We wish to support reproducible document formats from authoring through publication. A valuable step forward would be to enable researchers to publish the code and data behind their analyses in a form that can be easily examined, and thereby create figures and whole documents where users can faithfully reproduce key aspects of the work.

As such, we are embarking on a project with Substance and Stencila to develop the technology required to support the Reproducible Document through authoring, sharing and publication.

We will have succeeded once any scientist can easily create a standardised reproducible publication and submit it to a journal. Together with our supporters we are building an open source toolset, to be used by authors, journals and readers.

— Michael Aufreiter, Substance

The creation of an open standard for the exchange, submission and publication of reproducible documents is critical for widespread adoption by academic publishers, and will be beneficial for the discovery and persistence of research reported in this form. Therefore, a key output of this project will be a Reproducible Document Exchange Format, which will allow the data, code and computed outputs (graphs, statistical results, tables) embedded in a reproducible document to be recognised and presented online as an enhanced version of the published research article. In order to do this, Substance is investigating how to represent these assets in JATS XML, the publishing standard through which research manuscripts are processed through the publishing workflow:

<fig id="f1"> <caption> <title>Figure 1</title> <p>Biodiversity on Mars</p> </caption> <alternatives> <code executable="yes" specific-use="input" language="mini"> bars(counts_by_species) </code> <code specific-use="output" language="json"> { "execution_time": 322, "value_type": "plot-ly", "value": {...} } </code> <!-- static version for existing JATS toolchains --> <graphic xlink:href="89f8b53e361f.svg"/> </alternatives> </fig>

This complements Substance's work to develop Texture, an XML-based text editor for authoring, and contributions towards eLife Lens, the side-by-side article reader.

We recognise that these computational research tools are not the mainstay of all life sciences research. Efforts to encourage greater adoption of reproducible research methods by researchers who are less familiar with programming are welcomed to aid interdisciplinary communications, and facilitate those who wish to learn code-based research practises. Substance and eLife are already supporting the development of Stencila, an authoring platform and execution engine for reproducible documents that is targeted at researchers who are less comfortable with programming and more familiar with Microsoft Word and Excel.

The calls for research to be reproducible are growing louder. But many of the tools for reproducible research are code focussed and can be intimidating to non-coders. We’re creating tools with the same intuitive, visual interfaces that researchers are familiar with but built from the ground up with reproducibility in mind. We want to create a platform that is accessible to a greater range of scientists - without dumbing down their research or restricting their ability to learn new computational methods.

— Nokome Bentley, Stencila

With intuitive text and spreadsheet authoring interfaces capable of producing XML documents, Stencila offers a platform to feed directly into the reproducible document publishing workflow.

In addition, we are interested in developing features that will enable readers to make the most of this enhanced article. Above all, the task of replicating an author’s original research – at least from a computational and analysis angle – should be trivial from the reader’s standpoint.

To meet the needs of researchers, the project will need to address several key technological considerations, including: