Machine-to-machine communication for automatic retrieval of scientific data

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2016-03
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American English
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M.S.
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2016
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Purdue University
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Abstract

With the increasing need for accurate weather predictions, we need large samples of data from different data sources for an accurate estimate. There are a number of data sources that keep publishing data periodically. These data sources have their own server protocols that a user needs to follow while writing client for retrieving data. This project aims at creating a generic semi-automatic client mechanism for retrieving scientific data from such sources. Also, with the increasing number of data sources there is also a need for a data model to accommodate data that is published in different formats. We have come up with a data model that can be used across various applications in the domain of scientific data retrieval.

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Indiana University-Purdue University Indianapolis (IUPUI)
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