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For over 20 years, ESIP meetings have brought together the most innovative thinkers and leaders around Earth observation data, thus forming a community dedicated to making Earth observations more discoverable, accessible and useful to researchers, practitioners, policy makers, and the public. The theme of the meeting is Putting Data to Work: Building Public-Private Partnerships to Increase Resilience & Enhance the Socioeconomic Value of Data.

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Wednesday, July 15 • 2:00pm - 3:30pm
Exploring New Perspectives and Formulating Best Practices for Data Uncertainty Information - Part 1

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In the Fall of 2019, the Information Quality Cluster (IQC) published a white paper entitled “Understanding the Various Perspectives of Earth Science Observational Data Uncertainty” (Moroni et al., 2019; DOI: 10.6084/m9.figshare.10271450). This paper provides a diversely sampled exposition of both prolific and unique policies and practices, applicable in an international context of heterogeneous policies and working groups, made toward quantifying, characterizing, communicating and making use of uncertainty information throughout the comprehensive, cross-disciplinary Earth science data landscape from the following four perspectives: Mathematical, Programmatic, User, and Observational. These perspectives affect policies and practices in a diverse international context, which in turn influence how uncertainty is quantified, characterized, communicated and utilized. The IQC is now in a scoping exercise to produce a follow-on paper that is intended to provide a set of recommendations and best practices regarding uncertainty information. It is our hope that we can consider and examine additional areas of opportunity with regard to the cross-domain and cross-disciplinary aspects of Earth science data. For instance, the existing white paper covers uncertainty information from the perspective of satellite-based remote sensing well, but does not adequately address the in situ or airborne (i.e., sub-orbital) perspective. The 2020 Winter ESIP meeting offered an IQC session that explored these additional perspectives from Uncertainty Quantification (UQ) and Uncertainty Characterization (UC) work completed with Argo float data (presented by Mikael Kuusela) and challenges from the lens of the upcoming S-MODE EV-S mission (presented by Fred Bingham). The 2020 Summer session intends to explore additional UQ/UC use cases and expand the scope of context as we decide how best to move forward with the follow-on paper. This “Part 1” session will feature a review summary of the 2019 white paper, followed by invited speakers who can help expand our existing knowledge gaps on the following focus areas for UQ/UC: in situ, airborne, data assimilation and numerical modeling. While there will be a brief opportunity for Q&A and discussion in this session, there will be a “Part 2” session reserved for a deeper dive, considering all perspectives of UQ/UC, toward developing a set of recommendations and best practices to be included in a follow-on paper. Agenda 
2:00-2:15    Introduction and Status of Recent Efforts - David Moroni
2:15-2:30    Representing uncertainty in models and observations for earth system prediction - Aneesh Subramanian (University of Colorado at Boulder, http://www.aneeshcs.com/
2:30-2:45    An end-to-end UQ framework in ocean modeling and data science  - Patrick Heimbach (University of Texas at Austin, https://heimbach.wordpress.com/)
2:45-3:25    Panel Discussion
3:25-3:30 Wrap-up

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View Session Notes
View Presentations: See attached.

  • Need to look into new use cases, particularly capturing modeling/assimilation and end user perspectives on implications of uncertainty on multiple interpretations of scientific assessments.
  • Recognition of the Emerging need to resolve the difference in spatio-temporal scales between in situ, airborne, satellite and modeled/assimilated data; common ways of resampling for data fusion applications, and understanding the uncertainty associated with data resampling (i.e., representation error).
  • Need to have discipline-independent, open-source tools to support UQ workflows for algorithm developers who are doing the UQ estimation, which would allow for more consistent representation of UQ in data files; having the UQ/UC information consistently represented with a common vocabulary in data files addresses users’ needs to use UQ/UC information in a manner that fits their purpose.

avatar for Robert R. Downs

Robert R. Downs

Senior Digital Archivist, Columbia University
Dr. Robert R. Downs serves as the senior digital archivist and acting head of cyberinfrastructure and informatics research and development at CIESIN, the Center for International Earth Science Information Network, a research and data center of the Earth Institute of Columbia University... Read More →
avatar for H. K. “Rama” Ramapriyan

H. K. “Rama” Ramapriyan

Research Scientist, Subject Matter Expert, Science Systems and Applications, Inc.
avatar for Ge Peng

Ge Peng

Research Scholar, CISESS/NCEI
Dataset-centric scientific data stewardship, data quality management
avatar for David Moroni

David Moroni

Data Stewardship and User Services Team Lead, Jet Propulsion Laboratory, Physical Oceanography Distributed Active Archive Center
I am a Senior Science Data Systems Engineer at the Jet Propulsion Laboratory and Data Stewardship and User Services Team Lead for the PO.DAAC Project, which provides users with data stewardship services including discovery, access, sub-setting, visualization, extraction, documentation... Read More →
avatar for Yaxing Wei

Yaxing Wei

Scientist, Oak Ridge National Laboratory

Wednesday July 15, 2020 2:00pm - 3:30pm EDT
Room 5