Chapter 3. Data Counseling, Exploration, and Prototyping

The previous chapter outlined a way to analyze a real-world question and transform it into an actionable, operationalized task. This analysis involves many steps that require decisions along the way: identifying specific tasks that address the broad question; decomposing each task into specific objects, measures, and groupings; and finally building visualizations that validate and support these tasks. Carrying out this process effectively requires sophisticated domain expertise, knowledge of the data and the problem space, and a sense of what would be a good answer to the question. This chapter discusses a variety of techniques that support gaining this understanding through working with stakeholders and iterating on visualization prototypes.

We call this collaborative process data counseling. We chose this name because working with stakeholders is a back-and-forth process of conducting interviews; of diving deeply into a user’s intents around data; and of understanding the stories of where the data comes from, what problems are associated with it, and what it can mean.1 Data counseling is interwoven with exploring data, developing visualization prototypes, and collecting feedback on these preliminary results. This chapter describes techniques for these steps as well.

A major visualization project can require multiple interviews and rounds of prototypes in an intensively collaborative process. Recognizing the ecosystem of ...

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