Edward J. Wright

Credibility Models for Multi-Source Fusion

This paper presents a technical approach for fusing information from diverse sources. Fusion requires appropriate weighting of information based on the quality of the source of the information. A credibility model characterizes the quality of information based on the source and the circumstances under which the information is collected. In many cases credibility is uncertain, so inference is necessary. Explicit probabilistic credibility models provide a computational model of the quality of the information that allows use of prior information, evidence when available, and opportunities for learning from data. This paper provides an overview of the challenges, describes the advanced probabilistic reasoning tools used to implement credibility models, and provides an example of the use of credibility models in a multi-source fusion process

Envisioning uncertainty in geospatial information

Geospatial Reasoning has been an essential aspect of military planning since the invention of cartography. Although maps have always been a focal point for developing situational awareness, the dawning era of Network Centric Operations brings the promise of unprecedented battlefield advantage due to improved geospatial situational awareness. Geographic information systems (GIS) and GIS-based decision support systems are ubiquitous within current military forces, as well as civil and humanitarian organizations. Understanding the quality of geospatial data is fundamental to using it intelligently. A systematic approach to data quality requires: estimating and describing the quality of data as it is collected; recording the data quality as meta data; propagating uncertainty through models for data processing; exploiting uncertainty appropriately in decision support tools; and communicating to the user the uncertainty in the final product. Bayesian reasoning provides a principled and coherent approach to representing and drawing inferences about data quality. This paper describes our research on data quality for military applications of geospatial reasoning, and describes model views appropriate for model builders, analysts, and end users.