As students and researchers working on long-term projects, we often have to wrangle with complex datasets. Producing thoughtful conclusions from such data is something we have been trained to do for many years. Likewise, our keen eyes have been trained to interpret conclusions when they are published within the scientific literature. But, the day will come when it is time to report information to audiences outside of the scientific community. The same jargon and quantitative results used to increase comprehension within scientific literature will likely decrease comprehension when reported to a general audience!

So, what is a solution to this problem??? My answer is to use….

Well… maybe not quite as snazzy as WordArt… but the inclusion of purposeful visuals will help audiences understand your message and also keep them engaged. Furthermore, a nice visual can always be added to a thesis or powerpoint presentation to help communicate your ideas effectively.

To bring this idea home, take a look at the images below:

Presenting your relational database to the general public will leave you looking like the over-caffeinated, sleep-deprived PhD archetype you are trying to separate yourself from (image: http://knowyourmeme.com/memes/pepe-silvia).

The first image is of my current relational database for invasive mammalian pests throughout New Zealand’s offshore islands. The second image is of how I’ll be perceived if I try to explain it to anyone else. Although informative, the database’s complexity makes it difficult for others to understand. The time required to explain its “in’s and out’s” will ultimately take away from the message I am trying to get across. As a solution to this issue, I decided to amend my database to ArcMap as a way of making it visual (see the picture below).

An ArcMap image of New Zealand’s Hauraki Gulf. The different coloured polygons and data-points represent different features of the implemented database. I think we can all agree that this is much easier to explain than the other image!

Not only is it more interesting to look at, but the visual representation of my data clearly and concisely demonstrates what is going on (it’d help if I put a legend on the figure, though. Semantics.). Doing so has helped me spatially understand my dataset, too. instead of looking at lines of code, the visual form has provided context with which assist in the identification of geographic patterns.

Zach Carter is a PhD student in the University of Auckland School of Biological Sciences. He is developing eradication prioritisation models to assist in the removal of invasive mammals from New Zealand. He is supervised by James Russell and George Perry.