Visuall: a quickly customizable library for jumpstarting visual graph analysis components

Abstract

Graph visualization is an area of information visualization, where relational data is depicted in the form of nodes (objects) and edges (links). Many people or organizations utilize graph visualization for insightful analysis and interpretation of relational data. In graph visualization, primary challenges include complexity management, efficient database querying, and customization for specific domains. Visuall aims to solve these problems by providing a generic, highly customizable, and easily configurable software component for building web-based visual graph analysis tools. Essential functionalities needed by such visual analysis components include manually or automatically setting the layout of graph elements, support for nested or hierarchical drawings, efficient querying of the database or client-side data, emphasizing or highlighting graph elements of interest, customization of visuals and styles, clustering, calculating graph-theoretical properties, and time-based filtering of graph elements. Although Visuall provides all these functionalities out of the box for jumpstarting, customization of software for domain-specific needs is still unavoidable. Such software changes might result in complications due to unstructured code and code ignoring the invariants assumed by the orig-inal development team. To prevent these and to facilitate easily maintainable customization, Visuall provides a modular architecture. Furthermore, the devel-opers straightforwardly upgrade the software so long as the Visuall developers and the users developing visual analysis components based on Visuall maintain the provided architecture. We tested our database queries on a database that contains about half a million graph elements. We also examined our client-side operations up to a thousand graph elements. In both client-side and database operations, we observe that operations take at most several seconds, making Visuall convenient for interactive exploration and analysis of networks.