Julia Grippo

The introductory chapter of Healy’s Data Visualization for Social Science, narrates the importance of data visualization. The chapter explores good and bad uses of data visualization in an attempt to demonstrate the overall uses and applications of data visualization. I believe that Healy opens up with a beautiful interpretation about how to approach data visualization in stating, "it is better to begin by thinking about the relationship between the structure of your data and the perceptual features of your graphics." I agree with Healy. It is important to think about what design elements you can use to best narrate the story that your data is trying to tell. The chapter provided insights about how design factors such as color, line, and shape can be used to establish a hierarchy of information within these visualizations. The chapter highlighted the relationship between the structure of data and the perceptual features of the graphics. Overall, this chapter serves to show how visualization allows us to explore, understand, and explain data.

Within the “Bad Data” portion of the reading, Healy discusses how some graphics take on a misleading nature. In this way, creators have the ability to shift the narrative surrounding the data. They can use small changes of value on an axis to create a misleading depiction of the information. Therefore, I find it fascinating to think how something rooted in fact can take on a distorted truth by means of manipulating the axes. This ties in with Healy’s ideas of how aesthetic, substantive, and/or perceptual issues can arise within data visualization. In this way, it is interesting to view the ethics of data visualization. Is it possible that “fake news” can exist within something that is supposed to be truthful? How does data visualization then become paradoxical? How can design align itself with deception? Healy references Tufte to explain how Tufte believed that graphical excellence was found in telling the truth about data. Therefore, I feel like ethics lay at the core of this type of design.

When thinking further about perception in relation to data, it is interesting to consider how Healy speaks of optical illusions. I have never considered this correlation prior to reading Healy’s analysis of the matter. Furthermore, I enjoyed Healy’s analysis of how color theory aids the encoding of visual information. Healy describes the importance of shape and color in relation to graphing data. I look forward to employing methods of color theory to my work. I find that principles of design can be a key component in creating understanding for the viewer. I am curious as to how much the average viewer relies on a legend or key to understand visualization. How can we create successful interations where users can understand the visualization without a key?