Essay In the 6th class of Data Visualization, the professor shared us three important graphical perception essays. After reading those essay, I think from the beginning of the data visualization, data structure, and those essay - the graphical perception. While I reviewed the previous class text and slides and thought all these over again, I had the more clear concept of the data visualization.

Chart 1

Observing the chart of Milestones: time course of development, we know that before 1984 pie charts, maps were developed two hundred years ago.However, the charts and graphs of data visualization were not all reach to the high accuracy due to the unscientific measuring and data-visualization methods. Thus, Cox(1978) urged that “There is a major need for a theory of graphical methods.” Before Cox’s statement, Kruskal(1975) provoked that “. in choosing, constructing, and comparing graphical methods we have little to go on but intuition, rule of thumb, and a kind of mater-to-apprentice passing along of information. there is neither theory nor a systematic body of the experiment as a guide.”

Chart[2]

With the improvement of data exploration and data visualization, student and researcher dploy the chart by their own standard. The researcher might generate the self-explainable chart, however, it is not accurate when other researchers compare and comtract to other data set.Thank to the efforts of Cleveland and McGill.Cleveland, W. and McGill, R.(September, 1984), he composed the journal of Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods.[2]Thorugh the princiles and rule he elaborate in the article, the researcher gradually learn how to generate the chart that can be compare, comtract and comprehensable. Through this journal, they demonstrated all of the maps, charts, and tables. Through the article, I had the clear view of the data visualization. The authors guided us observing the data from scientific and measurable perspectives. They not only provided a standard to the all the scientists and researchers to follow but also regulate our problems solving logic. Later on, more and more researchers developed more variety of metrics and improve the accuracy of the data based on this journal.

In the chart 2, we would learn how to compare the data by position of the dots, the length of the line, the witdth of data, the area of object, the volume of the variables, the curve of the data distribution, the shade of the factors, and using the color to identify the items.

Chart[3]

When we mentioned about the accuracy, we could not neglect the “Pie Chart,” “Donut Chart.” Skaus, Kosara(2016) wrote the essay - Arcs, Angles, or Areas individual Data Encodings in Pie and Donut Charts.Though pie charts had been applied in the data visualization for 200 years, the researchers still hold scarcely perceptual understanding toward the pie charts. The authors, Skaus believes that it is because a general individual had difficulty to realize the angle of pie chart once the person sees the chart. In the serious of experiments, the author found that “angle” is not the only way that the observers realize the chart. According to the observation of arc charts and donuts charts, the readers identify the area and arc length to identify the ratio and further information from the charts. However, area and arc length still cause the high possibility of misguiding the reader to realize the data.Thus, I will avoid using the pie chart in future.

Citation: . Chart[1]Michael Friendly(2008) The Golden Age of Statistical Graphics, Statistical Science, 2008, Vol.23 NO4

. Chart[2] Cleveland, W. S., & Mcgill, R. (1984). Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods. Journal of the American Statistical Association 1984 experiments by McGill and Cleveland rank how accurately people assess graphic depictions of data

. Chart[3]Skau and Kosara(2016) Arcs, Angles, or Areas: Individual Data Encodings in Pie and Donut Charts,Eurographics Conference on Visualization(Euro Vis)2016