Towards Scalable Visual Exploration of Very Large RDF Graphs

TL;DR

This paper presents graphVizdb, a disk-based system for scalable visualization and exploration of very large RDF graphs, utilizing spatial indexing techniques like R-trees for efficient querying.

Contribution

The paper introduces a novel disk-based infrastructure that leverages spatial data structures for scalable visualization of large graphs, enabling efficient exploration operations.

Findings

Efficient spatial indexing enables scalable graph visualization.

The platform supports real-time exploration of large RDF graphs.

Improves performance over existing graph visualization tools.

Abstract

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.