Data representation is the act displaying the visual form of your data. The process of identifying the most effective and appropriate solution for representing our data is unquestionably the most important feature of our visualization design. Working on this layer involves making decisions that cut across the artistic and scientific foundations of the field.
Here we find ourselves face-to-face with the demands of achieving that ideal harmony of form and function that was outlined in Chapter 6, Data Representation. We need to achieve the elegance of a design that aesthetically suits our intent and the functional behavior required to fulfill the effective imparting of information.
According to Kirk 2019, in order to dissect the importance of data representation, we are going to “look at it from both theoretical and pragmatic perspectives.” Choose three of the storytelling techniques from the gallery of charts (Pages 140 – 188) in which data is presented and stories are being interpreted. Discuss the importance and advantages of using these techniques. Provide an example of each technique.
Kirk, A. (2019). Data Visualization: A Handbook for Data-Driven Design. 2nd Ed. Thousand Oaks, CA: Sage Publications, Ltd.
When replying to a classmate, offer your opinion on what they posted and discuss the important advantage of their selected technique.
Also, using at least 3 – 5 sentences, are the examples, in your opinion, relevant and usable?
Background: Quantitative data can be measured and documented with numbers. Additionally, quantitative data can be represented as quantities. On the other hand, qualitative data is not measured with numbers, but it is represented by qualities. For example, I use quantitative methods to conduct my PhD research because I like working with counts and measures.
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