F-OWL is an ontology inference engine for the Web Ontology Language OWL. The ontology inference mechanism in F-OWL is implemented using Flora-2, an object-oriented knowledge base language and application development platform that translates a unified language of F-logic, HiLog, and Transaction Logic into the XSB deductive engine. Key features of F-OWL include the ability to reason with the ontology model defined by the latest standard OWL language recommended by the W3C, the ability to support knowledge consistency checking using axiomatic rules defined in Flora-2, and an open application programming interface (API) for Java application integrations.

The latest release of F-OWL (v0.3) has been used as the ontology reasoner in a number of different intelligent system prototypes, including CoBrA a broker-centric agent architecture for pervasive context-aware systems, TAGA a multi-agent system for e-commerce trading simulation, and REI a policy-based security system for distributed trust management.

The use of an object-oriented rule based language (i.e., Flora-2) in an advanced Prolog logic programming system (i.e., XSB) differentiates the implementation of F-OWL from other ontology inference engines such as JTP, RACER and DAMLJessKB.

1. F-OWL exploits a special rule evaluation mechanism called tabling, provided by the underlying XSB system. This mechanism can facilitate result caching in the backward chaining reasoning, which is beyond the capability of a traditional Prolog system. As ontology reasoning often involves repetitive evaluation of some closed-world domain knowledge, the tabling mechanism can help to avoid repetitive ontology inference calculations, improving the overall system performance.
2. In contrast to the use of conventional logic languages in other ontology inference engines (e.g., KIF in JTP and CLIPS in DAMLJessKB), F-OWL adopts an object-oriented language Flora-2 that has a closer language constructs to the OWL language (e.g., both Flora-2 and OWL support the representations of classes, properties, restrictions, and instants).
3. Building F-OWL on an advanced logic programming system creates the potential for applications to be integrated and interoperate with other intelligent systems (e.g., integrating an existing planning system to exploit knowledge inferred from an existing ontology model).

F-OWL is still in its early stage of development. It's a joint work between a group of PhD students Harry Chen, Youyong Zou, Lalana Kagal and their advisor Tim Finin.