduct policies.

Results

Of 399 journals, 140 (35.1%) provided explicit definitions of misconduct. Falsification was explicitly mentioned by 113 (28.3%) journals, fabrication by 104 (26.1%), plagiarism by 224 (56.1%), duplication by 242 (60.7%) and image manipulation by 154 (38.6%). Procedures for responding to misconduct were described in 179 (44.9%) websites, including retraction, (30.8%) and expression of concern (16.3%). Plagiarism-checking services were used by 112 (28.1%) journals. The prevalences of all types of misconduct policies were higher in journals that endorsed any policy from editors’ associations, Office of Research Integrity or professional societies compared to those that did not state adherence to these policy-producing bodies. Elsevier and Wiley-Blackwell had the most journals included (22.6% and 14.8%, respectively), with Wiley journals having greater a prevalence of misconduct definition and policies on falsification, fabrication and expression of concern and Elsevier of plagiarism-checking services.

Conclusions

Only a third of top-ranking peer-reviewed journals had publicly-available definitions of misconduct and less than a half described procedures for handling allegations of misconduct. As endorsement of international policies from policy-producing bodies was positively associated with implementation of policies and procedures, journals and their publishers should standardize their policies globally in order to increase public trust in the integrity of the published record in biomedicine.     

New journal: Algorithms for Molecular Biology

This editorial announces Algorithms for Molecular Biology, a new online open access journal published by BioMed Central. By launching the first open access journal on algorithmic bioinformatics, we provide a forum for fast publication of high-quality research articles in this rapidly evolving field. Our journal will publish thoroughly peer-reviewed papers without length limitations covering all aspects of algorithmic data analysis in computatioal biology. Publications in Algorithms for Molecular Biology are easy to find, highly visible and tracked by organisations such as PubMed. An established online submission system makes a fast reviewing procedure possible and enables us to publish accepted papers without delay. All articles published in our journal are permanently archived by PubMed Central and other scientific archives. We are looking forward to receiving your contributions.     

Confirming microarray data--is it really necessary?

The generation of corroborative data has become a commonly used approach for ensuring the veracity of microarray data. Indeed, the need to conduct corroborative studies has now become official editorial policy for at least 2 journals, and several more are considering introducing such a policy. The issue of corroborating microarray data is a challenging one-there are good arguments for and against conducting such experiments. However, we believe that the introduction of a fixed requirement to corroborate microarray data, especially if adopted by more journals, is overly burdensome and may, in at least several applications of microarray technology, be inappropriate. We also believe that, in cases in which corroborative studies are deemed essential, a lack of clear guidance leaves researchers unclear as to what constitutes an acceptable corroborative study. Guidelines have already been outlined regarding the details of conducting microarray experiments. We propose that all stakeholders, including journal editorial boards, reviewers, and researchers, should undertake concerted and inclusive efforts to address properly and clarify the specific issue of corroborative data. In this article we highlight some of the thorny and vague areas for discussion surrounding this issue. We also report the results of a poll in which 76 life science journals were asked about their current or intended policies on the inclusion of corroborative studies in papers containing microarray data.     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

Identifiability in biobanks: models,measures, and mitigation strategies

The collection and sharing of person-specific biospecimens has raised significant questions regarding privacy. In particular, the question of identifiability, or the degree to which materials stored in biobanks can be linked to the name of the individuals from which they were derived, is under scrutiny. The goal of this paper is to review the extent to which biospecimens and affiliated data can be designated as identifiable. To achieve this goal, we summarize recent research in identifiability assessment for DNA sequence data, as well as associated demographic and clinical data, shared via biobanks. We demonstrate the variability of the degree of risk, the factors that contribute to this variation, and potential ways to mitigate and manage such risk. Finally, we discuss the policy implications of these findings, particularly as they pertain to biobank security and access policies. We situate our review in the context of real data sharing scenarios and biorepositories.     

The Importance of Biodiversity E-infrastructures for Megadiverse Countries

Addressing the challenges of biodiversity conservation and sustainable development requires global cooperation, support structures, and new governance models to integrate diverse initiatives and achieve massive, open exchange of data, tools, and technology. The traditional paradigm of sharing scientific knowledge through publications is not sufficient to meet contemporary demands that require not only the results but also data, knowledge, and skills to analyze the data. E-infrastructures are key in facilitating access to data and providing the framework for collaboration. Here we discuss the importance of e-infrastructures of public interest and the lack of long-term funding policies. We present the example of Brazil’s speciesLink network, an e-infrastructure that provides free and open access to biodiversity primary data and associated tools. SpeciesLink currently integrates 382 datasets from 135 national institutions and 13 institutions from abroad, openly sharing ~7.4 million records, 94% of which are associated to voucher specimens. Just as important as the data is the network of data providers and users. In 2014, more than 95% of its users were from Brazil, demonstrating the importance of local e-infrastructures in enabling and promoting local use of biodiversity data and knowledge. From the outset, speciesLink has been sustained through project-based funding, normally public grants for 2–4-year periods. In between projects, there are short-term crises in trying to keep the system operational, a fact that has also been observed in global biodiversity portals, as well as in social and physical sciences platforms and even in computing services portals. In the last decade, the open access movement propelled the development of many web platforms for sharing data. Adequate policies unfortunately did not follow the same tempo, and now many initiatives may perish.     

生物多样性数据论文发表趋势分析

近年来有关科学数据共享的呼声越来越高, 基于同行评审的生物多样性数据论文也受到越来越多的关注, 并出现了一些专门发表数据论文的数据期刊。本文总结了近年来生物多样性数据发表方面的进展, 选择两本代表性数据期刊(Biodiversity Data Journal和Scientific Data), 分析了它们自创刊以来的发文数量、涉及生物类群、文章浏览量和被引次数等指标。结果显示两本数据期刊的发文量都呈稳步增长趋势, 其生物多样性数据论文覆盖了包括动物界、植物界、真菌界在内的众多生物类群, 文章浏览量和被引次数方面也有可喜的表现, 说明数据论文正在被越来越多的研究者所接受。对文章作者国别的分析则显示了不同地区的研究者在发表生物多样性数据论文或数据共享方面的不均衡。建议相关领域的中国研究者和期刊关注生物多样性数据论文和数据共享政策, 更多地践行数据共享。     

Who Shares? Who Doesn't? Factors Associated with Openly Archiving Raw Research Data

Many initiatives encourage investigators to share their raw datasets in hopes of increasing research efficiency and quality. Despite these investments of time and money, we do not have a firm grasp of who openly shares raw research data, who doesn''t, and which initiatives are correlated with high rates of data sharing. In this analysis I use bibliometric methods to identify patterns in the frequency with which investigators openly archive their raw gene expression microarray datasets after study publication.Automated methods identified 11,603 articles published between 2000 and 2009 that describe the creation of gene expression microarray data. Associated datasets in best-practice repositories were found for 25% of these articles, increasing from less than 5% in 2001 to 30%–35% in 2007–2009. Accounting for sensitivity of the automated methods, approximately 45% of recent gene expression studies made their data publicly available.First-order factor analysis on 124 diverse bibliometric attributes of the data creation articles revealed 15 factors describing authorship, funding, institution, publication, and domain environments. In multivariate regression, authors were most likely to share data if they had prior experience sharing or reusing data, if their study was published in an open access journal or a journal with a relatively strong data sharing policy, or if the study was funded by a large number of NIH grants. Authors of studies on cancer and human subjects were least likely to make their datasets available.These results suggest research data sharing levels are still low and increasing only slowly, and data is least available in areas where it could make the biggest impact. Let''s learn from those with high rates of sharing to embrace the full potential of our research output.