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A relevancy algorithm for curating earth science data around phenomenon.

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  • 1NASA, Marshall Space Flight Center, Huntsville, AL, USA.

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Summary
This summary is machine-generated.

This study introduces an automated method for curating Earth science data by topic, improving data discovery for researchers. The developed web service enhances data search and usability across various applications.

Keywords:
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Area of Science:

  • Earth science
  • Geospatial data management

Background:

  • Earth science data are fragmented across multiple archives, hindering discovery.
  • Traditional data curation is manual and does not scale for large, diverse datasets.

Purpose of the Study:

  • To develop an automated methodology for curating Earth science data by topic.
  • To improve data discovery and accessibility for both anticipated and unanticipated users.

Main Methods:

  • Developed a novel methodology using Earth science metadata for automated data curation.
  • Implemented a relevancy ranking algorithm to prioritize data.
  • Created a stand-alone web service to deploy the methodology.

Main Results:

  • Successfully automated the process of searching and selecting data around specific phenomena.
  • The web service effectively augments search and usability in various data tools.
  • Demonstrated improved data discovery capabilities through automated topic-based curation.

Conclusions:

  • Automated data curation using metadata is a viable solution for Earth science data discovery challenges.
  • The developed methodology and web service offer significant improvements in data accessibility and usability.
  • This approach supports broader scientific exploration by making data more discoverable.