Plotly enables users to create dozens of different types of charts, networks and maps, all of which have a basic-level of interactivity where you can zoom, pan, rotate (for 3D plots) and hover your cursor over a data point to see its value(s). However, you can add also more interactivity by adding one or more advanced interactive features to your figures such as dropdown options, sliders and dynamic animations.
To mark the introduction of this new feature, we are reducing Article Processing Charges* for all articles with at least one Plotly figure by 50%. The submission deadline for the APC reduction is December 31st 2017. You can find more information about this and how to submit your Plotly figure at the end of this post.
We plan to feature published interactive figures throughout the year, including a roundup of the best visualizations in late January 2018 on our and Plotly’s blogs.
“Plotly is thrilled to be working with F1000Research as scientific publishing transitions to interactive, online graphics. Plotly charts keep the data and chart intrinsically linked – a major improvement over submitting charts as static image files. Open research is the future and Plotly is proud to lend cutting edge tools to open science publications.” Jack Parmer, Plotly CEO
Finding clarity in interactivity
Scientific publishing made the transition to the web almost two decades ago, and yet we still treat online articles as if they have the same physical limitations as their printed equivalents. We even still use terms such as ‘papers’ and ‘preprints’ to refer to works that only exist online. The same is of course true for elements within articles such as figures, which remain in the same static state since William Playfair drew the first statistical charts in 1786.
The entire purpose of a scientific figure is to help readers understand. When information is visualized graphically it is much easier to comprehend than a table densely packed with numbers or a long tract of text. However, biological and environmental systems are complex and it’s often difficult to represent in a static 2D object. This is especially true if the research involves many 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 so the figure fits with the paper’s margins. Being able to zoom, filter, and hover over individual data points to see their values, address these challenges and help readers to properly explore data at a much finer scale.
A very densely packed gene expression heatmap. Thankfully, you can select smaller regions of the chart, or use the zoom options in the top right, to get a better idea of what the heatmap shows. Chart from Plotly: https://plot.ly/ipython-notebooks/bioinformatics/
The same data, different visualizations
Interactive and animated 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.
This last point is most famously demonstrated by Hans & Ola Rosling’s Gapminder visualization, a dynamic graph showing the changes in life expectancy, income per person and population size for almost every country in the last 215 years. The graph helps tell a rich demographic story, of human progress and inequality in the global distribution of that progress. Their 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 that it represents. Hans’ Gapminder lectures might not have racked up the tens of millions of views had it been static (plus it would probably have to be split into several graphs to makes sense). Scientific articles are becoming increasingly difficult to read; used appropriately, interactive figures have the potential to help counteract this trend. This is especially true for communicating findings to policy makers and the wider general public.
A Plotly version of the Gapminder visualization, which shows global changes in wealth, health and population (represented by bubble size) over the last 55 years (N.B. the original visualization covers the last 215 years). Chart created by Plotly.
Partnering for flexibility and scalability
We are excited to partner with Plotly to help researchers visualize their data without the traditional constraints. Some scientific publishers, including us, have experimented with publishing interactive figures before; we even went as far as publishing the first ‘living’ figure. However, these efforts were custom-built attempts that were either scalable but not flexible, or flexible but not scalable. Plotly, which launched the same year as F1000Research, 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.
Make your data tell a story
We look forward to seeing your creative ways of visualizing your data using this new feature for our articles. In case you needed some inspiration, Plotly’s Modern Data and Medium blogs showcase lots of scientific and non-scientific interactive charts.
Instructions and FAQs for creating and submitting interactive Plotly figures to F1000Research can be found here.
*Articles over 8000 words of main text will still incur the long article surcharge of $1000. For the definition of ‘main text’, see our Article-Processing Charge page. Articles already published on F1000Research can be updated to include interactive figures, but they will not be eligible for the APC reduction.