PLOS, Center for Open Science, and Flu Lab collaborate to Open Influenza Research | The Official PLOS Blog

“The Flu Lab, the Center for Open Science (COS) and PLOS have announced a three-pronged collaboration to open influenza research and help tackle this perennial and massive threat to global health. PLOS ONE is publishing peer-reviewed research arising from a call for proposals funded and coordinated by the Flu Lab and COS. This will form part of a special collection, alongside commentaries and perspectives published by PLOS Biology and PLOS Pathogens.

The focus of these three prongs is emptying, and publishing, the “file drawer” of influenza research and doubling down on ensuring verification and reproducibility of this research, two notions that should never be in question for such a potentially devastating health risk. At PLOS we know that all science—including negative outcomes—informs the scientific record and this initiative will reduce the time and resources needed by current and future researchers to further advance the field….”

Technical and social issues influencing the adoption of preprints in the life sciences [PeerJ Preprints]

Abstract:  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.

Technical and social issues influencing the adoption of preprints in the life sciences [PeerJ Preprints]

Abstract:  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.

Opening Influenza Research

“Reproducible evidence is a signature strength of science, yet replications and negative results rarely appear in journals because cultural incentives emphasize novelty over verification (Nosek, Spies, & Motyl, 2012). These behaviors must be addressed and amended in all areas of research, and especially as they relate to findings that can dramatically improve public health and education.

 

The Public Library of Science (PLOS), the Center for Open Science (COS), and Flu Lab are collaborating to bypass these detrimental incentives and to encourage the availability of all findings that contribute to the influenza body of knowledge. 

Through the Opening Influenza Research project, we invite the influenza research community to “empty the file drawers” and contribute to a thorough aggregation of open and accessible findings….”

Opening Influenza Research

“Reproducible evidence is a signature strength of science, yet replications and negative results rarely appear in journals because cultural incentives emphasize novelty over verification (Nosek, Spies, & Motyl, 2012). These behaviors must be addressed and amended in all areas of research, and especially as they relate to findings that can dramatically improve public health and education.

 

The Public Library of Science (PLOS), the Center for Open Science (COS), and Flu Lab are collaborating to bypass these detrimental incentives and to encourage the availability of all findings that contribute to the influenza body of knowledge. 

Through the Opening Influenza Research project, we invite the influenza research community to “empty the file drawers” and contribute to a thorough aggregation of open and accessible findings….”

The Genomics Research and Innovation Network: creating an interoperable, federated, genomics learning system | Genetics in Medicine

Abstract:  Purpose:

Clinicians and researchers must contextualize a patient’s genetic variants against population-based references with detailed phenotyping. We sought to establish globally scalable technology, policy, and procedures for sharing biosamples and associated genomic and phenotypic data on broadly consented cohorts, across sites of care.

Methods

Three of the nation’s leading children’s hospitals launched the Genomic Research and Innovation Network (GRIN), with federated information technology infrastructure, harmonized biobanking protocols, and material transfer agreements. Pilot studies in epilepsy and short stature were completed to design and test the collaboration model.

Results

Harmonized, broadly consented institutional review board (IRB) protocols were approved and used for biobank enrollment, creating ever-expanding, compatible biobanks. An open source federated query infrastructure was established over genotype–phenotype databases at the three hospitals. Investigators securely access the GRIN platform for prep to research queries, receiving aggregate counts of patients with particular phenotypes or genotypes in each biobank. With proper approvals, de-identified data is exported to a shared analytic workspace. Investigators at all sites enthusiastically collaborated on the pilot studies, resulting in multiple publications. Investigators have also begun to successfully utilize the infrastructure for grant applications.

Conclusions

The GRIN collaboration establishes the technology, policy, and procedures for a scalable genomic research network.

The Genomics Research and Innovation Network: creating an interoperable, federated, genomics learning system | Genetics in Medicine

Abstract:  Purpose:

Clinicians and researchers must contextualize a patient’s genetic variants against population-based references with detailed phenotyping. We sought to establish globally scalable technology, policy, and procedures for sharing biosamples and associated genomic and phenotypic data on broadly consented cohorts, across sites of care.

Methods

Three of the nation’s leading children’s hospitals launched the Genomic Research and Innovation Network (GRIN), with federated information technology infrastructure, harmonized biobanking protocols, and material transfer agreements. Pilot studies in epilepsy and short stature were completed to design and test the collaboration model.

Results

Harmonized, broadly consented institutional review board (IRB) protocols were approved and used for biobank enrollment, creating ever-expanding, compatible biobanks. An open source federated query infrastructure was established over genotype–phenotype databases at the three hospitals. Investigators securely access the GRIN platform for prep to research queries, receiving aggregate counts of patients with particular phenotypes or genotypes in each biobank. With proper approvals, de-identified data is exported to a shared analytic workspace. Investigators at all sites enthusiastically collaborated on the pilot studies, resulting in multiple publications. Investigators have also begun to successfully utilize the infrastructure for grant applications.

Conclusions

The GRIN collaboration establishes the technology, policy, and procedures for a scalable genomic research network.

Workflow systems turn raw data into scientific knowledge

“Finn is head of the sequence-families team at the European Bioinformatics Institute (EBI) in Hinxton, UK; Meyer is a computer scientist at Argonne National Laboratory in Lemont, Illinois. Both run facilities that let researchers perform a computationally intensive process called metagenomic analysis, which allows microbial communities to be reconstructed from shards of DNA. It would be helpful, they realized, if they could try each other’s code. The problem was that their analytical ‘pipelines’ — the carefully choreographed computational steps required to turn raw data into scientific knowledge — were written in different languages. Meyer’s team was using an in-house system called AWE, whereas Finn was working with nearly 9,500 lines of Python code.

“It was a horrible Python code base,” says Finn — complicated, and difficult to maintain. “Bits had been bolted on in an ad hoc fashion over seven years by at least four different developers.” And it was “heavily tied to the compute infrastructure”, he says, meaning it was written for specific computational resources and a particular way of organizing files, and thus essentially unusable outside the EBI. Because the EBI wasn’t using AWE, the reverse was also true. Then Finn and Meyer learnt about the Common Workflow Language (CWL).

CWL is a way of describing analytical pipelines and computational tools — one of more than 250 systems now available, including such popular options as Snakemake, Nextflow and Galaxy. Although they speak different languages and support different features, these systems have a common aim: to make computational methods reproducible, portable, maintainable and shareable. CWL is essentially an exchange language that researchers can use to share pipelines for whichever system. For Finn, that language brought sanity to his codebase, reducing it by around 73%. Importantly, it has made it easier to test, execute and share new methods, and to run them on the cloud….”

JMIR Preprints #16078: Transparent, Reproducible, and Open Science Practices of Published Literature in Dermatology Journals: A Cross-sectional Analysis

Abstract:  Background:

Reproducible research is a foundational component for scientific advancements, yet little is known regarding the extent of reproducible research within the dermatology literature.

Objective:

We sought to determine the quality and transparency of the literature in dermatology journals by evaluating for the presence of 8 indicators of reproducible and transparent research practices.

Methods:

By implementing a cross-sectional study design, we conducted an advanced search of publications in dermatology journals from the National Library of Medicine catalog. Our search included articles published between January 1, 2014 to December 31, 2018. After generating a list of eligible dermatology publications, we then searched for full-text PDF versions using Open Access Button, Google Scholar, and/or PubMed. Each publication was analyzed for eight indicators of reproducibility and transparency, using a pilot-tested Google Form.

Results:

After exclusions, 127 studies with empirical data were included in our analysis. The majority of publications (113, 89%) did not provide unmodified, raw data used to make computations, 124 (98%) failed to make complete protocols available, and 126 (99%) did not include step-by-step analysis scripts.

Conclusions:

Our sample of studies published in dermatology journals do not appear to include sufficient detail to be accurately and successfully reproduced in their entirety. Solutions to increase the quality, reproducibility, and transparency of dermatology research are warranted. More robust reporting of key methodological details, open data sharing, and stricter standards journals impose on authors regarding disclosure of study materials might help to better the climate of reproducible research in dermatology.

Perspectives From Authors and Editors in the Biomedical Disciplines on Predatory Journals: Survey Study | Journal of Medical Internet Research

Abstract:  Background: Predatory journals fail to fulfill the tenets of biomedical publication: peer review, circulation, and access in perpetuity. Despite increasing attention in the lay and scientific press, no studies have directly assessed the perceptions of the authors or editors involved.

Objective: Our objective was to understand the motivation of authors in sending their work to potentially predatory journals. Moreover, we aimed to understand the perspective of journal editors at journals cited as potentially predatory.

Methods: Potential online predatory journals were randomly selected among 350 publishers and their 2204 biomedical journals. Author and editor email information was valid for 2227 total potential participants. A survey for authors and editors was created in an iterative fashion and distributed. Surveys assessed attitudes and knowledge about predatory publishing. Narrative comments were invited.

Results: A total of 249 complete survey responses were analyzed. A total of 40% of editors (17/43) surveyed were not aware that they were listed as an editor for the particular journal in question. A total of 21.8% of authors (45/206) confirmed a lack of peer review. Whereas 77% (33/43) of all surveyed editors were at least somewhat familiar with predatory journals, only 33.0% of authors (68/206) were somewhat familiar with them (P<.001). Only 26.2% of authors (54/206) were aware of Beall’s list of predatory journals versus 49% (21/43) of editors (P<.001). A total of 30.1% of authors (62/206) believed their publication was published in a predatory journal. After defining predatory publishing, 87.9% of authors (181/206) surveyed would not publish in the same journal in the future.

Conclusions: Authors publishing in suspected predatory journals are alarmingly uninformed in terms of predatory journal quality and practices. Editors’ increased familiarity with predatory publishing did little to prevent their unwitting listing as editors. Some suspected predatory journals did provide services akin to open access publication. Education, research mentorship, and a realignment of research incentives may decrease the impact of predatory publishing.