Utilizing Structured Information from Multiple External Sources in the Context of the Multidimensional Data Model

Analytical Information Systems (AIS) enable analysts to visualize and analyze large amounts of data. They are based on a Data Warehouse in whose context typically various types of metadata are used. Often these metadata slightly consider additional information especially concerning the Multidimensional Data Model (MDM) like definitions, business rules, terminology or background information. By adding this metadata, particularly regarding the linked data movement, a significant improvement in the domain of AIS can be achieved. Our approach suggests a semantic metadata layer that enhances the AIS to allow modeling additional information in form of real-world entities. These entities correlate with MDM elements and are derived and integrated from various external structured sources. As a prototype we show the feasibility of this approach through a filter component that filters classification nodes with information not covered by the MDM.