[Esip-preserve] Student Fellow Telecon/Presentation on Data Citation

[Hou, Chung-Yi]

Hi everyone,

Thank you very much for your participation in the Doodle Poll.  

Based on the responses, the time that would accommodate the most people will be Thursday, May 14th, at 12pm ET/9am PT.

If you have not had a chance to fill out the Doodle Poll but would be interested in attending the presentation, please let me know, and I would be happy to be send you a meeting invite.

Thank you again.

Best regards,
Sophie
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Today's Topics:

   1. Student Fellow Telecon/Presentation on Data Citation
      (Justin Goldstein)


----------------------------------------------------------------------

Message: 1
Date: Fri, 1 May 2015 07:29:22 -0400
From: Justin Goldstein <jgoldstein at usgcrp.gov>
To: "esip-preserve at lists.esipfed.org"
        <esip-preserve at lists.esipfed.org>
Subject: [Esip-preserve] Student Fellow Telecon/Presentation on Data
        Citation
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        <CAPHi6spRDX9uJyrqEHLObWoZ7B7JzJiuj_MA8M9QbcHuYtZ=OQ at mail.gmail.com>
Content-Type: text/plain; charset="utf-8"

Dear Colleagues,
   Due to the myriad of activities performed by the Data Stewardship
Committee, we have a lot of material to discuss during our monthly calls.
In order to accommodate a longer presentation and discussion, our Student
Fellow Sophie Hou has therefore agreed to present her Masters research
during a special telecon.  Please find the abstract for her talk, which
pertains to data citation, below. Those interested in attending are asked
to complete the doodle poll available on the web page accessible at:

  http://doodle.com/5qwnp9yan6ehz4xi

Sophie and I look forward to this opportunity, and are looking forward to
hosting the active discussion.

Best,
Justin


Abstract:

 As scientific data volumes, format types, and sources increase rapidly
with the invention and improvement of scientific capabilities, the
resulting datasets are becoming more complex to manage as well.  One of the
significant management challenges is pulling apart the individual
contributions of specific people and organizations within large, complex
projects.  This is important for two aspects: 1) assigning responsibility
and accountability for scientific work, and 2) giving professional credit
to individuals (e.g. hiring, promotion, and tenure) who work within such
large projects.

  This presentation will provide an overview for the concept of data
citation, its current practices, and the strengths and weaknesses of the
current data citation methods when applied to climate model dataset.  Using the
NCAR Global Climate Four-Dimensional Data Assimilation (CFDDA) Hourly 40km
Reanalysis as a case study, the presentation will also demonstrate the
creation of a detailed attribution framework using a movie-credit
style.  Analogous
to acknowledging the different roles and responsibilities shown in movie
credits, the methodology developed in the study could be used in general to
identify and map out the relationships among the organizations and
individuals who had contributed to a dataset.  Finally, discussion
questions will be presented in order to consider how this framework could
be applied to create data attribution for other dataset types beyond
climate models datasets.

--
_________________________________
Justin Goldstein, Ph.D.
Advance Science Climate Data and Observing Systems Coordinator
US Global Change Research Program
1717 Pennsylvania Ave NW, Suite #250
Washington, DC 20006

O: (202) 419-3496
M: (202) 285-3005

e-mail: jgoldstein AT usgcrp Dot gov
http://www.globalchange.gov
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