weekly Reading - Truthful Art: Data, Charts, Maps for communication (Chap.1&2)

Last semester when we needed to choose the courses for the new term, one of my senior she strongly recommended this course, and showed her project to me which attracted me at first sight. Yet I regarded it as a design class at first until I read the book. Thanks for that, I got a basic and comprehensive understanding of visualization, following are some key points I considered during the reading. 


image 1.1 My friend showed me the project she did

Chapter one gives an understandable introduction of what is visualization. Like the basic elements of visual presentation: chart, map, etc. Besides, there are other two subcategories as infographics and data visualization with a blurry boundary between them. From my perspective, the difference between infographic and data visualization is that the author of the former will not include all the information but just pick put the one or two s/he cares about most to reveal ideas; but for data visualization, it may not has much texts but want that people apply the designed data to draw their own conclusions. One more interesting type and we've seen in the class is the new application, which relates data being presented to audience's own life. Last but not the least,  we needn't cost too much efforts on classifying but should pay more attention to the illumination; after all, the goal of the visualization is enabling communication.
As an extend of chapter one, chapter two mainly talk about what is a good visualization and how to make it. The five qualities are listed below:
  • Truthful  As a part of the book title, it's not only a quality but a principle when we do projects. Take Hockey Stick Chart of globe warming for example, to make a best persuasive effect, it collect the data from tree ring, varved sediments and other paleoclimate data which is not asw easy as citing resources from a book. That is a big reason why it could make a huge hit and arouse so much awareness. On the contrary, NCTA is a good case to show that credibility of visualization is not just the expertise, but also the trustworthiness.  To achieve the goal, we are ought to be honest with our audience and try avoiding self-deception. As the Goebbels effect warns, if the lie be told thousands of times, it could be truth in the end. 
  • Functional It means the visualization should help audience interpret information correctly. It is not about personal taste, but rational thinking. As professor said in class, there is no right or false of applying what kind of chart or map; but more or less suitable with the message you want to emphasize.
  • Beautiful This part is what I'm interested most. For I used to learn advertising, which has a lot of design class. "Beauty matter because attractive and pleasing things work better." I can't agree with it anymore. However, it. does not mean that visualization is data decoration. the appearance of an object should always connect to it purpose tightly. So for the visualization of Accurat.it, I prefer the redesigned one, since it's more clear and concise. Although the circle is a good metaphor of life, we need to draw something useful for conclusion but not just appreciate its beauty.
Visualization of Accurat.it vs. Redesign of it
  • Insightful It has two types as spontaneous insight and knowledge building one. What we should do is focus on revealing evidence.
  • Enlightening This is a consequence of previous four qualities,  that is, if we want to enlighten someone, we should pay attention to the whole. Another thing that decide the level of enlightening is topic itself. "Some topic do matter more than others indeed because they are more critical to the well-being of more people." Nowadays, many big companies grasp tons of users' information, especially Internet company such as Facebook. They do bring the convenience to our daily life with these "big data" as they advertise themselves; but do they always treat the data as they promise?  Well, facts speak louder than words. Therefore, "Do Good with Data."

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