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

SricharanLochan Gangaraju, Purdue University


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.




Liang, Purdue University.

Subject Area

Atmospheric sciences|Computer science

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