This work is focused on the use of hybrid ontology to represent a subset of a geospatial domain concerning landslide detection.

The W3C Consortium has established the Ontology Web Language (OWL), a Description Logics (DL) language as the standard for ontology definition. However, complex domains like the geospatial domain cannot be represented completely with OWL which may require a combination of different knowledge representation languages.

OWL-log is an implementation of the AL-log hybrid knowledge representation system formed by a structural component based on description logics (DL) and a relational component based on Datalog. OWL-log restricts the Datalog atoms to be unary or binary, and the Description Logics (DL) component is extended to the Web Ontology Language OWL DL. The interaction between the subsystems is done through the specification of constraints (DL classes) in the Datalog rules which "type" variables appearing elsewhere in the body, so the DL theory acts as an expressive language to structure knowledge for
Datalog predicates.

The purpose of this ontology is to represent concepts and relationships relative to the detection of zones threatened by landslides. The ontology was constructed by extending a bottom-up constructive methodology, as a product a set of concepts and rules where specified.

A benchmark adapted to the universe of discourse was used. During the test, selected queries were executed concluding that Owl-log is capable of retrieving knowledge using reasoning rules with complex interaction between factors or conditions. OWL-log is suitable for expressing dependencies both, between properties and predicates related to an ontology.