Extension of Reliability Theory of Surveying Adjustment into Spatial Data Analytics

Reliability is one quality element of analysis results, and also one optimization criteria of analytical models construction. In surveying and mapping, Li Deren proposes two multi-dimensional alternative hypothesis of model errors discrimination and the gross error elimination of posterior error variance-based weight iterative algorithm. With the promotion of electromagnetic physics and ubiquitous computing, the surveying and mapping technologies have evolved into the geospatial information technologies. Accordingly, the reliability theory is extended from gross error processing, outlier analysis until credible service computation, and its analytical method is developed from statistical inference, optimization computation to logical reasoning. With the metaphor of linguistics, gross error proce-ssing can be considered as grammar analysis, outlier analysis considered as semantic analysis, and credi-ble service computing considered as pragmatic analysis. Roughly, here the reliability of spatial data analysis is formalized. Generally, the criterions of object function in optimization are energy minimization of physic systems, information maximization of data systems, and risk minimization of user decision systems. Nowadays, reliability modeling is holistic by considering the dialectical properties of the normal and anomaly, the interior and exterior, the static and dynamic, the subjective and objective. Upon the requirement of eco-social developments, internet-related big data is mostly related to human mental models, which brings us the great difficulties of modeling human irrationality and spatial cognition.