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Data mining is presented in this paper as an example of geoinformatics, to illustrate how a collaborative effort between data-mining experts and geoscientists is essential for analyzing large volumes of data to extract knowledge. There is a wide variety of mining algorithms and tools available for both predictive and descriptive data mining that have been applied on a variety of geoscience problems. This paper provides a high-level overview of the data-mining process, several mining algorithms and tools, and their application to the geosciences. It also describes the geoscience data characteristics that make mining these data a challenge, and details some of the common data preparation operations that are required to make the geoscience data ready for mining. Three data-mining applications are presented in detail in this paper to demonstrate the usefulness of data mining to solve specific geoscience problems. Issues relevant in determining a successful data-mining application in geoscience are presented as lessons learned. Finally, the paper looks at challenges ahead by focusing on two relevant research areas for data mining and geosciences: mining streaming data in real time and exploiting the emerging cyberinfrastructure for mining.

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