The process of collecting pavement data has been evolving with advances in technology, thus generating huge amounts of data to be stored in pavement management systems (PMS) databases. The rapid size increases of these databases presents a challenge for state agencies, as they attempt to understand and take advantage of the data to support pavement maintenance and rehabilitation decisions. The knowledge discovery (KDD) process and data mining are being applied to large pavement data sets with the objective of extracting useful information. For example, the data can be used to predict pavement serviceability ratings (PSR), as an indirect way of obtaining the remaining life of pavements. The Missouri Department of Transportation (MoDOT) provided pavement condition data from 1995 to 1999 to be used in the study. Research is being conducted in which results from the whole set of data will be presented and interpreted in order to obtain a better view of the condition of pavements in Missouri and be able to increase the effectiveness of the decision-making process. Parameters needed for future work that would improve the quality of information extracted are also presented.
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