This dissertation discusses the problems and the methods of creating and using ontologies in the area of digital cultural heritage. One of the problems is that content annotations in semantic cultural heritage portals commonly make spatiotemporal references to historical regions and places using names whose meanings are different in different times. For example, historical administrational regions such as countries, municipalities, and cities have been renamed, merged together, split into parts, and annexed or moved to and from other regions. The contribution of this dissertation to this problem is to develop methods which can be used to model, produce and utilize geospatio-temporal ontologies. The resources in geospatio-temporal ontologies can be used as annotation terms for describing content, and also for seeking information. The main point of this dissertation is to describe schemas, models and methods that produce and utilize a geospatio-temporal ontology. The schemas and the models are used as inputs for the methods. These methods generate identifiers for spatio-temporal instances, and also relationships between them. In this work, historical Finnish municipalities were modeled and geospatio-temporal descriptions for them created from a filled-up schema. Methods enriched the models by creating geospatio-temporal relationships between these temporal municipalities. The resulting collection of models are referred to as the Finnish Spatio-temporal Ontology (Suomen ajallinen paikkaontologia, SAPO). Specific relationships of the geo-spatiotemporal instances provided the basis for novel recommendation, data mining and visualization schemes. The results of the experiments were promising. For example, with the help of the ontology a user has the ability to retrieve also the content annotated to a historic region even if she searches using a contemporary name of the same or partially overlapping region. The work contributes also to modeling and reasoning about imprecise temporal intervals. A set of different measures based on analyzing two fuzzy temporal intervals are presented and evaluated in the work. The use of a combination of different measures for calculating relevance between temporal intervals was found out to perform best
