GRHCSep 7, 2020

Responsive Matrix Cells: A Focus+Context Approach for Exploring and Editing Multivariate Graphs

arXiv:2009.03385v132 citations
AI Analysis

This addresses the problem of managing complex multivariate graph data for visualization researchers and practitioners, though it appears incremental as an enhancement to existing matrix-based methods.

The paper tackles the challenge of visualizing and editing multivariate graphs by proposing responsive matrix cells, a focus+context approach that embeds interactive views into matrices, enabling users to explore and edit node and edge attributes directly without external tools.

Matrix visualizations are a useful tool to provide a general overview of a graph's structure. For multivariate graphs, a remaining challenge is to cope with the attributes that are associated with nodes and edges. Addressing this challenge, we propose responsive matrix cells as a focus+context approach for embedding additional interactive views into a matrix. Responsive matrix cells are local zoomable regions of interest that provide auxiliary data exploration and editing facilities for multivariate graphs. They behave responsively by adapting their visual contents to the cell location, the available display space, and the user task. Responsive matrix cells enable users to reveal details about the graph, compare node and edge attributes, and edit data values directly in a matrix without resorting to external views or tools. We report the general design considerations for responsive matrix cells covering the visual and interactive means necessary to support a seamless data exploration and editing. Responsive matrix cells have been implemented in a web-based prototype based on which we demonstrate the utility of our approach. We describe a walk-through for the use case of analyzing a graph of soccer players and report on insights from a preliminary user feedback session.

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