The paper puts forth the different types of data that can be represented in a visualization and the tasks that can be performed on data types. The author divides the data that can be visualized into seven different categories each with its own properties. The author proposes this data taxonomy and explains which data can be categorized into these categories. The author also explains the different tasks or the functions that the user has to perform to actually make sense from the data if it is of that type. To explain this, her gives us brilliant examples which helped me actually visualize how the user can interpret from the data.
The categorization of data into these types and knowledge of how the user will perceive it helps us to get an approach of how exactly to put forth the visualization to the user. The paper also explains the tasks that need to be performed on the data in order to get effective results out of any visualization. These tasks are common and apply to almost all data types. The author also mentions the advanced filtering task which adds the interaction property.
The paper brings out a right view of how visualization are built up by using one of the data types mentioned and how it is needed for effective visualizations to be built using a combination of such data types. It is imperative for a visualization to make sure that the basic tasks are provided to the user to analyze the data. I like the way the author brings out the relation between these two things. But, it seems that the points put forth here are overly generalized. The data-types are not necessarily only those that are mentioned but as the amount of data all over the world grows, data types will emerge and some of them might be complex enough to require a series of tasks in order to analyze them completely.
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