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Welcome to the Summer Meeting for the Earth Science Information Partners (ESIP)! The 2017 theme is Strengthening Ties Between Observations and User Communities. The theme is based on one of the goals in the 2015 - 2020 ESIP Strategic Plan, which provides a framework for ESIP’s activities over the next three years.
  • Check out the full 2017 Summer Meeting Guide here -> http://bit.ly/ESIP_Sum_Guide_2017
  • Find a map if the Indiana Memorial Union HERE.
  • There will be lots going on in Slack during the meeting, find your invite HERE. #summer_mtg

Miss the plenary? Click here to check it out!
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Wednesday, July 26 • 2:00pm - 3:30pm
Scientific Data Quality - Information Quality Cluster

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Session Summary

This session is intended to follow the plenary session (http://sched.co/As6G) on Scientific Quality, which has a special focus on data uncertainty. The purpose of the session is to continue discussion initiated during the plenary session inspired by the invited panelists’ presentations from the plenary session. It will foster a more collaborative interchange of technical information intended to help advance the Scientific Quality of Earth science data and to discuss effective ways to communicate uncertainty to a broader community. This session will feature an additional invited speaker who will join the plenary speakers to facilitate this discussion. The panelists’ diverse perspectives and subject matter expertise will enable exchange of ideas and deeper technical discussion with the active participants in the session. .

As indicated in the plenary session description, the Information Quality Cluster has formally defined information quality as a combination of the following four aspects of quality, spanning the full life cycle of data products: 1. Scientific quality; 2. Product quality; 3. Stewardship quality; and 4. Service quality. The focus of this session is on scientific quality, and especially on uncertainty. In the preceding plenary session, a panel of invited speakers from a variety of Earth science disciplines will have addressed questions such as: How is uncertainty determined and characterized in the products of their research or application? What are the major side effects and limitations of common statistical techniques used to quantify and characterize uncertainty? What is the impact of uncertainty on the quality of their data products? How is data uncertainty accounted for when multiple sources of data are spliced and woven into a single product? How do they document and convey the information about uncertainty to other scientific users? What is the best way of conveying uncertainty to (possibly skeptical) public?

This session provides for more discussion with the panelists and other practitioners in scientific data generation, scientific quality assessment, and management. The discussion is expected to help identify issues pertaining to understanding, capturing and conveying uncertainty and to recommend actions that the Earth science data community can readily act upon to ensure and improve the overall scientific quality of their datasets.

 

Agenda

Introduction - H. K. "Rama" Ramapriyan       10 min.

Panelist Presentation:

  1. Bridging the gap between data and models - Matthew Plumlee  (University of Michigan) 15 min.

Key Points and Issues from Plenary Session – David Moroni – 5 min.

Additional Comments from Plenary Session Speakers:

  1. Information about the Data is as Important as the Data itself - Carol Anne Clayson (Woods Hole Oceanographic Institution)    5 min.
  2. Data uncertainty: what is it, where does it come from, and why should we care? - Amy Braverman (Jet Propulsion Laboratory, California Institute of Technology)   5 min.
  3. Challenges in Evaluating a Global Climate Models with the Limited Observational Data Record - Isla Simpson (National Center for Atmospheric Research)   5 min.

Open Discussion - All

Details:

Session notes at https://docs.google.com/document/d/16crMtTMJ_cqh0hpirS4nwn7hu-HzB6i7nip2YhZtWY4/edit

Bridging the gap between data and models - Matthew Plumlee (University of Michigan)

Abstract:  Commonly, data are used for model verification, validation, and calibration. Because data can be noisy and biased and models can be inexact, it is often done ad-hoc and does not produce the desired results.  This talk gives a brief, high-level overview of the data/model gap and some conceptual approaches to better work at this interface.

Biography: Matthew Plumlee’s studies include a method for statistical experimentation and uncertainty quantification for complex systems.   He received his PhD from the Georgia Institute of Technology and has since worked as an Assistant Professor the University of Michigan.  This fall, he will be joining Northwestern University's Industrial Engineering and Management Science Department.

Abstracts of the talks and biographies of the speakers from the plenary session can be found at http://sched.co/As6G.


Moderators
DM

David Moroni

Data Engineer, Jet Propulsion Laboratory, Physical Oceanography Distributed Active Archive Center
I am a Data Engineer at the Jet Propulsion Laboratory working primarily on the PO.DAAC Project, which provides users with data stewardship services including discovery, access, sub-setting, visualization, extraction, documentation, and metadata for their oceanographic datasets... Read More →
avatar for Ge Peng

Ge Peng

Research Scholar, CICS-NC/NCEI
Dataset-centric scientific data stewardship, data quality management
avatar for H. K. “Rama” Ramapriyan

H. K. “Rama” Ramapriyan

Research Scientist, Subject Matter Expert, Science Systems and Applications, Inc.
Member, ESIP Data Stewardship Committee; Chair, ESIP Information Quality Cluster; Co-Chair, NASA ESDSWG Data Quality Cluster; NASA ESDIS Project (Assistant Project Manager, Retired).

Speakers | Moderators
DM

David Moroni

Data Engineer, Jet Propulsion Laboratory, Physical Oceanography Distributed Active Archive Center
I am a Data Engineer at the Jet Propulsion Laboratory working primarily on the PO.DAAC Project, which provides users with data stewardship services including discovery, access, sub-setting, visualization, extraction, documentation, and metadata for their oceanographic datasets... Read More →
avatar for Ge Peng

Ge Peng

Research Scholar, CICS-NC/NCEI
Dataset-centric scientific data stewardship, data quality management
avatar for H. K. “Rama” Ramapriyan

H. K. “Rama” Ramapriyan

Research Scientist, Subject Matter Expert, Science Systems and Applications, Inc.
Member, ESIP Data Stewardship Committee; Chair, ESIP Information Quality Cluster; Co-Chair, NASA ESDSWG Data Quality Cluster; NASA ESDIS Project (Assistant Project Manager, Retired).


Wednesday July 26, 2017 2:00pm - 3:30pm
1 - Dogwood 900 E 7th St, Bloomington, IN 47405

Attendees (31)