Preparing, storing, and distributing multi-dimensional scientific data

Ranjeet Devarakonda, Yaxing Wei, Michele Thornton, Ben Mayer, Peter Thornton, Bob Cook

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Data of all sizes, generated by simulation and observation (i.e., instruments and satellites) activities, should be collected, stored, and organized, along with associated tools and research results, so that they are easily discoverable and accessible. Most observational data capture conditions at an exact point in time and are thus not reproducible, therefore it is imperative that initial data be captured and stored correctly the first time. In this paper, we will discuss how NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) is preparing, storing, and distributing large volumes of multi-dimensional scientific data using Daily Surface Weather Data and a corresponding Climatological Summaries Dataset (Daymet) as an example.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015
EditorsFeng Luo, Kemafor Ogan, Mohammed J. Zaki, Laura Haas, Beng Chin Ooi, Vipin Kumar, Sudarsan Rachuri, Saumyadipta Pyne, Howard Ho, Xiaohua Hu, Shipeng Yu, Morris Hui-I Hsiao, Jian Li
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2811-2813
Number of pages3
ISBN (Electronic)9781479999255
DOIs
StatePublished - Dec 22 2015
Event3rd IEEE International Conference on Big Data, IEEE Big Data 2015 - Santa Clara, United States
Duration: Oct 29 2015Nov 1 2015

Publication series

NameProceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015

Conference

Conference3rd IEEE International Conference on Big Data, IEEE Big Data 2015
Country/TerritoryUnited States
CitySanta Clara
Period10/29/1511/1/15

Keywords

  • Daymet
  • ORNL DAAC
  • Single Pixel Tool
  • THREDDS

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