Relationship Management

In the S-57 specification, Relation is used to define logical links between different data elements (such as features and geometries) in the chart data model. These relationships can be spatial relationships (e.g., topology) or non-spatial relationships (e.g., logical connections between features). Relationships are implemented via pointers in the data structure, which contain foreign keys to establish one-way associations between records.

Feature association relationships are very important rules in the S-57 standard and are divided into two types: aggregation and master-slave:

  • Aggregation: A logical combination of multiple features, often used to describe multiple features as a whole.
    • Aggregated Feature
      • A group of light buoys (a combination of multiple light buoys) is considered as a single navigation auxiliary function.
      • Multiple waterways form a route network.
    • Associated Feature
      • An association between a bridge feature and its navigation restrictions (such as clearance height).
      • A functional association between a port and its berthing areas.
  • Master-Slave: Features have hierarchical and dependency relationships, often describing how one feature (the master feature) controls or contains another (the slave feature). For example, a light buoy can be considered the master feature, while its topmark, light characteristics, and fog signal can be regarded as its slave features.
    • Master Feature: Plays a primary role and defines the dominant feature in the association.
    • Slave Feature: Subordinate to the master feature, used to complement the functionality or characteristics of the master.

In chart data processing, Relationship Management is key to ensuring structured, normalized, and efficient application of data. By defining and implementing logical relationships between feature objects, data organization capabilities are enhanced, supporting complex chart production and navigation applications. At the same time, these relationships also provide a foundation for subsequent standards (such as S-101), ensuring the sustainable development of the chart data model.

This chapter will introduce the following content:

  • Create Aggregation: Describes how to define collection or association relationships between multiple features through attribute tables to organize and manage the logical connections of features in chart data without requiring geometric support.
  • Create Master-Slave: Describes how to define hierarchical chart feature relationships by specifying master and slave features to clarify hierarchical relationships between features, improving the accuracy of data management and representation.
  • Build Master-Slave Relationships in Batches: Describes how to quickly establish large numbers of master-slave relationships by automatically matching feature coordinates, improving efficiency and ensuring data consistency and accuracy.
  • Modify Association Relationship: Describes how to adjust the reference object of combined features or the dependency relationship between master and slave features to ensure the accuracy of feature relationships.
  • Information Types: Describes how to view, add, and delete information types in S-101 electronic charts.