Research on visualizing Semantic Web data has yielded many tools that rely on information visualization techniques to better support the user in understanding and editing these data. Most tools structure the visualization according to the concept definitions and interrelations that constitute the ontology’s vocabulary. Instances are often treated as somewhat peripheral information, when considered at all. These instances, that populate ontologies, represent an essential part of any knowledge base. Understanding instance-level data might be easier for users because of their higher concreteness, but instances will often be orders of magnitude more numerous than the concept definitions that give them machine-processable meaning. As such, the visualization of instance-level data poses different but real challenges. The authors present a visualization technique designed to enable users to visualize large instance sets and the relations that connect them. This visualization uses both node-link and adjacency matrix representations of graphs to visualize different parts of the data depending on their semantic and local structural properties. The technique was originally devised for simple social network visualization. The authors extend it to handle the richer and more complex graph structures of populated ontologies, exploiting ontological knowledge to drive the layout of, and navigation in, the representation embedded in a smooth zoomable environment.
|Number of pages||24|
|Journal||International Journal on Semantic Web and Information Systems|
|Publication status||Published - 2013|