Intelligent Search of Solar Data

Details Intelligent Search of Solar Data Intelligent Search of Solar Data

Jan 2012

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012aas...21914411h&link_type=abstract

American Astronomical Society, AAS Meeting #219, #144.11

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Scientific paper

The enormous amount of solar data, a result of new observational missions, needs to be stored and retrieved intelligently. Existing systems (e.g., the Science Archive of the Solar and Heliospheric Observatory (SOHO); soho.nascom.nasa.go) manage solar data merely using metadata (e.g., the time that images were taken) or other programmatic information. As a result, such systems can only support very primitive queries (e.g., images taken in June 2009). From such search results, scientists have to manually select their needed data for further analysis.
On the other hand, solar data, either raw or processed, are often associated with semantic information such as the active regions in an image and corresponding text annotations. Such semantic knowledge can provide much more insights to the data and can help scientists quickly find data that are related to a specific research goal or topic (e.g., solar flares or coronal mass ejections). A solar data management system should be able to intelligently utilize such relevant semantic data to facilitate solar data retrieval, and ultimately saves investigators valuable time.
In this work, we build a prototype for the intelligent retrieval and exploration of solar data by utilizing the semantic knowledge associated with raw or processed solar data. The core of this prototype is a "query processing” component that utilizes a unified index technique to support both simple basic queries (e.g., images taken in 2007) over the metadata and intelligent topic queries (e.g., image regions related to "Solar Flares” in 2007) over other complicated contents. This component leverages different types of data (especially semantic information) to improve the search accuracy. Besides this, another facilitating component is designed to provide user-friendly result exploration functionalities when the "query processing” component returns a set of query results.

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