Spatial data quality capture through inductive learning

The relatively weak uptake of spatial error handling capabilities bycommercial GIS companies and users can in part be attributed to therelatively low availability and high costs of spatial data qualityinformation. Based on the well established artificial intelligencetechnique of induction, this paper charts the development of anautomated quality capture tool. By learning from example, the tool makesvery efficient use of scarce spatial data quality information, sohelping to minimise the cost and maximise availability of data quality.The example application of the tool to a telecommunications legacy datacapture project indicates the practicality and potential value of theapproach.