Data Visualization

The insight I got from the reading is that data visualization can largely influence people’s ways of reading and interpreting the data. By placing the data in a visual context, designers/data scientists help the audience to better understand the data as well as deliver messages about their own interpretations. I think the dog example in the Wurman reading is really interesting. Different insights are drawn when dogs are grouped using different rules. The categories played a leading role in how people interpret the data: for example when they are grouped by the country of origin, I would try to find the features that dogs in each country have in common.

I find some data visualizations on school magazine. The magazine uses data visualization to help readers understand the donation statistics of CMU Tepper School of Business.

For example, these two compares the total number of annual donors from 2018 and 2017. It kind of wants to do a comparison between the donors# from each year but I don’t think it did a good job. The “increase” is only visible immediately and readers need to compare the two numbers to see the increase. The use of color also doesn’t add any value.

This graph shows the different groups’ participation highlights. The pie charts work well here with the percentage. However, I think too many colors are used in this visualization. If the writer wants to highlight the three numbers which are highest ever, he/she can put those in red and the others in black.

I am very excited to learn more about data visualization and how to apply it effectively to help different users better understand the data.

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