The University of New Mexico, as a DCN Ambassador Institution, will host an in-person data curation workshop experience October 23-24, 2023, in Albuquerque, New Mexico.

This free two-day training session expands on the CURATE(D) workflow as a training foundation to bring together library data specialists, discipline and functional experts in a peer-to-peer learning environment. You can view our workshop curriculum for an overview of our workshop agenda. Participants will be invited to create or update a data curation primer individually or as part of a group.

We especially invite applications from individuals at minority serving institutions, including Historically Black Colleges and Universities and Hispanic Serving Institutions, and members of historically oppressed communities. Applications are open to international participation. A limited number of seats will be reserved for applicants from the US Southwest.

Application Timeline

  • July 31: Applications open
  • August 25: September 1: Applications due– Deadline extended!
  • September 6: Applicants will be notified of status
  • September 13: Registration / confirmation required

The workshop is capped at 30 participants. Applications will be reviewed using this publicly available rubric.

Travel Logistics

The workshop will begin at 9am Mountain October 23 and end by 2:30pm Mountain on October 24.

Attendees are responsible for their own travel arrangements. There is no cost to attend the training, and some meals will be provided. There are additional external funding opportunities available, including through the Digital Preservation Outreach and Education Network.

The event location will be released as soon as possible, along with hotel recommendations.


Jon Wheeler (he/him) has been with the University of New Mexico’s College of University Libraries and Learning Sciences since 2012. As the Data Curation Librarian within the College’s Research Data Services unit, Jon supports researchers in the development and execution of data management plans, and the sharing and preservation of research data. Since 2018, Jon has also lead the New Mexico Cyberinfrastructure Training program, a workforce development component of the NSF-funded NM EPSCoR SMART Grid Center. In this role, he coordinates data science education initiatives throughout the state in collaboration with the state EPSCoR office and the Software and Data Carpentry organizations. Jon’s research interests include the automation of data curation workflows, and the development of methods to better assess the impact of open access institutional repositories.

Sophia Lafferty-Hess (she/her) obtained an M.S. in Information Science and a Master of Public Administration from the University of North Carolina (UNC) at Chapel Hill. Sophia currently works at Duke University as a Senior Research Data Management Consultant where she provides data management instruction and guidance on best practices for organizing, documenting, preserving, and publishing research data. Sophia has supported the curation and archiving of research data for over ten years, in her current role she also helps manage the Duke Research Data Repository and is a curator within the Data Curation Network. Prior to joining Duke, Sophia worked at the Odum Institute for Research in Social Science Data Archive. 

Rachel (she/hers) works with library professionals and campus researchers to support data management planning and implementation across the research process. This includes a focus on data sharing and archiving via the University of Michigan’s data repository, Deep Blue Data, for which she serves as a curator as well as the service coordinator. Rachel is particularly interested in data repositories as storehouses for cultural heritage information, and research communities who may be under-supported in data management, dissemination, and preservation. Her background is in qualitative research, languages and humanities and she has extensive experience from previous positions with international health and population data such as surveys, epidemiological surveillance, and disease registries.