Abstract
A continuing question in the geospatial community is the evaluation of fitness for use of map data for a variety of use cases. While data quality metrics and dimensions have been discussed broadly in the geospatial community and have been modelled in semantic web vocabularies, an ontological connection between use cases and data quality expressions allowing reasoning approaches to determine the fitness for use of semantic web map data has not yet been approached. This publication introduces such an ontological model to represent and link situations with geospatial data quality metrics to evaluate thematic map contents. The ontology model constitutes the data storage element of a framework for use case based data quality assurance, which creates suggestions for data quality evaluations which are verified and improved upon by end-users. So-created requirement profiles are associated and shared to semantic web concepts and therefore contribute to a pool of linked data describing situation-based data quality assessments, which may be used by a variety of applications. The framework is tested using two test scenarios which are evaluated and discussed in a wider context.
Highlights
Data quality of maps has been defined using many data quality metrics judging various parameters of the geometry and its attributes, often but not exclusively comparing geometries to a comparison data set, the gold standard
The approach is based on the idea of thematic map evaluation which has been extended to evaluate situational descriptions by describing them as a set of thematic maps
The creation of a joint ontology model with the central concept of a requirement profile allows the linkage of geometries, situational descriptions, data quality vocabularies, provenance information and thematic map definitions
Summary
Data quality of maps has been defined using many data quality metrics judging various parameters of the geometry and its attributes, often but not exclusively comparing geometries to a comparison data set, the gold standard While it is, in general, a useful endeavour to be able to measure data quality parameters, it is usually up to the users to define which data quality parameters are required for their particular use case, how to combine them and how to aggregate the metrics’ results to achieve a data quality result for a particular purpose in a certain area. This paper builds upon Reference [2] a generalized ontological model which acts as the missing link between data quality metrics and application cases This model is used in a prototypical application which is able to a certain degree to judge which data quality metrics are appropriate and how they need to be prioritized to get an accurate result for particular use cases.
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