Improving Scientific Data Extraction using Metadata Classification

There are large scientific data archives manage and store huge quantities of data, deal with this data throughout its life cycle, and focus on particular scientific domains. Metadata can be used for assisting the information retrieval. Using metadata to represent the file system also reduces the processing required to handle operations. While the number of metadata file is daily incremental with the number of scientific data file increased, utilizing metadata file to help accessing daily-incremental data set is increasingly difficult. In this paper, we propose a Metadata Classification (MC) approach to construct a GridMap that is a two dimension array to assist user program quickly inquiring the target files. According to the performance evaluation, it shows that the MC approach has a significant performance enhancement in finding the target file.