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From Sky to Earth: Data Science Methodology Transfer

Published online by Cambridge University Press:  30 May 2017

Ashish A. Mahabal Open the ORCID record for Ashish A. Mahabal [Opens in a new window] ,
Daniel Crichton ,
S. G. Djorgovski ,
Emily Law  and
John S. Hughes
Ashish A. Mahabal
Affiliation:
Present address:Center for Data Driven Discovery, Caltech, Pasadena, CA 91125 email: [email protected], [email protected]
Daniel Crichton
Affiliation:
Center for Data Science and Technology, Jet Propulsion Laboratory, Pasadena, CA, 91109 email: [email protected], [email protected], [email protected]
S. G. Djorgovski
Affiliation:
Present address:Center for Data Driven Discovery, Caltech, Pasadena, CA 91125 email: [email protected], [email protected]
Emily Law
Affiliation:
Center for Data Science and Technology, Jet Propulsion Laboratory, Pasadena, CA, 91109 email: [email protected], [email protected], [email protected]
John S. Hughes
Affiliation:
Center for Data Science and Technology, Jet Propulsion Laboratory, Pasadena, CA, 91109 email: [email protected], [email protected], [email protected]
Rights & Permissions [Opens in a new window]

Abstract

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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.

Keywords

Data ScienceMachine LearningMeta-dataOntologies
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 12 , Symposium S325: Astroinformatics , October 2016 , pp. 17 - 26
Copyright
Copyright © International Astronomical Union 2017 

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