Academic criteria for promotion and tenure in biomedical sciences faculties: cross sectional analysis of international sample of universities | The BMJ

Abstract:  Objective To determine the presence of a set of pre-specified traditional and non-traditional criteria used to assess scientists for promotion and tenure in faculties of biomedical sciences among universities worldwide.

Design Cross sectional study.

Setting International sample of universities.

Participants 170 randomly selected universities from the Leiden ranking of world universities list.

Main outcome measure Presence of five traditional (for example, number of publications) and seven non-traditional (for example, data sharing) criteria in guidelines for assessing assistant professors, associate professors, and professors and the granting of tenure in institutions with biomedical faculties.

Results A total of 146 institutions had faculties of biomedical sciences, and 92 had eligible guidelines available for review. Traditional criteria of peer reviewed publications, authorship order, journal impact factor, grant funding, and national or international reputation were mentioned in 95% (n=87), 37% (34), 28% (26), 67% (62), and 48% (44) of the guidelines, respectively. Conversely, among non-traditional criteria, only citations (any mention in 26%; n=24) and accommodations for employment leave (37%; 34) were relatively commonly mentioned. Mention of alternative metrics for sharing research (3%; n=3) and data sharing (1%; 1) was rare, and three criteria (publishing in open access mediums, registering research, and adhering to reporting guidelines) were not found in any guidelines reviewed. Among guidelines for assessing promotion to full professor, traditional criteria were more commonly reported than non-traditional criteria (traditional criteria 54.2%, non-traditional items 9.5%; mean difference 44.8%, 95% confidence interval 39.6% to 50.0%; P=0.001). Notable differences were observed across continents in whether guidelines were accessible (Australia 100% (6/6), North America 97% (28/29), Europe 50% (27/54), Asia 58% (29/50), South America 17% (1/6)), with more subtle differences in the use of specific criteria.

Conclusions This study shows that the evaluation of scientists emphasises traditional criteria as opposed to non-traditional criteria. This may reinforce research practices that are known to be problematic while insufficiently supporting the conduct of better quality research and open science. Institutions should consider incentivising non-traditional criteria.

Biologer: an open platform for collecting biodiversity data

Abstract:  Background

We have developed a new platform named “Biologer” intended for recording species observations in the field (but also from literature resources and collections). The platform is created as user-friendly, open source, multilingual software that is compatible with Darwin Core standard and accompanied by a simple Android application. It is made from the user’s perspective, allowing everyone to choose how they share the data. Project team members are delegated by involved organisations. The team is responsible for development of the platform, while local Biologer communities are engaged in data collection and verification.

New information

Biologer has been online and available for use in Serbia since 2018 and was soon adopted in Croatia and Bosnia and Herzegovina. In total, we have assembled 536 users, who have collected 163,843 species observation records data from the field and digitalised 33,458 literature records. The number of active users and their records is growing daily. Out of the total number of gathered data, 89% has been made open access by the users, 10% is accessible on the scale of 10×10 km and only 1% is closed. In the future, we plan to provide a taxonomic data portal that could be used by local and national initiatives in Eastern Europe, aggregate all data into a single web location, create detailed data overview and enable fluent communication between users.

Biologer: an open platform for collecting biodiversity data

Abstract:  Background

We have developed a new platform named “Biologer” intended for recording species observations in the field (but also from literature resources and collections). The platform is created as user-friendly, open source, multilingual software that is compatible with Darwin Core standard and accompanied by a simple Android application. It is made from the user’s perspective, allowing everyone to choose how they share the data. Project team members are delegated by involved organisations. The team is responsible for development of the platform, while local Biologer communities are engaged in data collection and verification.

New information

Biologer has been online and available for use in Serbia since 2018 and was soon adopted in Croatia and Bosnia and Herzegovina. In total, we have assembled 536 users, who have collected 163,843 species observation records data from the field and digitalised 33,458 literature records. The number of active users and their records is growing daily. Out of the total number of gathered data, 89% has been made open access by the users, 10% is accessible on the scale of 10×10 km and only 1% is closed. In the future, we plan to provide a taxonomic data portal that could be used by local and national initiatives in Eastern Europe, aggregate all data into a single web location, create detailed data overview and enable fluent communication between users.

Open Entomology: Tips and Tools for Better Reproducibility in Your Research

“Many tools are available to make our work more reproducible, and I outline several in more detail in my paper, “A Guide and Toolbox to Replicability and Open Science in Entomology,” published in May in the open-access Journal of Insect Science. The article is part of a special “Open Entomology” group of papers published in the journal. I cowrote it with my advisor, Brian Aukema, Ph.D., of the University of Minnesota because there does not seem to be much open science communication targeted at the entomology community.

Open science practices and tools exist to make it easier for other people to pick up our work and see how we did it, which has the side effect of being beneficial to us individually! There is a common adage uttered in many statistics courses that captures this sentiment: “Your most important collaborator is you 6 months from now, and past you doesn’t answer emails.” At the start of my graduate work, I can’t tell you how many times I had to spend a few hours reacquainting myself with old data or analyses. If I had been aware of the open science movement and all the tools and practices available to me, I could have saved myself many headaches. Below are a few ways you can save yourself a headache, while simultaneously making your work more open and reproducible….

 

A community-maintained standard library of population genetic models | eLife

Abstract:  The explosion in population genomic data demands ever more complex modes of analysis, and increasingly these analyses depend on sophisticated simulations. Re-cent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to inconsistency and duplication of effort. This situation presents a major barrier to empirical researchers seeking to use simulations for power analyses of upcoming studies or sanity checks on existing genomic data. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here we describe a new resource, stdpopsim, that attempts to rectify this situation. Stdpopsim is a community-driven open source project, which provides easy access to a growing catalog of published simulation models from a range of organisms and supports multiple simulation engine backends. This resource is available as a well-documented python library with a simple command-line interface. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource.

 

JTEHM: The EMB Journey to Open Access – IEEE Journals & Magazine

Abstract:  The ultimate goal of engineering in medicine and biology (EMB) researchers is to improve medical care for patients and communities all over the world by providing a collaborative environment for engineer-scientists and clinicians. In order for this collaboration to occur, however, there must be a widely indexed platform that promotes communication among researchers across a spectrum of nations, both economically developed and underdeveloped, and between engineer-scientists and clinicians who are less likely to have access to IEEE Xplore. In response to this need, the EMB Society (EMBS) created the Journal of Translational Engineering in Health and Medicine (JTEHM), its first Gold Open Access (OA) journal. At its inception in 2012, JTEHM outlined a bold, comprehensive objective: Our unique mission—to bring together scientific researchers, practicing clinicians, and engineers to develop actionable, practical solutions for patients, families, and caregivers—requires open communication and free access

 

The NIH Preprint Pilot: A New Experiment for a New Era – NLM Musings from the Mezzanine

“Recognizing the growing interest in preprints, NLM is today launching the first phase of the NIH Preprint Pilot, which will test the viability of making preprints searchable in PubMed Central (PMC) and, by extension, discoverable in PubMed, starting with COVID-19 preprints reporting NIH-supported research.

To be clear, NLM is not building a preprint server for NIH investigators, nor are we developing a comprehensive preprint discovery resource. Rather, through this pilot, we plan to add a curated collection of preprints from eligible preprint servers to our established literature resources. In doing so, our goal is to improve scholarly communications by accelerating and expanding the findability of NIH research results.

With the encouragement of NIH leadership, NLM has been exploring ways to leverage its literature databases to help accelerate the discoverability and maximize the impact of NIH-supported research via preprints. The planned pilot builds on guidance released by NIH in March 2017, which encouraged NIH investigators to use preprints and other interim research products to speed the dissemination of research and enhance the rigor of their work through public comments and new scientific collaborations….”

Data-sharing recommendations in biomedical journals and randomised controlled trials: an audit of journals following the ICMJE recommendations | BMJ Open

Abstract:  Objective To explore the implementation of the International Committee of Medical Journal Editors (ICMJE) data-sharing policy which came into force on 1 July 2018 by ICMJE-member journals and by ICMJE-affiliated journals declaring they follow the ICMJE recommendations.

Design A cross-sectional survey of data-sharing policies in 2018 on journal websites and in data-sharing statements in randomised controlled trials (RCTs).

Setting ICMJE website; PubMed/Medline.

Eligibility criteria ICMJE-member journals and 489 ICMJE-affiliated journals that published an RCT in 2018, had an accessible online website and were not considered as predatory journals according to Beall’s list. One hundred RCTs for member journals and 100 RCTs for affiliated journals with a data-sharing policy, submitted after 1 July 2018.

Main outcome measures The primary outcome for the policies was the existence of a data-sharing policy (explicit data-sharing policy, no data-sharing policy, policy merely referring to ICMJE recommendations) as reported on the journal website, especially in the instructions for authors. For RCTs, our primary outcome was the intention to share individual participant data set out in the data-sharing statement.

Results Eight (out of 14; 57%) member journals had an explicit data-sharing policy on their website (three were more stringent than the ICMJE requirements, one was less demanding and four were compliant), five (35%) additional journals stated that they followed the ICMJE requirements, and one (8%) had no policy online. In RCTs published in these journals, there were data-sharing statements in 98 out of 100, with expressed intention to share individual patient data reaching 77 out of 100 (77%; 95% CI 67% to 85%). One hundred and forty-five (out of 489) ICMJE-affiliated journals (30%; 26% to 34%) had an explicit data-sharing policy on their website (11 were more stringent than the ICMJE requirements, 85 were less demanding and 49 were compliant) and 276 (56%; 52% to 61%) merely referred to the ICMJE requirements. In RCTs published in affiliated journals with an explicit data-sharing policy, data-sharing statements were rare (25%), and expressed intentions to share data were found in 22% (15% to 32%).

Conclusion The implementation of ICMJE data-sharing requirements in online journal policies was suboptimal for ICMJE-member journals and poor for ICMJE-affiliated journals. The implementation of the policy was good in member journals and of concern for affiliated journals. We suggest the conduct of continuous audits of medical journal data-sharing policies in the future.