In a rescue scenario, you have personnel from different organizations cooperating, and thispersonnel has to communicate both within their own organization and with personnel fromother organizations. If they are carrying handheld devices, they can receive and sendautomatic information updates within a mobile ad-hoc network that consists of all of thehandheld devices carried by rescue personnel and sensors that are within range. A challengewith this kind of information sharing is that different organizations may use different datamodels and vocabularies for defining the same concepts. Ontologies can be used as a bridgebetween these different vocabularies, enabling a mapping between the concepts of thedifferent vocabularies. The Web Ontology Language (OWL) can be used to express theontologies.OWL is a very expressive language, and has the advantage that it is possible to performreasoning over ontologies and infer knowledge that is not explicitly stated. The only problemis that reasoning engines for OWL typically require a lot of resources, and are therefore notwell suited for resource-limited handheld devices.Topic maps is another technology for expressing ontologies. Topic maps are less expressivethan OWL and do not provide support for automated reasoning, but there exists a topic mapengine that allows you to browse and query the topic map and that can be used on resourcelimiteddevices.OWL is built on another language called the Resource Description Framework (RDF), and thetopic map and RDF communities have looked at how these two different languages can betranslated into each other. Since OWL is built on RDF, we look into if any of the translationproposals for translating between RDF and topic maps also can be used for translatingbetween OWL and topic maps. This will allow us to create an ontology in OWL, performreasoning on the ontology and add the information inferred from the reasoning to the ontologydirectly. Then the ontology can be translated into a topic map, and can be used on a handhelddevice. This thesis looks at how one can translate ontologies from OWL to topic maps, andhow usable the resulting topic maps are in a mobile ad-hoc network for a rescue operation.