Data Management Training

From Earth Science Information Partners (ESIP)

Purpose

This wiki page intends to collect the resources and information relevant to Data Management Training Working Group in order to document the development effort.


Link to ESIP Data Stewardship Committee Wiki Page: Data Stewardship Committee Wiki


Email list

Join the discussions on the esip_dmtraining listserv at: http://lists.esipfed.org/mailman/listinfo/esip_dmtraining


Meeting Notes

Monthly meetings for this Working group are scheduled for the first Thursdays of the month at 8:30 am Pacific, 9:30 am Mountain, 10:30 am Central, 11:30 am Eastern.

Please use the following information to join Data Management Training Meetings/Calls:

  • To Join the meeting from your computer, tablet or smartphone.
  • You can also dial in using your phone.
  • United States: +1 (408) 650-3123
  • Access Code: 453-694-565


To see meeting agendas and notes relating the the Clearinghouse project, please use the following link:

Clearinghouse Project Meeting Agendas and Notes


Meeting Agendas and Notes for DMT Monthly Call


Meeting Agendas and Notes for the Role-Based Analyses of DMT Topics

Future Meeting Topics

  • Process of Developing knowledge & skill requirements for Marine Technologists - Shaun Smith, Florida State University
  • Open Science Framework & Data Management Skill Development - April Clyburne-Sherin
  • Report on RDAP 2016 - Shelley Knuth
  • Process for determining which of the existing Data Management for Short Course modules need to be updated - Ruth
  • Data management (core) skills

Collaboration Material

Data Management Core Skills R&D

Ideas for Funding Proposals

  • Suggestion from Justin Goldstein on 2015-02-27:
  • Pages 208-209 of the paper (Carlson, J., Johnston, L., Westra, B., & Nichols, M. (2013). Developing an approach for data management education: A report from the Data Information Literacy project. International Journal of Digital Curation, 8(1), 204–217. http://dx.doi.org/10.2218/ijdc.v8i1.254) describes how some results are not generalizable due to the small sample size. I'm thinking therefore that a future research project could deal with this problem by leveraging the libraries associated with the 15 Big 10 Institutions (14 schools + the Univ. of Chicago) as part of the Committee on Institutional Cooperation (CIC).