A Framework for Conceptual Modeling of Geographic Data Quality

Sustained advances in wireless communications, geo-positioning, and consumer electronics pave the way to a kind of location-based service that relies on the tracking of the continuously changing positions of an entire population of service users. This type of service is characterized by large volumes of updates, giving prominence to techniques for location representation and update.This paper presents several representations, along with associated update techniques, that predict the present and future positions of moving objects. An update occurs when the deviation between the predicted and the actual position of an object exceeds a given threshold. For the case where the road network, in which an object is moving, is known, we propose a so-called segment-based policy that predicts an object's movement according to the road's shape. Map matching is used for determining the road on which an object is moving. Empirical performance studies based on a real road network and GPS logs from cars areThe 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. reported.