![]() ![]() Our following 10 simple rules are dedicated to biologists and bioinformaticians who, while already being at the crossroads of many fields, want to venture further into the land of Data Visualization (“datavis” or “dataviz” for short). Given the gap between creating static figures and building a visualization tool from the ground up, it can be easy to get lost in this nontrivial journey. Unfortunately, most of the time, classic visual representations are insufficient to effectively communicate data complexity, and as O’Donoghue puts it, “ often dedicated communication approaches need to be developed to address specific data challenges, especially when conveying complex or unfamiliar ideas”. We are now used to seeing graphs and charts in our everyday lives and creating them for scientific papers as part of research. Coronavirus Disease 2019 (COVID-19) visualizations, good and bad, became omnipresent in the public debates, with interactive and dynamic visualization platforms like Nextstrain gaining a lot of popularity. Visualization is key for expanding and communicating knowledge to both specialized and broad audiences-after all, “ a picture is worth a thousand words,” right? That much has become clear during the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) outbreak when “ Flatten the curve!” turned into a catchier watchword than the usual “ Wash your hands!,” by referring to the related graphics rather than the health discourses themselves. ![]()
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