IEEE VIS 2024 Content: (Almost) All Data is Absent Data

(Almost) All Data is Absent Data

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Karly Ross - University of Calgary, Calgary, Canada

 Pratim Sengupta - University of Calgary, Calgary, Canada

 Wesley Willett - University of Calgary, Calgary, Canada

 Room: Esplanade Suites I + II + III

2024-10-14T16:00:00ZGMT-0600Change your timezone on the schedule page
2024-10-14T16:00:00Z

Exemplar figure, described by caption below — We compare two models of how we think about data to inform our visualization process. Left shows an abstracted data set with the areas with no data blanked out in grey. This model has many voids, but all within the existing data structure. On the right, a tiny speck of white is in a void. This speck indicates all the data that is collected in what we perceive to be an infinite field of all the data that could be collected. We use this second model to think about new possibilities in data visualization practices.

Abstract

We explain our model of data-in-a-void and contrast it with the idea of data-voids to explore how the different framings impact our thinking on sustainability. This contrast supports our assertion that how we think about the data that we work with for visualization design impacts the direction of our thinking and our work. To show this we describe how we view the concept of data-in-a-void as different from that of data-voids. Then we provide two examples, one that relates to existing data about bicycle mobility, and one about non-data for local food production. In the discussion, we then untangle and outline how our thinking about data for sustainability is impacted and influenced by the data-in-a-void model.