Prediction of data visibility in two-dimensional scatterplots

Abstract

The result of a visualization process depends on the user’s decisions along it. With the intention of accelerating this process and guaranteeing an appropriate visualization of the data, we are looking to semi-automatize the process to help the users with the decision-making along it. To contribute to this semi-automation, it is useful to have metrics that characterize different important aspects of the visualization techniques, such as data representation visibility. Besides, scatterplots are a widely used technique to visualize scalar datasets. In this context, this work presents a metric that evaluates data representation visibility considering glyph visibility in scatterplots. We defined a metric that estimates the proportion of glyphs that will be visible regardless of the drawing order, and it depends on the number of items in the dataset, the size of the window, and the size of the glyphs that will represent the data. To define and approximate the metric, we experimented with several random datasets for which both dimensions followed a normal distribution. This metric constitutes an alternative to characterize scatterplots and collaborates in the semi-automation of the user’s decisions along the visualization process.

Automatic suggestions to improve the quality of scatterplots during its creation

“…Based on the visibility index [5], we developed an ontology that encapsulates the knowledge of the index's interpretation. Using a semantic reasoner to infer from this knowledge, we can suggest to the user proper modifications to the scatterplot configuration without the need of actually creating the visualization.…”

“…The visibility index [5] was defined as a specific metric for scatterplots. Given a scalar dataset and the window's and glyph's dimensions, it estimates the expected percentage of glyphs that are not completely overlapped with other glyphs (there exists at least one pixel of the glyph which is not overlapped with another glyph), that is, the expected number of glyphs that are always visible despite the rendering order.…”

“…To analyze the possibilities that semantics offers, we selected a metric that measures the quality of a scatterplot without the need of rendering it [5]; however, as it is presented in the original paper, the interpretation and understanding of the given number are not trivial and inadvisable for non-expert users. Thus, we developed a detailed interpretation of the result and the actions to be taken accordingly.…”

“…Since configuring a scatterplot could be timeconsuming and frustrating, a visibility index [5] was developed. This index measures the quality of the scatterplot without the need of rendering it and its interpretation gives clues on how to improve the visualization.…”