Abstract

Abstract. Despite data quality has been long recognized as an essential component of geospatial data, it didn’t receive its deserved attention in the GIS-based applications. Due to the lack of a comprehensive framework for modelling, distribution and analysis of data quality of heterogeneous geospatial data, users are often forced to deal with data of unknown or unclear quality, an unpredictable level of risk is hence inevitable. With the rapid growth of data sharing mechanism, a close link between data producers and domain users must be established. We argue the use of quality information must be fully integrated with the commonly used GIS functions and further extended to the visualization of operation results. This is especially necessary for users who do not possess the required knowledge to correctly interpret the illustrated results in GIS-based interface. We first proposed a quality-aware workflow driven by standardized quality information, then use "data select" function as an example to demonstrate how the consideration of quality information can be assimilated into the design of GIS functions to ensure the correct interpretation of final results. The proposed workflow will not only improve the interoperability when integrating geospatial data from different resources, but also tremendously upgrade the intelligence of GIS-based operations to avoid wrong decision making.

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