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Building Scalable Knowledge Graphs for Earth ScienceKnowledge Graphs link key entities in a specific domain with other entities via relationships. From these relationships, researchers can query knowledge graphs for probabilistic recommendations to infer new knowledge. Scientific papers are an untapped resource which knowledge graphs could leverage to accelerate research discovery. Goal: Develop an end-to-end (semi) automated methodology for constructing Knowledge Graphs for Earth Science.
Document ID
20170011712
Acquisition Source
Marshall Space Flight Center
Document Type
Presentation
Authors
Ramachandran, Rahul (NASA Marshall Space Flight Center Huntsville, AL, United States)
Maskey, Manil (NASA Marshall Space Flight Center Huntsville, AL, United States)
Gatlin, Patrick (NASA Marshall Space Flight Center Huntsville, AL, United States)
Zhang, Jia (Carnegie-Mellon Univ. Pittsburgh, PA, United States)
Duan, Xiaoyi (Carnegie-Mellon Univ. Pittsburgh, PA, United States)
Miller, J. J. (Alabama Univ. Huntsville, AL, United States)
Bugbee, Kaylin (Alabama Univ. Huntsville, AL, United States)
Christopher, Sundar (Alabama Univ. Huntsville, AL, United States)
Freitag, Brian (Alabama Univ. Huntsville, AL, United States)
Date Acquired
December 13, 2017
Publication Date
December 11, 2017
Subject Category
Documentation And Information Science
Geosciences (General)
Report/Patent Number
MSFC-E-DAA-TN50133
Meeting Information
Meeting: AGU Fall Meeting 2017
Location: New Orleans, LA
Country: United States
Start Date: December 11, 2017
End Date: December 15, 2017
Sponsors: American Geophysical Union
Funding Number(s)
CONTRACT_GRANT: NNM11AA01A
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.

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