IMPROVING THE INTEGRATION OF GEOGRAPHIC INFORMATION THROUGH AUTOMATIC VERIFICATION OF DATA IMPERFECTIONS
The recent development of Geographic Information Systems and the high
availability of geolocation devices have been stimulating significant growth in the availability of geographic data. The correct usage of geographic information is severely dependent on data quality and integration capacity. Data manipulation, however, remains a problem in integration processes or sophisticated handling. Some of the main difficulties are to recognize, treat, or correct the geographic data attributes, since they are exposed to several sources of inconsistency: file formats, software, data precision, data representation choices, or inadequate manipulation. The improvement of data quality needs the development of techniques for controlling errors so that the data handler can comprehend, identify, classify, and treat inconsistencies over the geographic data. There are many efforts in this area, but little consensus about the best tool to manage problems in geographic data. In this context, this work to identify geographic errors and propose ways to correct them, for the purposes of (semi) automatic verification and data quality control. The verification will start from the classification of errors, suggesting possible ways of correction. The work will use integration strategies based on data from open formats and open source software. The expected result is a classification of the different types of errors and an automatic verification of geographic data, based on the standard ISO 19157: 2013.