Researchers can now publish interactive Plotly figures in F1000
This article was contributed by Thomas Ingraham, publishing editor at F1000Research.
F1000Research, an open research publishing platform, is excited to announce that researchers can now publish interactive figures created with Plotly in the online version of their publications; a first for a scientific publisher. To encourage researchers to embrace interactivity, F1000 is reducing the open access publishing charges for all articles containing an interactive Plotly figure by 50% (authors need to submit by December 31st 2017 to be eligible for the reduction). The best will be featured on both F1000Research and Plotly throughout the year. A full overview of the initiative can be found here and details on how to submit Plotly figures to F1000Research can be found here at the F1000 blog.
So long, static charts! 👋
Why are we making a concerted effort to encourage researchers to publish interactive figures? Well, scientific publishing made the transition to the web almost two decades ago, and yet the research community still treats online articles as if they have the same physical limitations as their printed equivalents. We even still use terms such as ‘papers’ and ‘pre-prints’ to refer to works that only exist online.
The same is of course true for elements within articles, including figures. They may now be in digital formats rather than drawn freehand, but graphs still remain in the same static state since William Playfair created the first statistical charts in 1786.
F1000Research publishes articles in the life sciences and related disciplines. Since we launched in 2012, we have worked hard to crumple the idea that online publications have the same properties as paper. We were the first to implement a versioning system so authors can update their articles, and everything we publish is fully open, with all articles open access, and associated data, code and signed peer review reports made publically available for others to use. None of this is possible in the un-linkable paper pages of a space-constrained print journal.
We have also experimented with publishing interactive figures (as have a small number of other academic publishers), and we went as far as publishing the first ‘living’ figure in a research article. However, all efforts to date have been custom-built attempts that were either scalable but not flexible with regards to figure type, or flexible but not scalable. Plotly, which launched the same year as us, has built a platform that excels at both, with elegant aesthetics as an added bonus. So, we are leaving it to the data visualization experts and focusing our efforts on supporting their tech.
The founding Plotly team also has scientific publishing roots. Alex Johnson, Plotly’s CTO, won the Newcomb Cleveland Prize for his paper coauthored in Science during his PhD. Jack Parmer, CEO, published his first physics paper at age 21. The Plotly team is dedicated to helping bring scientific publishing into an era of rich, interactive figures that enhance reproducibility and insight.
Finding clarity in interactivity
The entire purpose of a scientific figure is to help readers understand; information visualized graphically is much easier to comprehend than a table densely packed with numbers or a long tract of text.
That said, biological and environmental systems are complex and so they can still be difficult to represent in a static 2D figure. This is especially true if the research involves lots of variables or large quantities of data. Many readers of scientific articles will have struggled to decipher over-plotted charts, or network graphs crowded with hundreds of nodes all labelled in an unreadable font size just so the figure fits with the paper’s margins. Being able to zoom, filter, and hover over individual data points to see their values, which all Plotly figures have by default, addresses these challenges and helps readers to properly explore data at a much finer scale.
Interactive and dynamic scientific figures have other advantages over their static counterparts. If there are several ways to visualize your data, you no longer have to choose just one; if you want to demonstrate how different input values affect a model’s outputs, you can achieve this graphically; and if you want to represent the interplay of many variables, you can make use of dynamic changes in the size, color, shape, and location of data points over time.
Perhaps the greatest benefit is that interactivity and dynamism help graphs grab your attention. Hans Rosling’s lectures on the Gapminder visualization would certainly not have racked up the 10s of millions of views had it been static (plus it would probably have to be split into several graphs to makes sense). The use of color, size changes and movement help us to emotionally engage with the data, which in turn helps us appreciate the real-world processes they represents. Scientific articles are becoming increasingly difficult to read; used appropriately, interactive figures have the potential to help counteract this trend. This is especially true when communicating findings to policy makers and the wider general public.
The tech has been developed and the benefits are clear, so why should we be content with static figures?