Abstract
In this paper, we propose a comprehensive data integration and quality assurance model, called CHARIOT, for agro-meteorological data. This model comprised of two modules: an intermediary module and a data quality control module. The intermediary provides users with reliable and continuous access to heterogeneous weather databases from various sources; it also solves various compatibility issues in meteorological time series data. The data quality control tool consists of a multi-layer system spanning internal, temporal and spatial data checks. These two modules combined together provide users with clean and error-free inputs for weather-driven agricultural management decisions. When applying CHARIOT to weather data for a real-life agricultural application, CHARIOT is shown to be effective in controlling and improving data quality, which in turn leads to better and more accurate agricultural management decisions.
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