IN41C:
Quality Control and Provenance of Scientific Data: Data Producers and Consumer Perspectives I Posters

Submit an Abstract to this Session



Session ID#: 33691

Session Description:
Model Development, data analysis and end-user applications of scientific data are becoming increasingly popular and challenging. Although they may operate differently, they still share an important challenge: understanding the quality of the data being used. Thus, credibility becomes an important prerequisite for all stages of the data lifecycle, from observations used by models, to outputs generated by models, and finally the consumer applications that use the data. When integrating data from many sources, it is paramount that the Data Provenance is well understood, and this is a challenge faced across all data communities. From the use of metadata database engines to visualization techniques, researchers continue to look for techniques to best certify and document their data. The Jupyter notebook is one such example, but many others exist.


In this session, we invite presentations on value-added approaches to quality controlling scientific data effectively. Open-source technologies are particularly welcome.

Primary Convener:  Aparna Radhakrishnan, Geophysical Fluid Dynamics Laboratory, Princeton, United States; Engility, Chantilly, VA, United States
Conveners:  Mark Bushnell, CoastalObsTechServices, Virginia Beach, VA, United States, Eugene F Burger, NOAA Pacific Marine Environmental Laboratory, Seattle, WA, United States and Kevin O'Brien, University of Washington Seattle Campus, JISAO, Seattle, WA, United States; University of Washington/CICOES, NOAA/PMEL, Seattle, WA, United States
Chairs:  Mark Bushnell, CoastalObsTechServices, Virginia Beach, VA, United States and Kevin O'Brien, University of Washington Seattle Campus, JISAO, Seattle, WA, United States
OSPA Liaison:  Aparna Radhakrishnan, Engility, Chantilly, VA, United States

Cross-Listed:
  • A - Atmospheric Sciences
  • OS - Ocean Sciences
Index Terms:

1948 Metadata: Provenance [INFORMATICS]
1950 Metadata: Quality [INFORMATICS]
1994 Visualization and portrayal [INFORMATICS]
4260 Ocean data assimilation and reanalysis [OCEANOGRAPHY: GENERAL]

Abstracts Submitted to this Session:

Capturing and Understanding Experiment Provenance using NiNaC (288743)
Carlo Rosati, Princeton, NJ, United States
Preliminary GOES-R ABI navigation and registration assessment results (275237)
Bin Tan1,2, John Dellomo3,4, Robert Edward Wolfe1 and Alan D Reth5,6, (1)NASA Goddard Space Flight Center, Greenbelt, United States, (2)Science Systems and Applications, Inc., Lanham, United States, (3)NASA GSFC, Greenbelt, United States, (4)Global Science and Technology Inc Greenbelt, Greenbelt, MD, United States, (5)Chesapeake Aerospace LLC, Grasonville, MD, United States, (6)NASA Goddard Space Flight Center, Greenbelt, MD, United States
Lake Representations in Global Climate Models: An End-User Perspective (292762)
Richard B Rood1, Laura Briley2, Allison L Steiner3 and Karlie Wells1, (1)University of Michigan Ann Arbor, Climate and Space Sciences and Engineering, Ann Arbor, MI, United States, (2)University of Michigan, Great Lakes Integrated Sciences + Assessments, Ann Arbor, MI, United States, (3)University of Michigan, Climate and Space Sciences and Engineering, Ann Arbor, MI, United States
Efforts to integrate CMIP metadata and standards into NOAA-GFDL’s climate model workflow (275883)
Chris Blanton, Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States, Mick Lee, University of Maryland College Park, College Park, MD, United States, Erik E Mason, Engility, Science and Technology, Chantilly, VA, United States, Aparna Radhakrishnan, Engility, Chantilly, VA, United States and ES-DOC Team
Monitoring Satellite Data Ingest and Processing for the Atmosphere Science Investigator-led Processing Systems (SIPS) (260998)
Jennifer Witt1, Liam Gumley2, Jessica Braun3, Steve Dutcher4 and Bruce Flynn4, (1)Space Science and Engineering Center (SSEC), Madison, WI, United States, (2)Cooperative Institute for Meteorological Satellite Studies, Space Science and Engineering Center (SSEC), Madison, WI, United States, (3)University of Wisconsin-Madision, Space Science and Engineering Center (SSEC), Madison, WI, United States, (4)Space Science and Engineering Center, University of Wisconsin-Madison, Madison, United States
Data Quality Control: Challenges, Methods, and Solutions from an Eco-Hydrologic Instrumentation Network (299606)
David Eiriksson, University of Utah, Global Change and Sustainability Center, Salt Lake City, UT, United States, Amber Spackman Jones, Utah State University, Civil and Environmental Engineering, Logan, United States, Jeffery S Horsburgh, Utah State University, Civil and Environmental Engineering, Utah Water Research Laboratory, Logan, UT, United States, Chris Cox, Utah State University, Logan, UT, United States and Dylan Dastrup, Brigham Young University, Provo, UT, United States

See more of: Earth and Space Science Informatics