Scientific publishing has undergone dramatic changes in recent decades; from print to online, and pay-walls to open access. Despite these changes, one aspect of the scientific article has yet to budge; the static graph.

Graphs and figures are the backbone of every research paper, and often provide a sanity check for discussion sections, where authors might wish to indulge in 'over interpretation' of their findings. “I think the figures are the most important part of the paper, because the abstract and body of the paper can be manipulated and shaped to tell a compelling story,” says Jeremy Borniger in a recent Science Magazine editorial (

But graphs and figures can also be misleading and unclear. More often than not, summary statistics, rather than raw data, are presented in graphs, with the details left to the whims of authors and editors. Summarizing data with means (as opposed to medians) and representing variability with standard errors (rather than confidence intervals) can influence how readers perceive the results and validity of a study. Clarity of a figure can also affect its impact. Experiments are rarely straightforward, often involving multiple groups and conditions over several sampling points, and capturing all of the important aspects of the data in one graph can be difficult for even the most seasoned of scientists.

Breaking free from the traditional static figure, a group led by Tracey L. Weissgerber at Mayo Clinic (Rochester, MN) developed an online graphical tool that allows authors to build interactive graphs for readers to explore their data (PLoS Biol. 14, e1002484; 2016). Using the group's free web-based tool, authors can upload their data sets and create dynamic graphs that can be used in publications and changed (by the readers) to present different summary statistics and selectively display subsets of the data.

Although the tool developed by Weissgerber et al. has its potential uses, it might be too early to say it signals a shift from static to interactive scientific publishing. There are several limitations to the tool (only small data sets can be used), and it's possible that interactive graphs could simply add more confusion to a paper. Particularly in the biological sciences, towards which this tool is aimed, data is often messy and researchers can spend a good amount of time sorting, analyzing and displaying their data in order to rescue the signal from the noise. Will interactive graphs add value, or more chaos?