Mapping Sets for Spatial Observation Data Warehouses

The amount of time evolving spatial data that is currently being generated by automatic observation processes is huge. In general, observation data consists of both heterogeneous spatio-temporal data and relevant observation metadata. The former includes data of Spatial Entities (cities, roads, vehicles, etc.) and data of temporal evolution of both properties of Spatial Entities (population of a city, position of a vehicle, etc.) and properties of space (temperature, elevation, etc.). Real uniform integrated management of all these types of data is still not achieved by current models and systems. The present paper describes the design of a data modeling and management framework for observation data warehouses. A hybrid logical-functional data model based on the concept of MappingSet and relevant language enables the specification of spatio-temporal analytical processes. The framework in currently being implemented