Difference between revisions of "Community Forum planning"

From Earth Science Information Partners (ESIP)
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=== Potential questions ===
 
=== Potential questions ===
*What is your vision for the future regarding scientific data? Please be bold and include fanciful, idealistic, lofty, and even utopian ideas.
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*Thinking 5 years down the road, what trends will impact the way your agency collects, manages, stewards and uses Earth science data?
* What do you think should be the scope of the study?
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*What trends or technologies will have the biggest impact?
**Given that either extreme of depth or breadth is of less general use, what exactly should we target?  
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*How will your agency respond to these trends?  What will be constant? What will have to change?
**Earth Science only or broader?  For example, does it make sense to start "small" in the Earth Sciences and then generalize?  Or, as data management problems across all domains are basically similar, should we start with the more general and perhaps go into greater detail later?
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*Is there an aspect of your job that keeps you up at night?  What would make your job easier?
**Data? Software?  Methodologies?
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*What is your vision for the future regarding scientific data?   Please be bold and include fanciful, idealistic, lofty, and even utopian ideas.
*What would be metrics for assessing study success?
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*Do you think an NRC study would be useful and worthwhile?  Why?
*An NRC data study is risky because the topic is extremely broad, the community of data users is vast and heterogenous (and can include commercial interests), and the outcome will not be a focused mission, facility, or research initiative.  How should that risk be managed?
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*If so, what do you think should be the scope of the study? How can we avoid a study that is so extreme in either depth or breadth that it is not useful?
 +
*Should the study be limited to Earth and Space Science only or should it be broader to include, say, biomedical, physical, and social sciencesIf broad, how broad? 
 +
*Does it make sense to focus the study at a low level, focusing on details in scientific domains of limited scope and then generalize?  Or, as data management problems across domains have some similar characteristics, should we start with the a broad perspective and descend into greater detail later?
 +
*Should the study also consider software and methodologies involved in data creation?
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*Any other comments?
  
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<html><iframe src="https://docs.google.com/forms/d/15qvn7M1anl-6pBgY9HVkJgoWXnMVF3P9vn1cvggdNts/viewform?embedded=true" width="760" height="500" frameborder="0" marginheight="0" marginwidth="0">Loading...</iframe></html>
  
 
=== Results ===  
 
=== Results ===  
 
<html><iframe width='500' height='300' frameborder='0' src='https://docs.google.com/spreadsheet/pub?key=0ArDAFB2BsbfRdHBWM053N3RabzhJSHJUZ2t0WGl6LVE&output=html&widget=true'></iframe></html>
 
<html><iframe width='500' height='300' frameborder='0' src='https://docs.google.com/spreadsheet/pub?key=0ArDAFB2BsbfRdHBWM053N3RabzhJSHJUZ2t0WGl6LVE&output=html&widget=true'></iframe></html>

Revision as of 17:52, December 6, 2013

As the workshop in January will be closed, in order to get community input we will create a place on the web, which we are calling the Community Forum.

Forum goals: inform the community, gather input.

Part 1, purpose for the forum

The amount of available data is growing exponentially, and the landscape of tools for analyzing and sharing data is evolving rapidly. These trends, in the context of a changing scientific culture, are leading to fundamental shifts in the practice of science, presenting both great opportunities and great challenges.

A unifying vision is needed to guide the development of cohesive, effective strategies and policies and address the data grand challenges that span multiple domains and organizations.

ESIP and representatives from the National Research Council (NRC) have been discussing the possibility of a high level study to accomplish that convergence. In July 2013, a plenary discussion at the Summer ESIP meeting brought these issues into focus as panelists considered the need and feasibility of establishing a NRC study on data developments, management, and stewardship in the Earth sciences realm. In January ESIP will be holding a workshop of invited participants to discuss the matter further. Our goal is provide a set of recommendations to the NRC regarding the scope and conduct of the study. A more complete discussion of the idea is presented in this article that was submitted to AGU EOS: http://wiki.esipfed.org/images/0/06/Data_Study_EOS_November_2013_Paper.pdf.

ESIP is a community-led organization. This community forum exists in order to inform our community of these developments. We also need to hear from the community in order incorporate community input into our recommendations. Please consider the questions below and let us know what you think!

There are two relevant sessions at the upcoming AGU meeting...

Part 2, Questions for the community

We do not need to coordinate these questions with any workshop planning, as the plan for the workshop is to not prime the participants with material a priori.

Potential questions

  • Thinking 5 years down the road, what trends will impact the way your agency collects, manages, stewards and uses Earth science data?
  • What trends or technologies will have the biggest impact?
  • How will your agency respond to these trends? What will be constant? What will have to change?
  • Is there an aspect of your job that keeps you up at night? What would make your job easier?
  • What is your vision for the future regarding scientific data? Please be bold and include fanciful, idealistic, lofty, and even utopian ideas.
  • Do you think an NRC study would be useful and worthwhile? Why?
  • If so, what do you think should be the scope of the study? How can we avoid a study that is so extreme in either depth or breadth that it is not useful?
  • Should the study be limited to Earth and Space Science only or should it be broader to include, say, biomedical, physical, and social sciences? If broad, how broad?
  • Does it make sense to focus the study at a low level, focusing on details in scientific domains of limited scope and then generalize? Or, as data management problems across domains have some similar characteristics, should we start with the a broad perspective and descend into greater detail later?
  • Should the study also consider software and methodologies involved in data creation?
  • Any other comments?


Results