Meet PubSweet – Coko’s free, open source framework for building state-of-the-art publishing platforms

“PubSweet is Coko’s free, open source framework for building state-of-the-art publishing platforms. PubSweet enables you to easily build a publishing platform tailored to your own needs. It is designed to be modular and flexible.

PubSweet can be used to rapidly create custom publishing systems. If the existing components do not completely meet your needs, you can focus development on building new components to provide just the new functionality required.

Join the PubSweet community and help us build a common resource of open components for publishing by contributing components back.

Documentation and further information about PubSweet can be found here. Below are Publishing platforms built with PubSweet….”

Meet PubSweet – Coko’s free, open source framework for building state-of-the-art publishing platforms

“PubSweet is Coko’s free, open source framework for building state-of-the-art publishing platforms. PubSweet enables you to easily build a publishing platform tailored to your own needs. It is designed to be modular and flexible.

PubSweet can be used to rapidly create custom publishing systems. If the existing components do not completely meet your needs, you can focus development on building new components to provide just the new functionality required.

Join the PubSweet community and help us build a common resource of open components for publishing by contributing components back.

Documentation and further information about PubSweet can be found here. Below are Publishing platforms built with PubSweet….”

Meet PubSweet – Coko’s free, open source framework for building state-of-the-art publishing platforms

“PubSweet is Coko’s free, open source framework for building state-of-the-art publishing platforms. PubSweet enables you to easily build a publishing platform tailored to your own needs. It is designed to be modular and flexible.

PubSweet can be used to rapidly create custom publishing systems. If the existing components do not completely meet your needs, you can focus development on building new components to provide just the new functionality required.

Join the PubSweet community and help us build a common resource of open components for publishing by contributing components back.

Documentation and further information about PubSweet can be found here. Below are Publishing platforms built with PubSweet….”

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

Abstract:  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.

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

Abstract:  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.

A Guest Post from Hindawi – Introducing Phenom Review: Open Source Scholarly Infrastructure by Hindawi – OASPA

“Peer review systems have developed over time to adjust to the changing requirements of different academic journals, pushing the legacy systems to the edge of their capabilities. Most importantly, an ongoing shift towards a more open culture in scholarly communications, including Open Access and Open Data, has created new challenges by bringing to light the inherent limitations of current proprietary infrastructure. 

Now, imagine a world where peer review systems were built in a way that serves the wider research community, reducing duplication of effort, increasing flexibility and editorial control without sacrificing transparency, and bringing the cost of publishing down. What would that world look like and how do we build it? 

This month, a second Hindawi journal will move onto the Phenom Review system, our new peer review platform built entirely open source. Phenom Review is part of Hindawi’s collaboration with Coko utilizing their open source PubSweet framework….”

Open source and open data

“There’s currently an ongoing debate about the value of data and whether internet companies should do more to share their data with others. At Google we’ve long believed that open data and open source are good not only for us and our industry, but also benefit the world at large.

Our commitment to open source and open data has led us to share datasets, services and software with everyone. For example, Google released the Open Images dataset of 36.5 million images containing nearly 20,000 categories of human-labeled objects. With this data, computer vision researchers can train image recognition systems. Similarly, the millions of annotated videos in the YouTube-8M collection can be used to train video recognition.

With respect to language processing, we’ve shared the Natural Questions database, which contains 307,373 human-generated questions and answers. We’ve also made available the Trillion Word Corpus, which is based on words used on public web pages, and the Ngram Viewer, that can be used to explore the more than 25 million books in Google Books. These collections can be used for statistical machine translation, speech recognition, spelling correction, entity detection, information extraction and other language research.

And these are only a few  examples of a much broader activity: Google AI currently lists 62 datasets of this sort that we’re making available to the research community.   …”

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.

Pubfair – A Framework for Sustainable, Distributed, Open Science Publishing Services

“This white paper provides the rationale and describes the high level architecture for an innovative publishing framework that positions publishing functionalities on top of the content managed by a distributed network of repositories. The framework is inspired by the vision and use cases outlined in the COAR Next Generation Repositories work, first published in November 2017 and further articulated in a funding proposal developed by a number of European partners.

By publishing this on Comments Press, we are seeking community feedback about the Pubfair framework in order to refine the functionalities and architecture, as well as to gauge community interest….

The idea of Pubfair is not to create another new system that competes with many others, but rather to leverage, improve and add value to existing institutional and funder investments in research infrastructures (in particular open repositories and open journal platforms). Pubfair positions repositories (and the content managed by repositories) as the foundation for a distributed, globally networked infrastructure for scholarly communication. It moves our thinking beyond the artificial distinction between green and gold open access by combining the strengths of open repositories with easy-to-use review and publishing tools for a multitude of research outputs….”