Development of a real-time data quality monitoring system using embedded intelligence

Rule-based reasoning and case-based reasoning have emerged as two important and complimentary reasoning methodologies in the field of artificial intelligence (AI). This paper describes the development of a real-time data quality monitoring system (CORMS AI) using case-based and rule-based reasoning. CORMS AI was developed to augment an existing decision support system (CORMS Classic) for monitoring the quality of environmental data and information and their respective computer based systems for use in NOAA Ocean Service´s oceanographic operational products.