This post was authored by Halle Burns, Research Data Management Specialist at Princeton University.
As someone who joined the DCN only earlier this year, attending this years’ All Hands Meeting, from the Specialized Data Curation Workshop through the business meeting, especially as a member of the host institution, was such a treat! It was such a joy to meet everyone, put faces to names, and really learn from my peers. I greatly appreciated all of the conversations in which I was able to participate and the perspective that different DCN members were able to share.
While not new to data curation, the Specialized Data Curation Workshop was my first formal training since my graduate school days. As a Carpentries Instructor, I know all too well the challenges that can come with teaching an intensive curriculum, so I give major props to anyone who can get up and teach two full days of content, especially when it’s more on the technical side. I greatly appreciated Sherry, Wanda, Mikala, and Hannah’s hard work as planners and instructors for making this workshop hands-on and engaging (not an easy task).
One aspect that I truly treasured from the workshop experience was tied to hands-on activities and the ability to network and speak with others in the field. I found particular value in the extended exercise introduced near the end of the first day. The room was split into 4 groups (the tabular data group, sensitive data group, simulation data group, and the wildcard data group) and we were assigned a dataset to mock curate.
As a member of the Wildcard Group (go team!), I found this exercise extremely helpful and our team name very apt. When curating for Princeton’s repository, I never know what to expect. Will the data be a few files or several thousand thousand? What data types will be there? Topics, discipline, what level of documentation? Do I readily know how to open this type of file? Every dataset I curate is bound to be a wildcard in some aspect, something I personally find exciting. However, wildcard datasets always leave me with a level of uncertainty and a bit of imposter’s syndrome. Am I doing this right?
Curating this dataset with a group of people who all possessed different interests and experiences was extremely validating. We pooled our knowledge and our resources, asked each other questions, and reassured each other when something was unclear or uncertain. We were able to say, “Great idea! This is how I’ve approached this in the past and here’s why.” While this activity assisted us in applying the tools and approaches we gathered throughout the two-day workshop, I believe it also demonstrated the cornerstone of what the Data Curation Network represents: community, understanding, and support.
The workshop, as expected, gave me a chance to deepen my understanding of data curation and the various workflows and processes to be a successful curator. But I’d say, even more importantly than that, I left with a valuable reminder that I don’t need to be an expert in everything, because we’re in this together.