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14.3 Specifics of Semantic Web Applications 309 14.3.2 Agents In practice, we will probably have to deal with the problem that, though most known semantic markup methods are relatively mature, only a few solutions introduce proper agent systems, which understand semantic markup. On the positive side, however, agent-based solutions can be replaced by more conventional solutions, for instance Web services. These more conventional solutions use the ontology to integrate schemas from existing, previously heterogeneous data repositories. To this end, Web services are used to act as wrappers for the data repositories. The DAML-S description language (for Web Services) tries to contribute in this field (Ankolenkar et al. 2002). However, if the target application requires a high degree of complex and autonomous behavior, then an additional group of mediators and perhaps even facilitators have to be added to the integration layer. This type of target application is characterized by a heavily distributed multi-layer architecture, which is currently still associated with high development risks. Most developer teams will probably not have all the required competencies and, at the same time, some of the available technologies are still under development. In addition, these applications are characterized by high technical complexity. 14.3.3 Ontologies The following six principles have been identified to be characteristic for the Semantic Web (Koivunen and Miller 2001). All the listed points require some rethinking in general and about ontologies in particular, compared with the traditional approach in AI research and the technologies developed in this field. 1. Everything can be identified by URIs. Both things from the real (physical) world and things from the digital world can be referenced. The approach is pragmatic and allows, for example, to identify a person by referencing that person s employer address and e-mail. 2. Resources and links can be typed. While humans give meaning to resources and links on the traditional Web, the Semantic Web will allow to create a machine-readable way of allocating meanings to facilitate referencing online terminologies and ontologies. 3. Incomplete information must be tolerated. In contrast to many classic AI systems, the so-called closed-world assumption cannot be maintained on the Semantic Web. So, if we draw logical conclusions from a statement, then the fact that information is missing from the knowledge base should not automatically result in concluding that the statement is FALSE. 4. No claim is laid to absolute truth. Also in contrast to classic systems, the Semantic Web should tolerate claims to local levels of truth. 5. Evolution of information or resources is possible. Just as humans and things change over time, there will also be information that was correct at a certain point in time, but which should be replaced by new information at another

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