Tag Archives: reproducibility

Reproducible Classification. Q&A on ShinyLearner & the CODECHECK certificate, pt. 2

- April 8, 2020

ShinyLearner

This week we showcased a new way of peer reviewing software, testing code in an independent manner and providing a CODECHECK “certificate of reproducible computation” when the results in the paper can be reproduced. We’ve written a post on the CODECHECK process featuring a Q&A with CODECHECK founder Stephen Eglan, and here we’ll provide a follow […]

Continue reading

0 comments

Certified Reproducibility. Q&A on ShinyLearner & the CODECHECK certificate, pt. 1

- April 7, 2020

CODECHECK certificate

Out today in GigaScience is ShinyLearner, a new tool to make it easier to perform benchmark comparisons of classification algorithms. This tool stands out by making this process super systematic and reproducible, and despite needing to interface with many different libraries and languages it uses software containers (and a CodeOcean demo) so end users don’t […]

Continue reading

0 comments

iMicrobe: Fostering Community-Driven Science and Data Discovery. Q&A with Bonnie Hurwitz

- August 2, 2019

In this data-driven era, research is faced with new challenges, from sharing, storing and accessing data, including how to better integrate data to answer big questions in science. With many data repositories available, it is hard to maintain them all – some repositories are forced to close – meaning loss of access to invaluable datasets.  […]

Continue reading

0 comments

GigaBlog meets Gigantum: Guest Post from Tyler Whitehouse, Dean Kleissas and Dav Clark

- June 20, 2019

At GigaScience as our focus is on reproducibility rather than subjective impact, it can be challenging at times to judge this in our papers. Targeting the “bleeding edge” of data-driven research, more and more of our papers utilise technologies, such as Jupyter notebooks, Virtual Machines, and Containers such as Docker. Working these tools in to […]

Continue reading

0 comments

Meet the GigaScience ICG Prize Winner, Pt. 2: Lisa Johnson Q&A

- December 14, 2018

ICG prize winner

Yesterday we published the winning paper of the second GigaScience prize, with additional detail and coverage in GigaBlog describing why we and the judging panel found it so novel. This was an impressively case study in reproducibility, reassembling & reannotating around 700 microbial eukaryotic transcriptomes to demonstrate this approach can aid in revealing new biologically relevant […]

Continue reading

0 comments

Research Parasites Wanted. Q&A with Casey Greene & Brian Byrd

- September 14, 2017

As a journal focussed on open science we are big promoters of research parasites (and research on parasites), and try to feeds them with open data and tools. It is therefore appropriate this is the second year GigaScience has supported and sponsored the Research Parasite awards. In one of our Q&As, organisers Casey Greene and […]

Continue reading

0 comments

Data Intensive Software Publishing & Sailing The Code Ocean. Q&A With Ruibang Luo.

- June 27, 2017

GigaScience is always trying to push the boundaries of how we disseminate reproducible research, and to adapt to the challenges of dealing with experiments become more data-intensive. We now showcase a new reproducible research platform we’ve been testing called Code Ocean, and have a Q&A with our Author Ruibang Luo on his experiences using it. […]

Continue reading

0 comments

Guardians of the Galaxy Workflow

- April 28, 2017

While the Guardians of the Galaxy film franchise has just released its second film, the GigaScience Galaxy series has just published its 10th, 11th and 12th papers. And all without the need of expensive CGI, although we do have our GigaGalaxy server on standby for additional computational support. For those not part of their large […]

Continue reading

0 comments

2016: An Eventful Year for GigaScience

- December 13, 2016

This year has been an eventful one, probably too eventful for many.  For GigaScience it has been eventful too, although fortunately in a much more positive way than many have experienced. While there are fears of us entering a “post-truth” era, there is more need than ever for our role as promoters of transparency, reproducibility and providers of cold-hard data. We celebrated our birthday with Mickey Mouse, and experienced many other milestones. On the technical front, this year we have brought you better integration with citable and updatable methods, bigger better and broader data types, and much more. In the tradition of end-of-year-introspection, here is a summary of some of our 2016 achievements as we continue to push the boundaries of innovative publishing of all research objects and reproducible research.

Continue reading

0 comments

The lowest common denominator: marketing science with jIF

- July 8, 2016

Our Editor in Chief Laurie Goodman gives her thoughts on the journal impact factor (jIF), and how we need to move beyond shallow, untransparent, gameable, out-of-date proxies that promote bad scientific practices.

Continue reading

2 comments