There are many different ways to visualize data, from a simple bar graph to a detailed infographic. When displaying any type of data the first thing you should ask yourself is, “How do I display my data for maximum impact?” This will directly influence the type of figure you use to present your information. Often in research-heavy fields there are restrictions on the way a data set can be formated, especially for publishing. Even still, the elements of design should always be taken into consideration.
In all cases, readability and clarity are the two top things to be aware of. Anything that looks cluttered can confuse or distract your audience and is to be avoided. Stay away from any weird fonts or busy patterns. All of your visuals should be consistent, with the same color scheme, text font and size. This makes all the data being presented more of a cohesive work. Also make sure you graphic has appropriate contrast so each element stands out. Be sure to title and label all parts of the graphic clearly; which includes removing any redundant information.
The most common way to display a large amount of data is to use a table. Always check to make sure that the labels are easily readable and line up properly with the data. By being aware of visual clutter and clearly naming all data categorizes, a large amount of data can be quickly and neatly shown to an audience. There are situations where it is useful to use a table in addition to another type of visual, such as a line graph.
All graphs have a vertical “Y” axis and a horizontal “X” axis, both should always have a label. A legend describing the graph should be also always be included. This takes the place of a title when preparing figures for journal publication. Bar graphs are best used to display differences in one variable among a group. A related graph called a histogram shows frequencies of data points along a axis of that variable.
X,Y scatterplots plot data points with two variables to show a relationship between them. The dependent variable is typically displayed on the “Y” axis and the independent on the “X” axis. Computer software can then calculate an equation fitted to your data set which can be used to predict trends. A X,Y line graph works similarly with two variables, but instead just draws lines between the data points. Connecting the dots instead of mathematically modeling all of them. Error bars can be included around the data points to show a range of uncertainty in many different types of figures.
There are many other ways data can be displayed including photographs, which in research publications are subject to the same guidelines as other figures. In general all data being displayed for a research purpose should have a clear purpose and be easy to read. By keeping these ideas in mind you can give the data you’ve worked so hard to collect the best possible presentation.
Chelsea Babcock is currently majoring in biochemistry at the University of South Florida. In addition to her schoolwork she tutors biology, chemistry, and mathematics through USF. Before starting her science career she graduated from the honors art and design program at Booker High School, Visual and Performing Arts Academy.