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. Due to metadata with certain attributes characterizing the data files, to extract data with help of metadata can be expectably to simplify the work. In our previous work, we have proposed a Metadata Classification (MC) to improve significantly the performance of scientific data extraction. In this paper, we will propose a scientific data extraction architecture that is based on the assistance of classified metadata. The architecture is built by utilizing mediator/wrapper to develop a scientific data extracting system to help oceanographer to analyze the ocean’s ecology by means of temperature, salinity and other information. The result shows that the architecture with the help of metadata classification can extract user’s desired data effectively and efficiently.
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Chang, YS., Cheng, HT. (2010). A Metadata Classification Assisted Scientific Data Extraction Architecture. In: Bellavista, P., Chang, RS., Chao, HC., Lin, SF., Sloot, P.M.A. (eds) Advances in Grid and Pervasive Computing. GPC 2010. Lecture Notes in Computer Science, vol 6104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13067-0_70
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DOI: https://doi.org/10.1007/978-3-642-13067-0_70
Publisher Name: Springer, Berlin, Heidelberg
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