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Proposed Model Transformation Rule: Fan-Out Feature Types to Multiple Feature Classes #102

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jsaligoe opened this issue Oct 12, 2019 · 0 comments

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For consideration, a Model Transformation (MT) rule to fan-out features into separate feature classes depending on the feature type.

MTXXX: (PROPOSED) Fan-Out Feature Types to Multiple Feature Classes

Category
Simplification

Description
To improve usability within standard GIS systems, the feature type may be fanned-out into multiple feature classes for portrayal in layers.

When features are overlapping and nested spatially, it is not always practical to show all nested feature types within the same feature class. In some application schemas, feature types may have properties that categorize the features into different scale ranges, like nationalLevel for AdministrativeUnit features. For example, in AdministrativeUnit six feature classes would represent nationalLevel (1stOrder, 2ndOrder, etc.).

Additionally, in some application schemas feature type may have properties that categorize features by distinct attributes, such as transportation service types. In such case, service type may be fanned-out into multiple feature classes for portrayal in layers.

Original vs. Transformed UML Model, where applicable

Original instance in default encoding

Transformed instance in default encoding, where applicable

Model Transformation Rule
Parameters:

Feature class names may be based on the application schema suffixed with the feature type value, i.e.,
• AdminUnit_1stOrder
• AdminUnit_2ndOrder
• AdminUnit_3rdOrder

Instance Transformation Rule

Solved Usability issues
In standard GIS systems it is not feasible to see and filter features that are scale dependent or otherwise nested in the same feature class. For portrayal and analysis standard GIS systems, it is not practical to mix multiple feature types into the same feature class.

Known Usability issues
None.

INSPIRE compliance conditions and reversibility
Data transformed using this rule is INSPIRE compliant as long as there is no information loss from the source data. Data in separate feature classes may still be complex, therefore other rules may still be needed, e.g., MT001: Flatten Nested Structures.

Examples of use
Fanning-out of feature types to multiple feature layers is used in ELF to make data fit for purpose.

Additional notes
None.

Other comments

Examples to be provided.

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