Abstract
ABSTRACTPilot 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.
Highlights
A Pre-flight Information Bulletin (PIB) provides pilots with current Notices to Airmen[1] but may include other types of messages relevant for a flight[2] e.g., meteorological information
We introduced the concept of air traffic management (ATM) information cube, an adaptation of the data cube metaphor, where instead of numeric measure values, each cell consists of a set of data items e.g., Digital NOTAMs (DNOTAMs) or Meteorological Aerodrome Report (METAR)
Dedicated query operations allow for the merge and abstraction of the data items organised in ATM information cubes in order to provide a condensed view – a management summary – of relevant ATM information
Summary
A Pre-flight Information Bulletin (PIB) provides pilots with current Notices to Airmen[1] but may include other types of messages relevant for a flight[2] e.g., meteorological information. Digital NOTAMs (DNOTAMs) allow for automated filtering as well as classification of messages along different dimensions (or facets) e.g., importance, geographic area, flight phase, and event scenario, that can be employed to flexibly structure the ePIB to reduce information overload[7]. We propose the notion of the ATM information cube, which hierarchically organises semantic containers along different dimensions relating to the container content e.g., the geographic and temporal applicability, flight criticality, and flight phase that the container content is relevant for. In this regard, we assume the existence of appropriate rule-based filtering mechanisms to collect ATM information into the containers. We present adapted excerpts of standard ATM information exchange models employed in the examples
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