SpEuler: Semantics-preserving Euler Diagrams

TL;DR

SpEuler is a fast, semantics-preserving method for creating Euler diagrams that effectively visualize complex overlapping set data, ensuring readability and aesthetic quality while handling challenging cases gracefully.

Contribution

We introduce a novel two-step layout technique for Euler diagrams that guarantees semantic correctness and aesthetic appeal, with a fallback for complex data where perfect diagrams are not possible.

Findings

Our method produces well-matched, well-formed Euler diagrams for complex data.

It outperforms existing methods in preserving semantics and aesthetics.

The approach is validated through examples in text analysis and infographics.

Abstract

Creating comprehensible visualizations of highly overlapping set-typed data is a challenging task due to its complexity. To facilitate insights into set connectivity and to leverage semantic relations between intersections, we propose a fast two-step layout technique for Euler diagrams that are both well-matched and well-formed. Our method conforms to established form guidelines for Euler diagrams regarding semantics, aesthetics, and readability. First, we establish an initial ordering of the data, which we then use to incrementally create a planar, connected, and monotone dual graph representation. In the next step, the graph is transformed into a circular layout that maintains the semantics and yields simple Euler diagrams with smooth curves. When the data cannot be represented by simple diagrams, our algorithm always falls back to a solution that is not well-formed but still well-matched, whereas previous methods often fail to produce expected results. We show the usefulness of our method for visualizing set-typed data using examples from text analysis and infographics. Furthermore, we discuss the characteristics of our approach and evaluate our method against state-of-the-art methods.