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September Data Carpentry All-Stars!

Recognizing volunteers for their outstanding work in the community.

This post originally appeared on the Data Carpentry website

As a community-led organisation, Data Carpentry depends on our active and highly-engaged volunteer community to carry out many of our core activities. Volunteer efforts span a wide range of activities, including teaching workshops, developing and maintaining lessons, and training and mentoring new instructors, among many other efforts. Without the commitment of our volunteers, Data Carpentry would never be able to reach such a broad learner base and to make such a huge impact on our learners.

We’d like to make it a habit to actively recognise and publicly acknowledge the great work that is being done by members of our community. Because there are so many ways to contribute to Data Carpentry, we’d like to focus each month on a different way that our volunteers are making an impact. This month, we’d like to start out by showcasing the efforts of our most active instructors.

Every one of these Data Carpentry badged instructors has taught at least three workshops since January 2016, including at least one Data Carpentry workshop. Many are also actively involved in serving the Carpentry community in other ways.

A big thank you to:

  • Martin Callaghan
  • Emily Davenport
  • Westa Domanova
  • Auriel Fournier
  • Ivan Gonzalez
  • Christopher Hamm
  • Christina Koch
  • Mateusz Kuzak
  • Paula Andrea Martinez
  • François Michonneau
  • John Moreau
  • Hani Nakhoul
  • Lex Nederbragt
  • Joseph Stachelek
  • Sarah Stevens
  • Steve Van Tuyl
  • Lukas Weber
  • Jason Williams

On behalf of the Data Carpentry community, and all of our learners, we’d also like to offer a hearty thank you to all of our instructors!

Please join us again in upcoming months to recognise the great work being done by other segments of our community.

Important caveat: If you’re a Data Carpentry instructor who should be listed above, but aren’t, please let us know so we can correct our mistake! We sincerely apologise for any inadvertent omissions.

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