Interactive Visual Analysis of Hierarchical Enterprise Data
Source: University of California
In this paper, the authors present an interactive visual technique for analyzing and understanding hierarchical data, which they have applied to analyzing a corpus of technical reports produced by a corporate research laboratory. The analysis begins by selecting a known entity, such as a topic, a report, or a person, and then incrementally adds other entities to the graph based on known relations. As this bottom-up knowledge building process proceeds, meaningful graph structure may appear and reveal previously unknown relations. The ontology of the data, which represents the types of entities in the data and all possible relations among them, is displayed as a guide to the analyst in the process.