An ontology framework for quality of geographical information services
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
An Integrative Approach to Geospatial Data Fusion
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
Geometrical DCC-Algorithm for merging polygonal geospatial data
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part I
A data fusion system for spatial data mining, analysis and improvement
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part II
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After the introduction of digital mapping techniques in the 1960s and then GIS shortly afterwards, researchers realized that error and uncertainty in digital spatial data had the potential to cause problems that had not been experienced with paper maps [1]. Spatial data quality is a very active domain in geographic information research. This paper describes the significance of data quality and how is data quality defined. Data conflation can help to increase the amount of suitable for usage data. This paper analyzes results of spatial data conflation.