[CRYOLIST] Arctic Data Workshop at University of Maine - Second Circular

Arctic Data Workshop icecores-group at maine.edu
Wed Jan 30 06:42:10 PST 2019


Second Circular - Arctic Data Workshop

On behalf of the Organizing Committee, we are pleased to announce that the
NSF-funded Arctic Data Workshop at the University of Maine, Orono on 14-16
May 2019 is accepting new applications.
Application form

To apply to attend the NSF 2019 Arctic Data Workshop (
http://arctic.icecoredata.org/) at the University of Maine from 14-16 May
2019, please send an email to icecores-group at maine.edu by March 1, 2019.
Applications will be reviewed on a rolling basis.

Please include your:

   1.

   First name
   2.

   Last name
   3.

   Contact email
   4.

   Institution
   5.

   Current role in the research projects(s) (e.g. Master’s student, Ph.D.
   student, researcher, professor, etc.)
   6.

   Whether or not you’ve had a conversation with any of the meeting
   organizers (so we know how to most efficiently route your application)


(strongly encouraged) Please answer the following questions in the body of
the email to help us better prepare for the workshop:


   1.

   What is is your primary area of expertise/study?



   1.

   Why are you interested in participating in the 2019 Arctic Data Workshop?



   1.

   Please indicate your level of expertise for the following software
   packages (novice/moderate/expert):
   1.

      Github
      2.

      Python
      3.

      Jupyter Notebooks
      4.

      R
      5.

      NCL (NCAR Command Language)
      6.

      Octave



   1.

   Can you recommend any software, datasets, or publications you produced
   that may be relevant to the workshop goals (see below)?



   1.

   For those working in data/software – Please provide a brief description
   of the most extensive program you have written in the past two years.
   Include programming environment and indicate the program operational
   purpose.



   1.

   For those working in earth/climate science – Please list any climate
   reanalysis or paleoclimate reconstruction or proxy products that you
   developed in the last two years.

About the workshop

Please check the workshop website for the most current information:

http://arctic.icecoredata.org

The workshop goal is to bring together a diverse group of researchers
(including faculty and graduate students) that are using or would like to
use ice core data available from the Arctic Data Center. The goal is to
learn about common research workflows that the community is using and to
test the applicability of selected Arctic data sets and software tools to
build the next generation of digital paleoclimate data products and
reconstructions.
Background Information

In the past decade, the volume and complexity of data available in ice core
science has grown rapidly. This increase has several major drivers: First,
an increase in sampling frequency and quality has resulted in rapid
generation of data. Second, advances in the Web and computer system
integration of related technologies have simplified data exchange. Finally,
the scientific community and funding agencies are supporting major efforts
to increase research transparency by requiring researchers to publicly
share project data collected during research in long term data
repositories. All of these converging elements hold the potential to
significantly boost scientific discovery due to the benefits of sharing
data with other disciplines, but new computing approaches are needed.

The 2019 Arctic Data Workshop will focus on evaluation and testing of tools
that simplify the use of publicly available Arctic data in a meaningful
way. The goal is to increase the ease and transparency of working back from
scientific results, for example a table within a publication, to the
original datasets from which the summarized data were derived. By actively
soliciting community-wide input and experience, the workshop will
incorporate and share with the community related best practices from code
development, digital curation, and software engineering.
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