Data-driven visualizations should be considered an interpretation of the data set they emulate rather than a direct and 100% accurate reflection. As digital scholars we look to find ways to comprehend these complex sets of data and are able to do so by visualizing them on a map. However, the simple fact that we use an outside tool, such as a map, is indicative of our own implementation to understand what has already been given. It is through these methods that we manipulate data to better construct the narrative we wish to tell. It is crucial for researchers to recognize and acknowledge this process as it is the duty of the data analyst to protect the integrity of the data set. It is just as easy to manipulate data and lie with a map as it is to go great lengths to prevent such incursion by implementing alien methodologies with the visualization process. They are not of equal moral repercussions but equally distort the data to fit our own comprehension.