A combined approach to checking web ontologies

Abstract

The understanding of Semantic Web documents is built upon ontologies that define concepts and relationships of data. Hence, the correctness of ontologies is vital. Ontology reasoners such as RACER and FaCT have been developed to reason ontologies with a high degree of automation. However, complex ontology-related properties may not be expressible within the current web ontology languages, consequently they may not be checkable by RACER and FaCT. We propose to use the software engineering techniques and tools, i.e., Z/EVES and Alloy Analyzer, to complement the ontology tools for checking Semantic Web documents. In this approach, Z/EVES is first applied to remove trivial syntax and type errors of the ontologies. Next, RACER is used to identify any ontological inconsistencies, whose origins can be traced by Alloy Analyzer. Finally Z/EVES is used again to express complex ontology-related properties and reveal errors beyond the modeling capabilities of the current web ontology languages. We have successfully applied this approach to checking a set of military plan ontologies.

Verifying OWL and ORL Ontologies in PVS

“…In our previous works [8,20], we have attempted to use a combination of SW and formal methods tools to reason about DAML+OIL/RDF ontologies. We used Alloy Analyzer (AA) [13], Z/EVES [18], RACER and OilEd [1] in combination to check for properties of interest.…”

Reasoning support for Semantic Web ontology family languages using Alloy

“…RACER can only partially support ABox reasoning. Alloy approach proposed in this paper can complement FaCT and RACER [3].…”

“…Currently, it is desirable if the strength from different ontology reasoning tools can be integrated. [3] presented the methodology of checking ontologies using tools RACER, Z/EVES and AA in conjunction. This approach has been successfully applied for reasoning a real life military ontology.…”

Integrated Collections: Approach to Software Component Reuse

“…Depending on the complexity of components, the taxonomy may include descriptions of terminology and definitions; algorithmic details in some format such as pseudocode; search keywords relevant to the component functionality; the application programmer interface (API) including formal parameters, expected behavior, pre-and postconditions, data format, and known limits and constraints; and patterns among components in the collection. Related work to the Taxonomy can be found in the field of semantic web [9,10].…”