Spatial Data Management

Vector Data

Vector data, also known as feature data, is used to store models of geographical objects and dervied interpretations. Vector datasets can be the result of data collection and interpretation by surveyors, architects and inspectors in the field. Examples are cadastral objects, buildings, roads, trees and country borders. Often data processing algorithms on point clouds or raster datasets also result in vector datasets, such as depth and height contours, object recognition and location tracking.        

Vectordata in GeolinQ

GeolinQ offers functionality to import files in Shape format and in GML format. In addition GeolinQ offers functionality to import features from WFS web services. If the datamodel of the vectordataset is available as part of the file format, from the WFS or as XSD, the datamodel to store the vector dataset is generated automatically. When no datamodel is available, the datamodel has to be created by the user. During import the created datamoel must be linked to the attributes of the input file.   

GeolinQ finally offers functionality to link external Oracle and PostgreSQL databases containing vector datasets as a datasource. The database schemes of the linked database are imported to make the vector datasets available in GeolinQ.

Vector data retrieval

Vector datasets can easily be queried on metadata attributes. These metadata attributes can be defined by the user. The ISO 19115 metadata standard is also available and can be used ‘as is’ or as a guideline for a user-defined metadata schema. Styling functionality is available for visualisation and creating thematic layers. These thematic layers can be published as WMS. The features from vector datasets can be published as WFS.