Integrating heterogeneous data sources using rule-based reasoning, backward-chaining and custom built-ins

In this paper, we investigate the challenge of integrating heterogeneous, dis-tributed data sources using semantic technologies to enable the answering of complex user queries on the combination of available data. Our solution uses a common OWL ontology that contains the concepts that represent the data in all the distributed sources providing maximum querying flexibility towards the user. Retrieval of specific data from distributed sources is done using a set of customized rules and built-in functions that call the data sources APIs triggered when a user issues a SPARQL query. We validated our system with forward and backward ruling strategies in a horticultural application domain. The most important lessons learned are that the ap-proach is very flexible in the sense that only a few customized rules enable the querying of a large set of concepts. Using backward-reasoning rules largely improves the performance of the system, because the reasoner only executes those rules that it deems necessary to answer the user query.