Taking the journal article to the next level: Taylor & Francis partner with Code Ocean
30th January 2018
Taylor & Francis and Code Ocean announce a new partnership that enables researchers to easily share and run code, making journal articles more robust.
Readers will enjoy new interactivity where the Code Ocean widget is embedded within an article. They can run the code instantly within the page to easily reproduce and replicate data findings, so results can be verified and tested, and knowledge improved.
Authors can share their executable code with their data so that it can be visualized, augmented, and built upon. They will benefit from greater visibility of their code and can collaborate with others, with any open source programming language, plus MATLAB and Stata. Recognizing the use of code across many fields – from engineering to psychology – Taylor & Francis will implement Code Ocean across disciplines.
Leon Heward-Mills, Global Publishing Director at Taylor & Francis, said: “From displaying supplemental material to enabling the execution of code, our authors’ articles will be richer than ever before with this new partnership with Code Ocean. We recognize code as an important research output and encourage citations to the unique DOIs to increase attribution and enable researchers to get the credit they deserve.”
Simon Adar, CEO of Code Ocean, said: “Taylor & Francis’ readers will have immediate access to executable code, statistical analysis, and algorithms without having to install anything on their local computer, saving valuable time as they advance their own work.”
Authors retain their copyright for code and can authorize use with any open source license they choose. Code Ocean assigns a Digital Object Identifier (DOI) to the code when it is deposited to the platform and can be associated with the article at any stage of publication. Taylor & Francis will incorporate Code Ocean into its publishing workflow starting with a selection of journals in early 2018, with the goal to roll it out across journals that are rich in code and data.