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From Sky to Earth: Data Science Methodology Transfer

Published online by Cambridge University Press:  30 May 2017

Ashish A. Mahabal
Affiliation:
Present address: Center for Data Driven Discovery, Caltech, Pasadena, CA 91125 email: aam@astro.caltech.edu, djorgovski@cd3.caltech.edu
Daniel Crichton
Affiliation:
Center for Data Science and Technology, Jet Propulsion Laboratory, Pasadena, CA, 91109 email: daniel.j.crichton@jpl.nasa.gov, emily.s.law@jpl.nasa.gov, john.s.hughes@jpl.nasa.gov
S. G. Djorgovski
Affiliation:
Present address: Center for Data Driven Discovery, Caltech, Pasadena, CA 91125 email: aam@astro.caltech.edu, djorgovski@cd3.caltech.edu
Emily Law
Affiliation:
Center for Data Science and Technology, Jet Propulsion Laboratory, Pasadena, CA, 91109 email: daniel.j.crichton@jpl.nasa.gov, emily.s.law@jpl.nasa.gov, john.s.hughes@jpl.nasa.gov
John S. Hughes
Affiliation:
Center for Data Science and Technology, Jet Propulsion Laboratory, Pasadena, CA, 91109 email: daniel.j.crichton@jpl.nasa.gov, emily.s.law@jpl.nasa.gov, john.s.hughes@jpl.nasa.gov
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Abstract

We describe here the parallels in astronomy and earth science datasets, their analyses, and the opportunities for methodology transfer from astroinformatics to geoinformatics. Using example of hydrology, we emphasize how meta-data and ontologies are crucial in such an undertaking. Using the infrastructure being designed for EarthCube - the Virtual Observatory for the earth sciences - we discuss essential steps for better transfer of tools and techniques in the future e.g. domain adaptation. Finally we point out that it is never a one-way process and there is enough for astroinformatics to learn from geoinformatics as well.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2017 

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