Catégorie : EN

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A cross-sectional description of open access publication costs, policies and impact in emergency medicine and critical care journals

Authors : Chante Dove, Teresa M. Chan, Brent Thoma, Damian Roland, Stevan R. Bruijns

Introduction

Finding journal open access information alongside its global impact requires access to multiple databases. We describe a single, searchable database of all emergency medicine and critical care journals that include their open access policies, publication costs, and impact metrics.

Methods

A list of emergency medicine and critical care journals (including citation metrics) was created using Scopus (Citescore) and the Web of Science (Impact Factor). Cost of gold/hybrid open access and article process charges (open access fees) were collected from journal websites.

Self-archiving policies were collected from the Sherpa/RoMEO database. Relative cost of access in different regions were calculated using the World Bank Purchasing Power Parity index for authors from the United States, Germany, Turkey, China, Brazil, South Africa and Australia.

Results

We identified 78 emergency medicine and 82 critical care journals. Median Citescore for emergency medicine was 0.73 (interquartile range, IQR 0.32–1.27). Median impact factor was 1.68 (IQR 1.00–2.39). Median Citescore for critical care was 0.95 (IQR 0.25–2.06).

Median impact factor was 2.18 (IQR 1.73–3.50). Mean article process charge for emergency medicine was $2243.04, SD = $1136.16 and for critical care $2201.64, SD = $1174.38. Article process charges were 2.24, 1.75, 2.28 and 1.56 times more expensive for South African, Chinese, Turkish and Brazilian authors respectively than United States authors, but neutral for German and Australian authors (1.02 and 0.81 respectively).

The database can be accessed here: http://www.emct.info/publication-search.html.

Conclusions

We present a single database that captures emergency medicine and critical care journal impact rankings alongside its respective open access cost and green open access policies.

URL : A cross-sectional description of open access publication costs, policies and impact in emergency medicine and critical care journals

DOI : https://dx.doi.org/10.1016%2Fj.afjem.2019.01.015

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Toward collaborative open data science in metabolomics using Jupyter Notebooks and cloud computing

Authors : Kevin M. Mendez, Leighton Pritchard, Stacey N. Reinke, David I. Broadhurst

Background

A lack of transparency and reporting standards in the scientific community has led to increasing and widespread concerns relating to reproduction and integrity of results. As an omics science, which generates vast amounts of data and relies heavily on data science for deriving biological meaning, metabolomics is highly vulnerable to irreproducibility.

The metabolomics community has made substantial efforts to align with FAIR data standards by promoting open data formats, data repositories, online spectral libraries, and metabolite databases.

Open data analysis platforms also exist; however, they tend to be inflexible and rely on the user to adequately report their methods and results. To enable FAIR data science in metabolomics, methods and results need to be transparently disseminated in a manner that is rapid, reusable, and fully integrated with the published work.

To ensure broad use within the community such a framework also needs to be inclusive and intuitive for both computational novices and experts alike.

Aim of Review

To encourage metabolomics researchers from all backgrounds to take control of their own data science, mould it to their personal requirements, and enthusiastically share resources through open science.

Key Scientific Concepts of Review

This tutorial introduces the concept of interactive web-based computational laboratory notebooks. The reader is guided through a set of experiential tutorials specifically targeted at metabolomics researchers, based around the Jupyter Notebook web application, GitHub data repository, and Binder cloud computing platform.

URL : Toward collaborative open data science in metabolomics using Jupyter Notebooks and cloud computing

DOI : https://doi.org/10.1007/s11306-019-1588-0

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Open Up – the Mission Statement of the Control of Impulsive Action (Ctrl-ImpAct) Lab on Open Science

Authors : Christina B. Reimer, Zhang Chen, Carsten Bundt, Charlotte Eben, Raquel E. London, Sirarpi Vardanian

The present paper is the mission statement of the Control of Impulsive Action (Ctrl-ImpAct) Lab regarding Open Science. As early-career researchers (ECRs) in the lab, we first state our personal motivation to conduct research based on the principles of Open Science.

We then describe how we incorporate four specific Open Science practices (i.e., Open Methodology, Open Data, Open Source, and Open Access) into our scientific workflow. In more detail, we explain how Open Science practices are embedded into the so-called ‘co-pilot’ system in our lab.

The ‘co-pilot’ researcher is involved in all tasks of the ‘pilot’ researcher, that is designing a study, double-checking experimental and data analysis scripts, as well as writing the manuscript.

The lab has set up this co-pilot system to increase transparency, reduce potential errors that could occur during the entire workflow, and to intensify collaborations between lab members.

Finally, we discuss potential solutions for general problems that could arise when practicing Open Science.

URL : Open Up – the Mission Statement of the Control of Impulsive Action (Ctrl-ImpAct) Lab on Open Science

DOI : http://doi.org/10.5334/pb.494

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Research data management and the evolutions of scholarship: policy, infrastructure and data literacy at KU Leuven

Authors : Tom Willaert, Jacob Cottyn, Ulrike Kenens, Thomas Vandendriessche, Demmy Verbeke, Roxanne Wyns

This case study critically examines ongoing developments in contemporary scholarship through the lens of research data management support at KU Leuven, and KU Leuven Libraries in particular.

By means of case-based examples, current initiatives for fostering sound scientific work and scholarship are considered in three associated domains: support for policy-making, the development of research infrastructures, and digital literacy training for students, scientists and scholars.

It is outlined how KU Leuven Libraries collaborates with partner services in order to contribute to KU Leuven’s research data management support network. Particular attention is devoted to the innovations that facilitate such collaborations.

These accounts of initial experiences form the basis for a reflection on best practices and pitfalls, and foreground a number of pertinent challenges facing the domain of research data management, including matters of scalability, technology acceptance and adoption, and methods for effectively gauging and communicating the manifold transformations of science and scholarship.

URL : Research data management and the evolutions of scholarship: policy, infrastructure and data literacy at KU Leuven

DOI : http://doi.org/10.18352/lq.10272

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Technical and social issues influencing the adoption of preprints in the life sciences

Authors : Naomi C Penfold, Jessica K Polka

Preprints are gaining visibility in many fields. Thanks to the explosion of bioRxiv, an online server for preprints in biology, versions of manuscripts prior to the completion of journal-organized peer review are poised to become a standard component of the publishing experience in the life sciences.

Here we provide an overview of current challenges facing preprints, both technical and social, and a vision for their future development, from unbundling the functions of publication to exploring different communication formats.

DOI : https://doi.org/10.7287/peerj.preprints.27954v1

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Contest models highlight inherent inefficiencies of scientific funding competitions

Authors : Kevin Gross, Carl T. Bergstrom

Scientific research funding is allocated largely through a system of soliciting and ranking competitive grant proposals. In these competitions, the proposals themselves are not the deliverables that the funder seeks, but instead are used by the funder to screen for the most promising research ideas.

Consequently, some of the funding program’s impact on science is squandered because applying researchers must spend time writing proposals instead of doing science. To what extent does the community’s aggregate investment in proposal preparation negate the scientific impact of the funding program?

Are there alternative mechanisms for awarding funds that advance science more efficiently? We use the economic theory of contests to analyze how efficiently grant proposal competitions advance science, and compare them with recently proposed, partially randomized alternatives such as lotteries.

We find that the effort researchers waste in writing proposals may be comparable to the total scientific value of the research that the funding supports, especially when only a few proposals can be funded.

Moreover, when professional pressures motivate investigators to seek funding for reasons that extend beyond the value of the proposed science (e.g., promotion, prestige), the entire program can actually hamper scientific progress when the number of awards is small.

We suggest that lost efficiency may be restored either by partial lotteries for funding or by funding researchers based on past scientific success instead of proposals for future work.

URL : Contest models highlight inherent inefficiencies of scientific funding competitions

DOI : https://doi.org/10.1371/journal.pbio.3000065

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How much research shared on Facebook is hidden from public view? A comparison of public and private online activity around PLOS ONE papers

Authors : Asura Enkhbayar, Stefanie Haustein, Germana Barata, Juan Pablo Alperin

Despite its undisputed position as the biggest social media platform, Facebook has never entered the main stage of altmetrics research. In this study, we argue that the lack of attention by altmetrics researchers is not due to a lack of relevant activity on the platform, but because of the challenges in collecting Facebook data have been limited to activity that takes place in a select group of public pages and groups.

We present a new method of collecting shares, reactions, and comments across the platform-including private timelines-and use it to gather data for all articles published between 2015 to 2017 in the journal PLOS ONE.

We compare the gathered data with altmetrics collected and aggregated by Altmetric. The results show that 58.7% of papers shared on the platform happen outside of public view and that, when collecting all shares, the volume of activity approximates patterns of engagement previously only observed for Twitter.

Both results suggest that the role and impact of Facebook as a medium for science and scholarly communication has been underestimated. Furthermore, they emphasise the importance of openness and transparency around the collection and aggregation of altmetrics.

URL : https://arxiv.org/abs/1909.01476