Spatial data plays a big part in the Information Age, from online mapping services to downloadable data from thousands of government agencies. Do you always trust spatial data? Do your users trust your GIS data? Creating and maintaining accurate spatial data is one of the keys to a successful GIS implementation. Without quality data, the most user-friendly GIS will not be accepted and used by it’s intended audience. This course will present best practices, processes, quality control and quality assurance techniques for developing and maintaining high-quality spatial data that users will trust and utilize.
Project managers and technical staff creating or maintaining spatial data, GIS users considering acquiring or developing new spatial data – both in the government and private sectors, and spatial data users who need a better understanding of how quality data is developed.
Guidelines for selecting the appropriate levels of quality and accuracy
Establishing an effective data quality control program
Data conversion quality control / quality assurance
How to attack and defeat quality problems
High quality processes lead to high quality data
Principles and processes for statistics-based quality assurance testing