Towards Scalable Visual Exploration of Very Large RDF Graphs
This work addresses scalability issues for researchers and practitioners handling massive graph data, though it appears incremental as it builds on existing spatial indexing techniques.
The authors tackled the problem of visualizing and exploring very large RDF graphs by developing graphVizdb, a disk-based platform that uses an R-tree spatial index to store graph layouts, resulting in efficient runtime operations through spatial queries.
In this paper, we outline our work on developing a disk-based infrastructure for efficient visualization and graph exploration operations over very large graphs. The proposed platform, called graphVizdb, is based on a novel technique for indexing and storing the graph. Particularly, the graph layout is indexed with a spatial data structure, i.e., an R-tree, and stored in a database. In runtime, user operations are translated into efficient spatial operations (i.e., window queries) in the backend.