How Data Visualization Helps Us Understand Science

Data Visualization in Science

The more information scientists gather about the world around us, the more unmanageable all that data becomes. That’s why data visualization has become so essential in helping us understand science.

Data can take countless forms across the array of scientific fields, so for this industry we must define data visualization broadly as well. In the field of paleontology, a lifelike rendering of what a dinosaur may have looked like — from size and coloring to feathers vs. scales — contains a huge amount of data, even if not all of this data can be measured in a numerical way. Scientific visualizations like this translate information into something that viewers can understand instantly. In astronomy, drawings or computer renderings of celestial bodies such as neutron stars or galaxies are also based on mountains of information. Meanwhile, data visualization in the form of graphs or charts is of course just as important in the scientific world.

Let’s take a look at a few of the ways that science is visualizing data and information, and how these strategies are helping the nonscientists among us understand science on a deeper and more meaningful level.

This is the fourth post in a series called Data Visualization in Industry. If you’re interested in reading more, check out our other articles in the series:

Graphs and Charts That Speak Volumes

Data visualization is perhaps most powerful in scientific applications when it is used to discover meaning in a fog of data. Graphs help us recognize trends and patterns much more quickly, and help us make comparisons. Without them, it might be hard to understand what’s really important in the data we’re looking at.

Today, scientists rely a great deal on graphs, charts, scanner plots, curve plots, and image annotations. These visualizations can update in real time with new data if they have interactive capability. Scientists also use computer-simulated data visualizations, model rendering, and 3D computer rendering. Some of the simulations that scientists run using their datasets can require the power of multiple supercomputers to be carried out.

An October 2018 article in ScienceDaily reports a new development in the use of charts in science, medicine, and potentially across other industries as well. Tufts University and Columbia Engineering computer scientists reported developing a method called “Pixel Approximate Entropy.” The goal? To measure the complexity of a data visualization and simplify that visualization for ease of reading if necessary.

“In fast-paced settings, it is important to know if the visualization is going to be so complex that the signals may be obscured,” explained Eugene Wu, an assistant professor of computer science and coauthor of a paper on this method. For instance, in high-stakes medical settings, such as when physicians are reading EEGs in emergency rooms, the most important information needs to stand out quickly in a visualization, which can be obscured by a static of unnecessary data.

Such developments could further empower scientists to discover trends and patterns in their data.

Illustrations That Help Us Understand Science

Visualizing large quantities of complex information in a way that’s elegantly simple is no easy task. That’s why Killer differentiates visual communication from design: the former is a specialized skill that involves juggling both form and function, so that you create something that’s not only beautiful, but meaningful as well.

The same holds true for scientific visualization. You don’t just need to be a designer to create an accurate depiction of what a Spinosaurus might have looked like. You also need to be able to interpret the scientific information that you’re given about not just the animal itself, but the environment in which it lived. Only with this level of understanding will you be able to design an accurate portrayal of the dinosaur in its native environment.

All of this goes to show why Scientific and Information Visualization are their own fields of design — “branches of computer graphics and user interface design that are concerned with presenting data to users, by means of images,” as ScienceDaily explains it.

A whole community has built up around people who specialize in the accurate visualization of paleontological data. You can check out their designs and discussions by searching for the #SciComm hashtag on Twitter and Instagram.

These designers will often work closely alongside a scientist to create their visualization starting with a skeletal reconstruction, then building up from there until the animal’s full body has been reconstructed. Check out this visualization, for example, of an early relative of the crocodile; read the caption to see just how much the designer had to know before creating the illustration:

Models of the Microscopic World

Software programs that enable scientists and designers to visualize microbiological forms and molecules in interactive interfaces are becoming more common. These interactive visualizations are used in cheminformatics and bioinformatics to not only train personnel, but to interpret data collected in a laboratory.

The field of molecular graphics is closely tied with the development of new treatments and technologies. These interactive graphics actually help scientists test new ideas and possibilities. For example, in a 2007 article for the journal Comprehensive Medicinal Chemistry II, medicinal chemistry professor Donald J. Abraham talks about structure-based drug design. This is a method of inventing new medicines that uses not only advances in computational chemistry, but also molecular modeling software. Such tools allow scientists to understand atomic interactions on a deeper level by visualizing a broad range of possibilities.

Applications in Science Education

Abraham’s article notes that the use of such visualization tools as AstexViewer “drastically simplifies the time-consuming task of preparing figures for talks and publications.” Scientific data visualization, then, is an essential part of science education, and brings key information to the masses more efficiently and in a more comprehensible form.

Check out this visualization of a tardigrade, which allows a clearer view of these wondrous little animals and sparks fascination in just about anyone who sees it:

Inspiring a sense of wonder is one of the most important goals of science education, and therefore an essential role of data visualization in science.

These are just a few of the most cutting-edge ways that data visualization is being used in scientific contexts. From these examples, it should be easy to see that the future holds myriad new possibilities for the convergence of science and design.

Erin McCoy

Author Erin McCoy

Erin McCoy is director of content marketing and public relations at Killer Visual Strategies. She earned her BA in Spanish with minors in French and Russian, and holds 2 master’s degrees from the University of Washington: an MFA in creative writing and an MA in Spanish literature. She has won nearly 2 dozen awards in photojournalism, and has dedicated those skills to boosting Killer’s brand recognition and thought leadership in visual communication. Since Erin took on her marketing/PR role, Killer has been named a member of the Inc. 5000 for 4 years in a row; has been featured in such publications as Inc., Forbes, Mashable, and the Huffington Post; and has been invited to present at such conferences as SXSW and SMX Advanced.

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