Tag Archives: reproducibility

Improvements for Man and Machine in Scientific Publishing

- October 5, 2022

interactive figures

Frictionless Data improves not just machine readability of scientific articles, but also enables humans to directly interact with the data within the article itself. A new article in GigaByte demonstrates frictionless data can help bring papers to life with interactive figures.

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From Frictionless Data to Interactive Visualisation

- September 1, 2022

Frictionless Data

A guest post from our summer data science intern Raniere Silva from Hong Kong City Uiniversity on his work on Frictionless Data and Interactive Visualisation

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Open Access Week 2021: GigaScience’s 10 Examples of Open

- October 29, 2021

Open Access Week 2021

For Open Access Week 2021 we look back over 10 of our favourite GigaScience papers providing examples of barriers we’ve tried to break for more open science.

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Gigantum Joins the Giga Reproducibility Toolkit

- June 2, 2021

Joining our Giga reproducibility toolkit is Gigantum, with a new paper being our first example using this platform for better collaboration, sharing and making reproducible research easier.

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Changing the Culture of Data Management and Sharing: A Report on the NASEM Workshop

- May 26, 2021

changing culture of data sharing

The National Academies of Sciences, Engineering, and Medicine (NASEM) hosted the virtual workshop “Changing the Culture of Data Management and Sharing”. Here we have a write-up of the event.

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GigaByte and River Valley Technologies push the boundaries of Executable Research Articles using Stencila and Code Ocean

- February 25, 2021

Executable Research Article

Today GigaByte publishes its first Executable Research Article (ERA), using technology from Stencila and Code Ocean to showcase interactive and executable versions of the figures.

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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 […]

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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 […]

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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.  […]

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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 […]

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