A Theoretical Multi-Tier Trust Framework for the Geospatial Domain

Abstract

Sensory data also known as Geospatial data is collected in-situ or remotely by different types of sensors from different geographic locations, by different agencies and over a period of time. A vast amount of data is processed via web services. The quality of the techniques, models and algorithms applied along the processing chain in transforming sensory data critically influences the quality of the eventually derived information. In this paper we evaluate trustworthiness of the processing chain or workflow from data acquisition to knowledge discovery. We present work in progress of a theoretical multi-tier trust framework for processing chain from data acquisition to knowledge discovery in geospatial domain. Holistic trust will be computed trough a trust function that integrate take the existing trust models.