Data Visualization In Science & Beyond

Today, science & R&D social media channels have become just as cluttered as retail consumer channels. Just one of the many ways trying to get the word out on your research paper has come to parallel digital and online marketing. Scientists must now communicate the main points of their research engagingly, on top of effectively, if they hope to reface to the top (or at least get a social share).

According to Buffer, visual content is more than 40X more likely to get shared on social media than other types of content. In fact, infographics are Liked and shared on social media 3X more than other any other type of content. (MassPlanner) Authorea encourages the inclusion of data visualization in articles because its interactive element improves article visibility. Click here to read about How the Scientific Community Reacts to Newly Submitted Preprints.

Here is some more convincing (in case you needed it), as well as a few of our favorite papers that take advantage of interactive figures and sites that have drawn lots of traffic due to sharing of its data visualization.

Recap: Benefits of Data Visualization

1. Comprehend quickly. It's significantly faster to analyze information in graphical format (versus in spreadsheets). Extensive amounts of complicated data can be overwhleming, but correlations, patterns, trends, outliers, etc. are easier to spot with creative visual aids. By using graphical representations of information, especially if it a live, interactive figure. Scientists (as well as governments and businesses) are able to see large amounts of data in clear, cohesive ways – and draw sometimes surprising conclusion. 

2. Communicate effectively. The learning curve and jargon-issue often make cross-disciplinary collaboration difficult. Using charts, graphs or other visually impactful representations of data gets the message across quickly and engage new audiences in magificent ways.

Consider trying to understand Frank Drake’s Fermi Paradox which estimates the number of technological civilizations that might exist among the stars. (\(R\) is the annual rate of star formation, \(n_e\) is the average number of habitable planets, \(f_p\) is the fraction of stars that have planets, \(f_p\) is the fraction of stars that have planets, \(f_l\) is the fraction of habitable planets, \(f_i\) is the fraction of life-bearing planets that develop an intelligent life-form, and \(f_c\) is the fraction of intelligent life-forms that decide to communicate) \[\nonumber N =\underbrace{\overbrace{R}^{\approx10} \times \overbrace{f_p}^{\approx 1} \times \overbrace{n_e}^{\approx 0.2}}_{\sim 2} \times \underbrace{f_l \times f_i \times f_c \times L}_{?}\]

Although this particular equation is not too difficult to imagine, does the interactive chart below make it easier still?