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Crowdsourcing Guidelines for a Successful Data ...

Crowdsourcing Guidelines for a Successful Data Event: An Un(conference) Panel

Presentation given at Research Data Access and Preservation (RDAP) 2016.

Brianna Marshall

May 05, 2016
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  1. Crowdsourcing Guidelines for a Successful Data Event: An Un(conference) Panel

    Jamene Brooks-Kieffer Michelle Hudson Andrew Johnson Mark Laufersweiler Brianna Marshall Scott Martin Steve Van Tuyl University of Kansas Yale University University of Colorado University of Oklahoma University of Wisconsin University of Michigan Oregon State University RDAP 2016 | May 5, 2016
  2. Software + Data Carpentry Active learning environment with limited prepared

    slides (not the same as free form, defined lesson plan still there) •  Mistakes embraced and become teaching moments, especially wrt instructor mistakes •  Working test environment (software setups) Community •  Instructors are peers and not necessarily experts •  Come with a colleague or friend Learning new tools, lowering barriers, demystification Approaching best(better) practices
  3. -----Differences----- Focus: reproducibility in workflow with code *nix shell Language

    and code •  test driven development •  Beginner / Intermediate •  R/Python/Matlab Version Control •  Git and GitHub Capstones available •  NLT •  Pandas •  Geomics Focus: best practices for data management and visualization Domain specific (ecology, genomics, geo, social, etc.) Tools: •  Spx best practices •  SQL •  R/Python Coding •  Mostly for data munging and visualization •  Some reproducibility concepts SC DC
  4. Learn •  In-depth about one data event •  Snippets from

    multiple data events Fill out the event template (now or later) Take notes How to use this session
  5. Pick a group! Link to shared folder: http://tinyurl.com/RDAP16 2-2:45pm: Discussion

    groups 2:45-3pm: Wrap up During this session you can move from group to group as much or as little as you’d like.
  6. Add your data event to the shared Google Drive folder

    by Friday, June 3. We will publish all collected data events through the Open Science Framework by Friday, July 1.