CMGV: Algorithms and a unified framework for complexity management in graph visualization.

The article focuses on CMGV (Complexity Management in Graph Visualization), a novel, rendering-independent framework and associated algorithms designed to efficiently manage complexity during the visual analysis of large relational data represented as compound graphs. CMGV integrates multiple complexity management operations—filter/unfilter, hide/show, and collapse/expand—within a unified graph model (CMGM) that maintains synchronization between the full graph and its visible subset, while preserving the user's mental map through customized incremental layout algorithms based on the force-directed fCoSE layout. Implemented in JavaScript and demonstrated with the Cytoscape.js rendering library, CMGV supports seamless, consistent complexity management even when operations are mixed and applied in arbitrary order, addressing limitations of existing tools. Experimental evaluations on randomly generated compound graphs confirm the framework's linear runtime efficiency, layout quality preservation, and effective mental map maintenance, further supported by a user study indicating ease of use and minimal user disorientation. The framework and its Cytoscape.js integration are openly available on GitHub for use and further development.