Distribution of Noise Pollution in University District Area
Learn to Visualize Data
The project that we received this week is about information visualization. We used Tableau to analysis complex data, 911 Incident Response Dataset. Before actually dealing with a large amount of data, I practice using Tableau to analysis little information. And also some straightforward analysis about the big dataset. For instance, I made the Seattle Bike Rack Map during the sprint on 02/22.
According to my personal experience at the University of Washington, I made my decision about visualization user group. I picked students who live in the residence halls of UW or neighborhood apartments, particularly people who want to find a good place to live and study near the university campus. I chose noise pollution as my research topic because a quiet living condition is vital to college students. By using the data, which contains noise disturbance in the 911 Incident Response Dataset, I made three different types of visualizations about the distribution of noise pollution in University District area. (see three pictures I included)
Importance of Visualization
During the sprint this week, I learned various useful strategies to analysis a significant amount of complex data. After knowing the basic features of Tableau, I found that it is extremely helpful and powerful for visualization. For instance, it can easily access to all the data which having the same property, such as noise disturbance in my visualization. After I had made several visualizations in the sprint, I found the biggest challenge for this project is choosing the appropriate type of visualization. I needed to make my decision based on the different user groups, research questions, and data types. It was useful to try out several options before making the final visualization.
Apply Visualization in Big Data Field
Nowadays, the usage rate of person devices is increasing significantly. The information and data, which researchers can collect from public, is growing even faster. Therefore, it is impossible to make an analysis of it by just looking at it. Researchers have to visualize the Big Data and get useful information from the visualizations. For instance, to develop the “Siri” feature in iPhone. Designers need to use visualization to analysis the similar patterns or questions appear in the previously using “Siri.” Knowing how to visualize data is becoming extremely vital and useful skill in the modern world, especially in human center design. In many user researches and design process, we need visualization to analysis Big Data, to improve the efficiency.