Temporal ontology for representing uncertainly specified time periods is presented. Mature approaches like Allen interval relations are combined with introduction of time granularity and time uncertainty concepts. The ontology is applicable both as a static data representation and for logical data inference. Logical conclusions can be derived using an automated inference system. Uncertainty parametrization was developed for handling the domain specific uncertainty characteristics. Temporal statements containing the most frequent expressions in the domain of cultural heritage preservation are identified and categorized with respect to their accuracy. A temporal inference system is implemented using OCML language. Consistency checks can find non-causal data clusters and lead to improving current event data. Finally, resource annotation with Dynamic Narrative Authoring Tool utilizing temporal inference is presented.