the truthful art- part5 practice

Data visualization mainly relies on graphical means to convey and communicate information clearly and effectively. But that doesn't mean that data visualization must be tedious to achieve its functional purpose, or extremely complex to look colorful. In order to effectively convey ideas and concepts, aesthetic form and function need to go hand in hand and achieve deep insight into relatively sparse and complex data sets by visually conveying key aspects and features. However, designers often fail to strike a good balance between design and function, thus creating gaudy forms of data visualization that fail to achieve their main purpose, i.e. to convey and communicate information.

Data visualization is closely related to information graphics, information visualization, scientific visualization and statistical graphics. Currently, data visualization is a very active and critical aspect in research, teaching and development. The term "data visualization" achieves the unification of mature scientific visualization field and younger information visualization field.











In the process of reading, in order to help me better understand and better apply visual data to China, I searched some relevant literature and found several problems:

• visual noise: there is a strong correlation between most objects in a data set. Users can't show them as separate objects.

• information loss: it is possible to reduce visual data sets, but this can lead to information loss.

• large image perception: data visualization is limited not only by the aspect ratio and resolution of the device, but also by the perception of the real world.

• high-speed image transformation: although users can observe data, they cannot respond to changes in data strength.

• high performance requirements: this requirement is almost non-existent in static visualization because of the low visualization speed and low performance requirements.


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