The Data Curation Network in partnership with the National Institutes of Health Office of Data Science Strategy is happy to announce a new training series aimed at helping data curators and information professionals in assisting researchers in making data publicly accessible via repositories.

The series will include three workshops throughout the spring and summer of 2025. Workshops will be held in-person in Bethesda, MD on the NIH campus and travel costs will be covered for selected participants. All workshops will center peer-to-peer engagement and active learning with hands-on exercises with datasets.

The intended audience for these workshops are information and data professionals, curators or archivists working within repositories, or others interested in further developing their curation skills. Due to limited travel funding, we are only able to consider applications from individuals based in the United States. Workshops will be capped at 20 participants to ensure collaborative learning opportunities.

Apply now!

Workshop 1 (March 4-5): CURATED Fundamentals This workshop will use the CURATED model to guide participants through key practices involved in the curation of research data. 

Workshop 2 (May 12-13): Specialized Curation for Code and Simulations-based Research: This workshop will take a deeper dive into the curation of code and simulations-based research. A prerequisite for this workshop is a basic understanding of the CURATED model.1

Workshop 3 (July 14-15): Specialized Curation for Geospatial and Scientific Images: This workshop will take a deeper dive into the curation of geospatial data and scientific images. A prerequisite for this workshop is a basic understanding of the CURATED model.2

Each workshop will select 20 participants using the existing DCN Rubrics

Deadline for applications is January 9, 2025 with decisions sent by the week of January 20. 

Individuals may apply for as many workshops as they wish but will be asked to provide answers for each workshop. The selection committee will aim to maximize attendance by balancing participation opportunities against individual preferences. There is space in the application form to indicate workshop preferences.  

Questions regarding these workshops can be sent to Mikala Narlock [mnarlock@umn.edu]. 

Learning Objectives for each workshop

This workshop series builds upon previously developed curricula, funded by the Institute of Museum and Library Services. Core materials are publicly accessible in the DCN GitHub with archival copies preserved through the University of Minnesota. This workshop series expands upon these curricula to focus on curation of unique data types within a focus on the health sciences.

CURATED Fundamentals Learning Objectives:

  • Increase understanding of data curation practices and tools in various disciplines, data types, and formats.
  • Share expertise and enhance curation capacity for librarians nationwide.
  • Meet like-minded colleagues who are interested in building and extending curation practices at their institutions.

Code Learning Objectives:

  • Identify and explain real-world examples of how differences between computing environments lead to reproducibility problems.
  • Navigate significant differences between major operating systems and understand how they affect the reusability of software
  • Identify several common programming languages used in research computing and the file types and tools associated with each.
  • Identify and document dependencies used in research software for common programming languages.
  • Identify and improve different types of documentation associated with source code and research software.
  • Describe differences between software licenses and non-software licenses, and differences between different kinds of open source software licenses.
  • Implement commonly used project organization strategies used in the research community.

Simulations Research Learning Objectives:

  • Gain a basic understanding of simulation data and simulation-based research for curation purposes
  • Understand how to develop discussions with researchers regarding their simulation data. Through guided interactions with each other, participants will develop dataset specific approaches to establishing key questions necessary for interacting with researchers and curating simulation data.
  • Work with example datasets to gain a better understanding of common tools, methods and practices used to produce and curate simulation data

Geospatial Learning Objectives:

  • Recognize Geospatial Data terms and have a tool for reference (glossary)
  • Recognize essential Geospatial metadata elements
  • Evaluate geospatial metadata and documentation
  • Differentiate between raster and vector data in the geodatabase
  • Use basic transformation tools to create open format files for sharing6 Students will be introduced to Ethical, Equitable, and Accessible geospatial data considerations

Scientific Images Learning Objectives: 

  • Understand scientific images: Define scientific images and discuss the complexities involved in understanding and interpreting them.
  • Identify knowledge gaps: Determine missing information or documentation in the practice datasets that limit the interpretation and reuse of scientific images.
  • Gain a basic understanding of important software: Introduce and demonstrate key software tools for viewing and manipulating scientific images.
  • Recognize Ethical and Sharing Concerns: Identify potential ethical issues specific to scientific images, such as those involving human subjects, endangered species, and fossil specimens with location information.
  • Discuss implications for curation and data sharing: Explore how transformations affect data interoperability, reusability, and preservation, and identify potential risks when transforming image data.
  • Discuss formats of images for preservation vs. interoperability vs. reusability: Compare and contrast different image formats based on their intended use.

These workshops were developed and piloted with generous funding from the Institute of Library and Museum Services [#RE-85-18-004018 and #RE-252343-OLS-22]. Through support from the NIH Office of Data Science Strategy and MITRE, we have expanded the curricula and are pleased to offer this new iteration of the workshops.

Instructors

CURATE(D) Fundamentals Instructors

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Sophia Lafferty-Hess, Duke University
Mikala Narlock, DCN/University of Minnesota
Leslie Kirsch,
Michael J. Fox Foundation
Joanna Thielen,
University of Michigan

Specialized Curation for Code and Simulations-based Research Instructors

Wanda Marsolek, University of Minnesota
Greg Janée, University of California, Santa Barbara
L. Weaver, University of Utah
Seth Erickson, University of California, Santa Barbara

Specialized Curation for Geospatial and Scientific Images Instructors

Neggin Keshavarzian, Princeton University
Kelly Grove, Florida State University
Tim Norris, University of Miami
Amy Schuler, Cary Institute of Ecosystem Studies
Mariah Kenney, Pittsburgh Super Computing Center
  1. Note: Individuals may complete the CURATED pre-requisite for the specialized workshops by either having attended a CURATED workshop in the past, completing the online CURATED modules, or attending a future virtual CURATED training to be offered in Spring 2025. ↩︎
  2. Note: Individuals may complete the CURATED pre-requisite for the specialized workshops by either having attended a CURATED workshop in the past, completing the online CURATED modules, or attending a future virtual CURATED training to be offered in Spring 2025. ↩︎