Science Publishers Partner with Open Source Code Sharing Solutions to Strengthen Open Access to Empirical Data

Budapest Farmers Hack, Budapest, Hungary, September 1, 2012 | © Courtesy of Ars Electronica /Flickr.
Budapest Farmers Hack, Budapest, Hungary, September 1, 2012 | © Courtesy of Ars Electronica /Flickr.

Code Ocean, an Open Source data and algorithm sharing platform, assists large journal and book publishers to improve the reproducibility and transparency of scientific research results.

A Blog Article by Pablo Markin.

Global publishers, such as Taylor & Francis in January 2018, have been partnering with Code Ocean to add code sharing and execution capabilities to their journal articles. Code Ocean, a cloud-based platform for the computational reproducibility of research findings, enables scholars and publishes to have Open Access to empirical data on which academic articles are based. Since these capabilities can be expected to facilitate data interactivity, sharing and discovery, journal publishers have increasingly appreciated the possibility to run data analysis algorithms directly at the webpages at which scholarly articles are published on the Internet, which contributes to an independent verification of empirical research results.

Scientific authors sharing their data sets over Code Ocean also obtain improved visualization and collaboration opportunities within their respective scholarly communities and beyond. Since within Code Ocean data sets and algorithmic code receive their unique digital object identifiers (DOIs), these capabilities are also slated to improve the research output attribution and citation performance. Thereby, this Open Access platform for data sharing, itself building on other open source initiatives, such as R, has the potential to help scholars increase the visibility of their research by providing visualization tools for arcane scientific topics, such as quantitative plant morphology.

Likewise, collaborative computational code development also needs software execution and editing environments that support interactivity, such as New York-based Code Ocean and Plotly originating from Montreal, Canada, that have both free and paid-for use options. For these reasons, large-scale scholarly publishers, such as Cambridge University Press for its journal Political Science Research & Method in April 2018, have been partnering with Code Ocean as an Open Access repository for scientific data and code. This demonstrates the growing importance of Open Access not only for journal publishing, but also for fundamental research that is likely to gain from the transparency that Open Science entails, such as in the form of empirical results’ reproducibility, sharing and visibility.

Furthermore, cutting-edge, peer-reviewed research journals, such as Blockchain in Healthcare Today and Telehealth and Medicine Today have entered into a partnership with Code Ocean in July 2018, to improve the quality of their research findings and demonstrate leadership in their scientific communities globally, while accelerating the time it takes for research results to find market applications. Similarly, De Gruyter has partnered with Code Ocean in July 2018, in order to add to Studies in Nonlinear Dynamics and Econometrics, a peer-reviewed scientific journal, platform-independent capabilities of browser-based code sharing and execution.

In this manner, empirical data sets can be not only widely cited or shared, but also re-analyzed more easily than ever before, which reinforces the validity of the corresponding scientific results. In other words, Open Access to scientific data and algorithms can directly assist scientific progress by removing barriers to scholarly collaboration and research reproduction.

By Pablo Markin

Featured Image Credits: Budapest Farmers Hack, Budapest, Hungary, September 1, 2012 | © Courtesy of Ars Electronica /Flickr.

This post is based on an article that originally appeared in OpenScience, 02/08/2018,

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