3D star coordinate-based visualization of relation clusters from OWL ontologies
Abstract
The recent proliferation of high-level and domain-specific ontologies has necessitated the development of prudent integration strategies. Visualization techniques are an important tool to support the data and knowledge integration initiative. This chapter reviews a methodology to visualize clusters of relations from ontologies specified using the Web Ontology Language (OWL). The relations, which in OWL are referred to as object properties, from various ontologies are organized into clusters based upon their intrinsic semantics. The intrinsic semantics of every relation from an input ontology is explicitly specified by a framework of 32 common elements; each element captures a specific aspect of the relationship between a relation’s domain and range. Using this framework, each relation can be represented in a 32-dimensional “relation space.” Relation clusters in 32 dimensions are projected to 3 dimensions using an automated 3- dimensional (3D) star coordinate-based visualization technique. Results from applying an algorithm to create and subsequently visualize relation clusters formed from the IEEE Suggested Upper Merged Ontology (SUMO) are presented in this chapter and discussed in the context of their potential utility for knowledge reuse and interoperability on the Semantic Web.
Publication Title
Data Management in the Semantic Web
Recommended Citation
Kothari, C., Shaik, J., Russomanno, D., & Yeasin, M. (2011). 3D star coordinate-based visualization of relation clusters from OWL ontologies. Data Management in the Semantic Web, 391-408. Retrieved from https://digitalcommons.memphis.edu/facpubs/13347