A Framework for Conceptual Modeling of Geographic Data Quality

Abstract

The notion of data quality is of particular importance to geographic data. One reason is that such data is often inherently imprecise. Another is that the usability of the data is in large part determined by how good the data is, as different applications of geographic data require different qualities of the data are met. Such qualities concern the object level as well as the attribute level of the data. This paper presents a systematic and integrated approach to the conceptual modeling of geographic data and quality. The approach integrates quality information with the basic model constructs. This results in a model that enables object-oriented specification of quality requirements and of acceptable quality levels. More specifically, it extends the Unified Modeling Language with new modeling constructs based on standard classes, attributes, and associations that include quality information. A case study illustrates the utility of the quality-enabled model.