The ResearchDataQ Editorial Board is pleased to share a new editorial by Stacie Powell, Data Services Librarian at Clemson University, and Stacy Winchester, Research Data Librarian at the University of South Carolina. In this editorial, the authors share their experiences working cross-institutionally to increase data sharing and data-related outreach across the state of South Carolina. You can read the editorial here.
Editorial: Motivating Institutional Action on Research Data Management through Assessment of Public Availability
The ResearchDataQ Editorial Board is pleased to share a new editorial by Ali Krzton, Research Data Management Librarian at Auburn University Libraries, entitled “Motivating Institutional Action on Research Data Management through Assessment of Public Availability.” In this editorial, the author discusses raising interest in research data among university research administrators by utilizing publicly available data from federally funded research projects at the university. You can read the editorial here.
Editorial: The Canadian Research Data Management Jumpstart Program
The ResearchDataQ Editorial Board is pleased to share a new editorial by Jennifer Abel, Jane Fry, Nick Rochlin, and Mathew Vis-Dunbar titled “The Canadian Research Data Management Jumpstart Program.” In this editorial, the authors reflect on the lessons learned from a pilot training program for Canadian researchers interested in Research Data Management. Read the editorial here.
Editorial: Dispatches From the Field: DCN Specialized Data Curation Workshops
The ResearchDataQ Editorial Board is pleased to share a new editorial by L Weaver, Wanda Marsolek, Tim Norris, Mariah Kenney, Amy Shuler, and Sophia Lafferty-Hess. In this editorial, the authors reflect on two successful Data Curation Network workshops that were offered in 2025. Read the editorial here.
Call for Proposals: Brief Editorials on Data Services Initiatives for ResearchDataQ
The ResearchDataQ Editorial Board (part of the ACRL Digital Scholarship Section) is seeking proposals for editorials to be published on the ResearchDataQ website. Editorials are brief, reflective pieces that describe research data services, support models, or related activities, whether at your institution or across the field more broadly. This is a lightweight publishing opportunity that is ideal for reporting on works in progress, pilot efforts, or emerging ideas and trends. We especially welcome perspectives from early career professionals or LIS students.
Possible subjects for editorials could include:
- Collaborative data management/services (computing infrastructure, storage, software/code, etc.)
- Data ethics (privacy, ethical sharing, data ownership, data governance, data sovereignty, etc.)
- AI and data
- Data and instruction or tools built for instruction
- Responses to government or institutional policy changes related to research data
- Data rescue efforts
- Secondary use of data: acquisitions of data, collection policies related to data
- FAIR data in practice
- Replication/reproducibility
- Or anything else you want to share with the ResearchDataQ audience!
Proposals (up to 250 words) should clearly describe:
1. The activities or concepts you intend to address;
2. How you implemented this and/or what would be required to implement it elsewhere;
3. How this relates to relevant existing recommendations, policies, or standards (if applicable).
Please submit proposals here by September 15th, 2025. We expect to notify authors of accepted proposals in October, and we will ask authors to expand accepted proposal topics into approximately 1000-1500 word editorials (ideally by late November, with the possibility to extend if needed). The editorials will be featured on the ResearchDataQ website on a rolling basis in winter 2026.
If you have any questions, please contact Whitney Kramer (chair) at wbk39@cornell.edu.
Sincerely,
ResearchDataQ Editorial Board: Whitney Kramer, Isaac Wink, and June Kim.
Editorial: From Concept to Community: The Journey of Data Services at the University of Rochester Libraries
The ResearchDataQ Editorial Board is pleased to share a new editorial by Heather Charlotte Owen, Sarah, Siddiqui, and Matthew Mariner of the University of Rochester Libraries. In this editorial, titled “From Concept to Community: The Journey of Data Services at the University of Rochester Libraries,” the authors detail the creation of the Data Services department at the University of Rochester Libraries, the roles of the librarians involved, and their plans for the future. Read the editorial here.
Editorial: If You Build Research Data Services (and Market Them Well), They Will Come
It is a pleasure to announce a new editorial by Songyao Chen and Joyce Garczynski of Albert S. Cook Library, at Towson University. In the editorial, titled “If you build research data services (and market them well), they will come”, the authors explain the efforts of a new data science librarian to revitalize and reinvigorate data services at Towson Library, which involved work on partnerships, outreach, improvements on already existing services, and a new communication strategy. Read the editorial here.
Editorial: “Data Collection Guidelines: Overview and examples of application”
We are thrilled to share that ResearchDataQ is publishing a new editorial today by Brianne Dosch and Sidney Gavel, from University of Tennessee, Knoxville. They describe the guidelines the library created to direct the acquisition of datasets for their library collections, so that they remain relevant and impactful for their users, while keeping the process flexible and adaptable. The editorial provides examples of application of their guidelines, and discusses how to consider usage statistics, licensing, and interactions with non-traditional vendors when managing dataset collections. Read the editorial here.
Call for Editorial Proposals by March 31st
The ResearchDataQ Editorial Board (part of the ACRL Digital Scholarship Section) is seeking proposals for editorials that will be featured prominently on the ResearchDataQ website. We are seeking editorials that describe services, support, or related activities around research data at your institution. Topics could include:
- Collaborative data management/services (computing infrastructure, storage, software/code, etc.)
- Data ethics (privacy, ethical sharing, data ownership, data governance, data sovereignty, etc.)
- AI and data
- Data and instruction or tools built for instruction
- Data policies, including responses or practices that institutions have put in place to respond to the OSTP memo and other recent policies (NIH DMS policy)
- Secondary use of data: acquisitions of data, collection policies related to data
- FAIR data in practice
- Replication/reproducibility
- Or anything else you want to share with the ResearchDataQ audience!
Proposals (up to 250 words) should clearly describe:
1. The services, support, or related activities you intend to address;
2. How you implemented this and/or what would be required to implement it elsewhere;
3. How this relates to relevant existing recommendations, policies, or standards (if applicable).
Please submit proposals here by March 31st, 2025: https://forms.gle/4UuJfHcneQPy9mao7. We expect to notify authors of accepted proposals in April, and we will ask authors to expand accepted proposal topics into approximately 1000-1500 word editorials (ideally by late June, with the possibility to extend if needed). The editorials will be featured on the ResearchDataQ website on a rolling basis in early summer or fall 2025.
If you have any questions, please contact Clara Llebot Lorente (chair) at clara.llebot@oregonstate.edu.
Sincerely,
ResearchDataQ Editorial Board: Clara Llebot Lorente, Whitney Kramer, Marla Hertz, Charissa O. Jefferson, Ali Krzton and Isaac Wink.
Editorial “Leveraging Task-Specific Large Language Models to Enhance Research Data Management Services”
We are excited to announce a new editorial by Briana E Wham, of The Pennsylvania State university Libraries. The editorial titled “Leveraging Task-Specific Large Language Models to Enhance Research Data Management Services” explores the potential for integrating Large Language Models to enhance data management and sharing services. The editorial provides a high level perspective of the topic, including some examples and discussing its limitations.
