Data Quality

Introduction

With the advent of satellite remote sensing, GPS and GIS technology, and the increasing availability of digital spatial data, resource managers and others who formerly relied on the surveying and mapping profession to supply high quality map products are now in a position to produce maps themselves. At the same time, GISs are being increasingly used for decision-support applications, with increasing reliance on secondary data sourced through data providers or via the internet, from geo-webservices. The consequences of using low-quality data when making important decisions are potentially grave. There is also a danger that uninformed GIS users will introduce errors by incorrectly applying geometric and other transformations to the spatial data held in their database.

 We discuss positional, temporal and attribute accuracy, lineage, completeness, and logical consistency

Learning outcomes

Prior knowledge

Incoming relations

Learning paths