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<p class="MsoNormal"><span style="font-size:13.0pt">Dear ESIP Information Quality Cluster (IQC) Members,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt">The ESIP IQC organized two successful sessions at the ESIP Winter Meeting (<a href="https://2020esipwintermeeting.sched.com/">https://2020esipwintermeeting.sched.com/</a>) in early January, one surrounding
the <a href="https://esip.figshare.com/articles/Understanding_the_Various_Perspectives_of_Earth_Science_Observational_Data_Uncertainty/10271450">
Uncertainty White Paper</a> published by IQC in late 2019 and the other one on Citizen Science Data and Information Quality. Below are some brief summary of each of the two sessions and links to the presentations given at our sessions.
<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="font-size:14.0pt;background:silver;mso-highlight:silver">Session 1: “<a href="https://2020esipwintermeeting.sched.com/event/XrhN/bringing-science-data-uncertainty-down-to-earth-sub-orbital-in-situ-and-beyond">Bringing Science
Data Uncertainty Down to Earth - Sub-orbital, In Situ, and Beyond</a>” led by David Moroni</span></b><b><span style="font-size:14.0pt"><o:p></o:p></span></b></p>
<p class="MsoNormal"><b><span style="font-size:13.0pt">Summary:</span></b><span style="font-size:13.0pt"> In the Fall of 2019, the Information Quality Cluster (IQC) published a white paper entitled “<a href="https://esip.figshare.com/articles/Understanding_the_Various_Perspectives_of_Earth_Science_Observational_Data_Uncertainty/10271450">Understanding
the Various Perspectives of Earth Science Observational Data Uncertainty</a>”. The intention of this paper is to provide a diversely sampled exposition of both prolific and unique policies and practices, applicable in an international context of diverse policies
and working groups, made toward quantifying, characterizing, communicating and making use of uncertainty information throughout the diverse, cross-disciplinary Earth science data landscape; to these ends, the IQC addressed uncertainty information from the
following four perspectives: Mathematical, Programmatic, User, and Observational. 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. This session featured invited speakers to help inform on such opportunities to expand the scope of the IQC’s awareness of what is being done with regard to uncertainty information, while also providing participants and observers with
an opportunity to weigh in a panel discussion. This feedback was used to help us decide on how best to move forward with a planned follow-on paper. The session began with an IQC overview and summary of the recently published uncertainty white paper, presented
by David Moroni (Jet Propulsion Laboratory). The next speaker, Fred Bingham (University of North Carolina at Wilmington), delivered a presentation entitled “Uncertainty quantification for in situ ocean data: The S-MODE sub-orbital campaign.” The last speaker,
Mikael Kuusela (Carnegie Mellon University), delivered a presentation entitled “Uncertainty Quantification for Spatio-Temporal Mapping of Argo Float Data”. All speakers took part as panelists in the approximate 25 minute panel discussion that followed in the
final segment of the session.<o:p></o:p></span></p>
<p class="MsoNormal"><b><span style="font-size:13.0pt">Key points and outcomes from the session:<o:p></o:p></span></b></p>
<ul style="margin-top:0in" type="disc">
<li class="MsoListParagraph" style="margin-left:0in;mso-list:l2 level1 lfo1"><span style="font-size:13.0pt">Uncertainty Quantification (UQ) and Uncertainty Characterization (UC) within the In situ and sub-orbital domain of Earth observation tends to be mostly
best-effort, non-standardized, and disconnected from the much larger, more well organized science teams and programs within the space-based remote sensing domain.<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l2 level1 lfo1"><span style="font-size:13.0pt">UQ, both within space-based remote sensing as well as in situ and sub-orbital, is lacking transparent, user-accessible information on covariances to
accompany the uncertainty.<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l2 level1 lfo1"><span style="font-size:13.0pt">Obtaining realistic uncertainty requires proper handling of the length scales and the non-Gaussianity of the data.<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l2 level1 lfo1"><span style="font-size:13.0pt">IQC needs to consider looking at land-cover as a use case for UQ/UC, specifically for the next paper.<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l2 level1 lfo1"><span style="font-size:13.0pt">In addition to the considerations above, the next IQC white paper needs to provide concrete recommendations for the community, working with NetCDF-UQ
(Ken Kehoe) or UncertML<o:p></o:p></span></li></ul>
<p class="MsoNormal"><b><span style="font-size:13.0pt">Link to Detailed Session Notes:</span></b><span style="font-size:13.0pt">
<a href="https://docs.google.com/document/d/1vfYBK_DLTAt535kMZusTPVCBAjDqptvT0AA5D6oWrEc/edit">
https://docs.google.com/document/d/1vfYBK_DLTAt535kMZusTPVCBAjDqptvT0AA5D6oWrEc/edit</a>
<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="font-size:14.0pt;background:silver;mso-highlight:silver">Session 2: “<a href="https://sched.co/XrhT">Citizen Science Data and Information Quality</a>” led by Yaxing Wei</span></b><b><span style="font-size:14.0pt"><o:p></o:p></span></b></p>
<p class="MsoNormal"><span style="font-size:13.0pt">Summary: The ESIP IQC has formally defined information quality as a combination of the following four aspects of quality, spanning the full life cycle of data products: scientific quality, product quality,
stewardship quality, and service quality. Focus of the IQC has been quality of Earth science data captured by scientists/experts. With the advance of mobile computing technologies, including smart phones, Citizen Science (CS) data have been increasingly becoming
more and more important sources for Earth science research. CS data have their own unique challenges regarding data quality, compared with data captured through traditional scientific approaches. The purpose of this session is to broaden the scope of IQC efforts,
present the community with the state-of-the-art of research on CS data quality, and foster a collaborative interchange of technical information intended to help advance the assessment, improvement, capturing, conveying, and use of quality information associated
with CS data. We invited 4 speakers from different organizations to share their experience, knowledge, and insights on different aspects of CS data and information quality, including:<o:p></o:p></span></p>
<ul style="margin-top:0in" type="disc">
<li class="MsoListParagraph" style="margin-left:0in;mso-list:l0 level1 lfo2"><span style="font-size:13.0pt"><a href="https://static.sched.com/hosted_files/2020esipwintermeeting/5f/IQC1-20191122_GLOBE%20data%20quality_ESIP_AmosAndersen_r1.pdf" target="_blank">Citizen
Science Data Quality: The GLOBE Program</a> – Helen M. Amos (NASA GSFC)<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l0 level1 lfo2"><span style="font-size:13.0pt"><a href="https://static.sched.com/hosted_files/2020esipwintermeeting/46/IQC2-Laura-ESIP-PPT-Jan82020.pdf" target="_blank">Can we trust the power of the
crowd? A look at citizen science data quality from NOAA case studies</a> - Laura Oremland (NOAA)<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l0 level1 lfo2"><span style="font-size:13.0pt"><a href="https://static.sched.com/hosted_files/2020esipwintermeeting/fd/IQC3-Turning%20citizen%20science%20into%20community%20science.pdf" target="_blank">Community
data for community science</a> - Andrea Thomer (University of Michigan) and Stephen C. Diggs (Scripps Institution of Oceanography / UCSD) <o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l0 level1 lfo2"><span style="font-size:13.0pt"><a href="https://static.sched.com/hosted_files/2020esipwintermeeting/0b/IQC4-2020_STIP_ESIP%20Talk%20BOWSER.pdf" target="_blank">Earth Challenge 2020:
Understanding and Designing for Data Quality at Scale</a> - Anne Bowser (Wilson Center)<o:p></o:p></span></li></ul>
<p class="MsoNormal"><b><span style="font-size:13.0pt">Key points and outcomes from the session:<o:p></o:p></span></b></p>
<ul style="margin-top:0in" type="disc">
<li class="MsoListParagraph" style="margin-left:0in;mso-list:l1 level1 lfo3"><span style="font-size:13.0pt">Quality assurance performed in the GLOBE project includes Standardized Protocols, Participant Training, Range and Logic checks, Photo Approval, etc.<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l1 level1 lfo3"><span style="font-size:13.0pt">Laura Oremland’s presentation examined 7 citizen science case studies conducted by NOAA. Some lessons learned include keeping things simple to increase
chances of data quality; pairing manual with automated checks ensures more complete error catching; value of metadata; and engaging volunteers with questions sooner rather than later.<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l1 level1 lfo3"><span style="font-size:13.0pt">Two potential efforts to ensure that Citizen Science data becomes Community Data: participatory action research and community peer review<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l1 level1 lfo3"><span style="font-size:13.0pt">Interoperable citizen science data is one of the goals for Earth Challenge 2020.<o:p></o:p></span></li><li class="MsoListParagraph" style="margin-left:0in;mso-list:l1 level1 lfo3"><span style="font-size:13.0pt">Potential topics for future IQC discussion: assigning DOIs for citizen science data; how to assess the maturity of citizen science data;<o:p></o:p></span></li></ul>
<p class="MsoNormal"><b><span style="font-size:13.0pt">Link to Detailed Session Notes:</span></b><span style="font-size:13.0pt">
<a href="https://docs.google.com/document/d/1lRp19SF9U727ureKjY38PHOF3EGUgE-BixYDs2KlmII/edit">
https://docs.google.com/document/d/1lRp19SF9U727ureKjY38PHOF3EGUgE-BixYDs2KlmII/edit</a><o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt">We want to thanks again to all the speakers and participants in our sessions. We look forward to your comments, feedbacks, and suggestions ~<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt">Best,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt;color:black">Yaxing Wei, Robert Downs, Ge Peng, and David Moroni</span><span style="color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt;color:black">ESIP Information Quality Cluster<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><a href="http://wiki.esipfed.org/index.php/Information_Quality">http://wiki.esipfed.org/index.php/Information_Quality</a>
<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt;color:black"> </span><span style="color:black"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:13.0pt"><o:p> </o:p></span></p>
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