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A scientific data extraction architecture using classified metadata

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Abstract

Data extraction and information retrieval from a great volume of data set always is a tedious and difficult work. Therefore, an effective and efficient technology for searching for desired data becomes increasingly important. Since metadata with certain attributes may characterize data files, to extract data with the help of metadata can be expectably to simplify the work. Metadata Classification has been proposed to improve significantly the performance of scientific data extraction. In this paper, a scientific data extraction architecture based on the assistance of metadata classification mechanism is proposed. The architecture is built by utilizing mediator/wrapper architecture to develop a scientific data extracting system to help oceanographer analyzing ocean’s ecology. The result of performance evaluation shows that the architecture with the help of metadata classification can extract user’s desired data effectively and efficiently.

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Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taipei University, 151, University Road, Sanhsia, Taipei County, 237, Taiwan

    Yue-Shan Chang & Hsiang-Tai Cheng

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  1. Yue-Shan Chang
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  2. Hsiang-Tai Cheng
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Correspondence to Yue-Shan Chang.

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Chang, YS., Cheng, HT. A scientific data extraction architecture using classified metadata. J Supercomput 60, 338–359 (2012). https://doi.org/10.1007/s11227-010-0462-7

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  • DOI: https://doi.org/10.1007/s11227-010-0462-7

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