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In order to unleash the full potential of System Wide Information Management (SWIM), the BEST project (Achieving the Benefits of SWIM by Making Smart Use of Semantic Technologies) proposes the semantic container approach which shields service and application developers from the complexities of data provisioning in Air Traffic Management (ATM). In combination with SWIM, semantic containers facilitate the emergence of a marketplace of value-added information services, and allow for complex derivation chains of data sets. Along these derivation chains, existing data are intelligently filtered and prioritized as well as combined and annotated with additional information.

Pilot briefings, in their traditional form, drown pilots in a sea of information. Rather than unfocused swathes of air traffic management (ATM) information, pilots require only the information for their specific flight, preferably with an emphasis on the most important information. In this paper, we introduce the notion of ATM information cubes – in analogy to the well-established concept of Online analytical processing (OLAP) cubes in data warehousing. We propose a framework with merge and abstraction operations for the combination and summarization of the information in ATM information cubes to obtain management summaries of relevant information. To this end, we adopt the concept of semantic data container – a package of data items with a semantic description of the contents. The semantic descriptions then serve to hierarchically organise semantic containers along the dimensions of an ATM information cube. Leveraging this hierarchical organisation, a merge operation combines ATM information from individual semantic containers and collects the data items into composite containers. An abstraction operation summarises the data items within a semantic container, replacing individual data items with more abstract data items with summary information.

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