Personalizing Climate Change
Nadja Popovich’s personalizing climate change takes an interesting turn with its reversal of the presentation of climate change information. The data that she presents at the beginning of her talk showing how people think climate change will affect them vs other people makes a really compelling case to illustrate how climate change is affecting each individual. The concept of the near and far view of climate change gives the viewer more perspective, seeing not only the global effects but also the local effects. The choice of using localized geography gives the viewer an understanding of how the places they are familiar with are affected by climate change. Furthermore, the choice to use the reader’s birth year on top of local geography makes climate change even more personal, playing into the reader’s memories of the climate in their hometown. The reader is able to visually see the difference between their memories of the climate in the past, the present day climate reality and the possible future. The order of information also changes how the reader views the topic of climate change. Rather than emphasizing the global aspect of climate change off the bat, they choose to focus on showing that climate change is affecting the reader themselves, making it clear that they are not excluded from the global impact of climate change. Then by showing other regions of the world, they clearly illustrate the effects of climate change on neighboring countries and the severity of climate change in the most affected regions of the world. The presentation of information gives the viewer a relative view of climate change, understanding how climate is affecting regions differently. Overall, the choices made throughout this piece of information design accomplishes the goal of personalizing climate change.
Counting the Infected
Listening to the podcast made me realize just how hard it is to create these pieces of information design. Hearing about the whole process made me appreciate informative illustration and graphics so much more. The story that Robert Gebeloff tells about how the New York Times Data Team obtained data about COVID-19 cases in the United States illustrates how difficult it is to obtain accurate data and even harder to process and analyze the data. Learning about their methodology of processing, interpreting, analyzing, questioning the data (and repeating it over and over again) was really compelling especially in the case of learning about the racial disparities in COVID cases. From first finding the pattern in the racial disparity in COVID cases to asking more questions about why the racial disparity exists just shows that there is so much to learn from data and even more data to collect. It is also pretty easy to see how messy and political the process of obtaining data can get with the repression or omission of data. The conversation about the possibility that the CDC isn’t sharing everything sparked a train of thought, wondering just how much information has been kept from the media and/or the public. How would that missing information affect how we perceive events and what would our reactions to that information be?