Zhengxiang Pan, Abir Qasem, Jeff Heflin
We investigate the challenges that must be addressed for the Semantic Web to become a feasible enterprise. Specifically we focus on the query answering capability of the Semantic Web. We put forward that two key challenges we face are heterogeneity and scalability. We propose a flexible and decentralized framework for addressing the heterogeneity problem and demonstrate that sufficient reasoning is possible over a large dataset by taking advantage of database technologies and making some tradeoff decisions. As a proof of concept, we collect a significant portion of the available Semantic Web data; use our framework to resolve some heterogeneity and reason over the data as one big knowledge base. In addition to demonstrating the feasibility of a "real" Semantic Web, our experiments have provided us with some interesting insights into how it is evolving and the type of queries that can be answered.
Subjects: 11. Knowledge Representation; 11.2 Ontologies