Medical Theses and Derivative Articles: Dissemination Of Contents and Publication Patterns

Authors : Mercedes Echeverria, David Stuart, Tobias Blanke

Doctoral theses are an important source of publication in universities, although little research has been carried out on the publications resulting from theses, on so-called derivative articles.

This study investigates how derivative articles can be identified through a text analysis based on the full-text of a set of medical theses and the full-text of articles, with which they shared authorship.

The text similarity analysis methodology applied consisted in exploiting the full-text articles according to organization of scientific discourse (IMRaD) using the TurnItIn plagiarism tool.

The study found that the text similarity rate in the Discussion section can be used to discriminate derivative articles from non-derivative articles.

Additional findings were: the first position of the thesis’s author dominated in 85% of derivative articles, the participation of supervisors as coauthors occurred in 100% of derivative articles, the authorship credit retained by the thesis’s author was 42% in derivative articles, the number of coauthors by article was 5 in derivative articles versus 6.4 coauthors, as average, in non-derivative articles and the time differential regarding the year of thesis completion showed that 87.5% of derivative articles were published before or in the same year of thesis completion.


Global Data Quality Assessment and the Situated Nature of “Best” Research Practices in Biology

Author : Sabina Leonelli

This paper reflects on the relation between international debates around data quality assessment and the diversity characterising research practices, goals and environments within the life sciences.

Since the emergence of molecular approaches, many biologists have focused their research, and related methods and instruments for data production, on the study of genes and genomes.

While this trend is now shifting, prominent institutions and companies with stakes in molecular biology continue to set standards for what counts as ‘good science’ worldwide, resulting in the use of specific data production technologies as proxy for assessing data quality.

This is problematic considering (1) the variability in research cultures, goals and the very characteristics of biological systems, which can give rise to countless different approaches to knowledge production; and (2) the existence of research environments that produce high-quality, significant datasets despite not availing themselves of the latest technologies.

Ethnographic research carried out in such environments evidences a widespread fear among researchers that providing extensive information about their experimental set-up will affect the perceived quality of their data, making their findings vulnerable to criticisms by better-resourced peers. T

hese fears can make scientists resistant to sharing data or describing their provenance. To counter this, debates around Open Data need to include critical reflection on how data quality is evaluated, and the extent to which that evaluation requires a localised assessment of the needs, means and goals of each research environment.

URL : Global Data Quality Assessment and the Situated Nature of “Best” Research Practices in Biology


Reproducibility2020: Progress and priorities

Authors : Leonard P. Freedman, Gautham Venugopalan, Rosann Wisman

The preclinical research process is a cycle of idea generation, experimentation, and reporting of results. The biomedical research community relies on the reproducibility of published discoveries to create new lines of research and to translate research findings into therapeutic applications.

Since 2012, when scientists from Amgen reported that they were able to reproduce only 6 of 53 “landmark” preclinical studies, the biomedical research community began discussing the scale of the reproducibility problem and developing initiatives to address critical challenges.

Global Biological Standards Institute (GBSI) released the “Case for Standards” in 2013, one of the first comprehensive reports to address the rising concern of irreproducible biomedical research.

Further attention was drawn to issues that limit scientific self-correction, including reporting and publication bias, underpowered studies, lack of open access to methods and data, and lack of clearly defined standards and guidelines in areas such as reagent validation.

To evaluate the progress made towards reproducibility since 2013, GBSI identified and examined initiatives designed to advance quality and reproducibility. Through this process, we identified key roles for funders, journals, researchers and other stakeholders and recommended actions for future progress. This paper describes our findings and conclusions.

URL : Reproducibility2020: Progress and priorities


A Bibliometric study of Directory of Open Access Journals: Special reference to Microbiology

Author : K S Savita

The present study aim is to determine the number of free e-journal in the field of Microbiology available on DOAJ.

For this study the author has adopted bibliometric method and analyzed on the basis of country-wise distribution, language wise distribution and subject heading wise distribution.

URL : A Bibliometric study of Directory of Open Access Journals: Special reference to Microbiology

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What incentives increase data sharing in health and medical research? A systematic review

Authors : Anisa Rowhani-Farid, Michelle Allen, Adrian G. Barnett


The foundation of health and medical research is data. Data sharing facilitates the progress of research and strengthens science. Data sharing in research is widely discussed in the literature; however, there are seemingly no evidence-based incentives that promote data sharing.


A systematic review (registration: of the health and medical research literature was used to uncover any evidence-based incentives, with pre- and post-empirical data that examined data sharing rates.

We were also interested in quantifying and classifying the number of opinion pieces on the importance of incentives, the number observational studies that analysed data sharing rates and practices, and strategies aimed at increasing data sharing rates.


Only one incentive (using open data badges) has been tested in health and medical research that examined data sharing rates. The number of opinion pieces (n = 85) out-weighed the number of article-testing strategies (n = 76), and the number of observational studies exceeded them both (n = 106).


Given that data is the foundation of evidence-based health and medical research, it is paradoxical that there is only one evidence-based incentive to promote data sharing. More well-designed studies are needed in order to increase the currently low rates of data sharing.

URL : What incentives increase data sharing in health and medical research? A systematic review

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Should biomedical research be like Airbnb?

Authors : Vivien R. Bonazzi, Philip E. Bourne

The thesis presented here is that biomedical research is based on the trusted exchange of services. That exchange would be conducted more efficiently if the trusted software platforms to exchange those services, if they exist, were more integrated.

While simpler and narrower in scope than the services governing biomedical research, comparison to existing internet-based platforms, like Airbnb, can be informative.

We illustrate how the analogy to internet-based platforms works and does not work and introduce The Commons, under active development at the National Institutes of Health (NIH) and elsewhere, as an example of the move towards platforms for research.

URL : Should biomedical research be like Airbnb?


The Global Burden of Journal Peer Review in the Biomedical Literature: Strong Imbalance in the Collective Enterprise

Authors : Michail Kovanis, Raphaël Porcher, Philippe Ravaud, Ludovic Trinquart

The growth in scientific production may threaten the capacity for the scientific community to handle the ever-increasing demand for peer review of scientific publications. There is little evidence regarding the sustainability of the peer-review system and how the scientific community copes with the burden it poses.

We used mathematical modeling to estimate the overall quantitative annual demand for peer review and the supply in biomedical research. The modeling was informed by empirical data from various sources in the biomedical domain, including all articles indexed at MEDLINE.

We found that for 2015, across a range of scenarios, the supply exceeded by 15% to 249% the demand for reviewers and reviews. However, 20% of the researchers performed 69% to 94% of the reviews.

Among researchers actually contributing to peer review, 70% dedicated 1% or less of their research work-time to peer review while 5% dedicated 13% or more of it. An estimated 63.4 million hours were devoted to peer review in 2015, among which 18.9 million hours were provided by the top 5% contributing reviewers.

Our results support that the system is sustainable in terms of volume but emphasizes a considerable imbalance in the distribution of the peer-review effort across the scientific community.

Finally, various individual interactions between authors, editors and reviewers may reduce to some extent the number of reviewers who are available to editors at any point.

URL : The Global Burden of Journal Peer Review in the Biomedical Literature: Strong Imbalance in the Collective Enterprise