Data Curation Network Outputs
Persistent link for this collectionhttps://hdl.handle.net/11299/225718
Research and outputs from the Data Curation Network, a community of professional data curators, data management experts, data repository administrators, disciplinary scientists and scholars that represent academic institutions and non-profit data repositories who steward research data for future use. We strive to build a trusted community-led network of curators advancing open research by making data more ethical, reusable, and understandable.
Project website: https://datacurationnetwork.org/
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Item Indigenous data in an institutional repository: First steps toward putting the CARE Principles into practice(Data Curation Network, 2024) Zuniga, Alicia; Marsolek, Wanda; Hunt, ShandaThe authors collaborated to conduct an audit of Indigenous data in an institutional repository. As part of this work, the authors, led by Zuniga, created a list of search terms related to Indigenous data in Minnesota to help identify potential Indigenous datasets; a resource list of policies, practices, and documents related to Indigenous data; recommendations for DRUM based on findings; and a final report and roadmap so that others, including DRUM staff, can implement and build on the important groundwork established by Zuniga.Item Strengthening Research Infrastructure: Data Curation + Institutional Repositories(Data Curation Network, 2024) Darragh, Jen; Taylor, Shawna; Narlock, MikalaFrom the post: "In 2024, advocacy emerged as a focal point of external DCN activities, with members drawing on years of collaboration and expertise to emphasize the essential role of institutional repositories and professional data curation expertise. From surveying researchers and repository managers to publishing impactful articles and white papers, DCN members have provided compelling evidence underscoring the importance of local data stewardship and the value of contributions of data curators and curation in data sharing."Item Integrating the CURATE(D) Steps at the National Transportation Library's (NTL)(Data Curation Network, 2025-03) Long, Jesse Ann; Tvrdy, PeytonFrom the post: In June 2023 the National Transportation Library’s (NTL) Data Services Team incorporated the Data Curation Network’s CURATE(D) workflow into their data cataloging process. ... Our team was initially introduced to the Data Curation Network’s CURATE(D) Steps during their training events in early 2023. Seeing the potential for the CURATE(D) Steps to help NTL, we began the process of structuring the new workflow and documentation. Due to a backlog and minimal staff, the previous process was rather simple in nature, and the CURATE(D) Steps was a perfect tool to build upon our foundational workflow, close noticeable gaps, and ensure documentation throughout the whole process. The introduction of the CURATE(D) Steps additionally allows NTL to take a step forward in data management and data curation practices...Item Annual Report 2024: End of Year Highlights of the Data Curation Network(2025-01-31) Data Curation NetworkThis report showcases the numerous endeavors the DCN supports, including information about our members, our shared expertise and community of practice, research efforts, and governance. Highlights from the year include the dissemination of curricula for specialized data curation, updates from our partnership with the National Center for Data Services, and a continued focus on the community that is the heart of the DCN.Item Transforming Research with Data Curation Practices Webinar(Data Curation Network, 2024-11) Lafferty-Hess, Sophia; Marsolek, Wanda; Narlock, Mikala R.The Center for Open Science (COS) and the Data Curation Network (DCN) offered a webinar exploring how data curation can boost the accessibility, impact, and integrity of research. Learn about key curation practices, why they are essential for preserving and enhancing research outputs, and how to apply them effectively to various types of materials.Item Exploring Data Curation: Tools, Techniques, and AI in Summer Internship at NCDS(Data Curation Network, 2024) Phillips, JasmineExcerpt from the post: "During the summer of 2024, I had the opportunity to intern with the NNLM National Center for Data Services (NCDS) internship in partnership with the Data Curation Network (DCN). Working closely with Mikala and Shawna, along with two other interns, along with two other interns, we focused on cleaning, analyzing, and visualizing data related to data curator job postings and trends over time. Our project utilized the data pulled from the International Association for Social Science Information Service and Technology (IASSIST) job repository, containing job posts from 2005 through April 2024. The goal of the internship was to explore data curation related job trends over this time, while gaining hands-on experience with various tools used in data analysis and curation. Over the course of the summer, my fellow interns and I learned new programs and tools, such as Tableau, Akkio, and Voyant, while enhancing my skills in familiar tools such as Excel and OpenRefine. "Item Data curation: A guide to what and how(Data Curation Network, 2024) Narlock, Mikala R.Presented October 16, 2024 virtually to the National Cancer Institute Annual Data Sharing Symposium, this presentation provides a high-level overview of data curation with helpful resources for data stewards and researchers.Item A Newcomer’s Thoughts on Artificial Intelligence(Data Curation Network, 2024-09) Carlo, Kimberly GisselleExcerpt from the post: "I participated in the NNLM National Center for Data Services (NCDS) internship this summer, with the Data Curation Network (DCN) as a site host, with just a semester from the MLIS program at University at Buffalo under my belt. I was given the opportunity to work and learn from a researcher perspective, as well as to learn what it takes to be a data curator or data librarian. I entered this internship not expecting to use artificial intelligence (AI) at any point. When I found out that was an option to use with AI to curate data, albeit experimentally, I instantly thought to myself, “no, thanks.” I had a view about AI that most people probably have: AI is unethical, it steals work from others, and we don’t understand precisely where this information is originating from. "Item Institutional data repositories are vital(Science, 2024-09) Darragh, Jen; Narlock, Mikala R.; Burns, Halle; Cerda, Peter A.; Cowles, Wind; Delserone, Leslie; Erickson, Seth; Herndon, Joel; Imker, Heidi; Johnston, Lisa R.; Lake, Sherry; Lenard, Michael; Hofelich Mohr, Alicia; Moore, Jennifer; Petters, Jonathan; Pullen, Brandie; Taylor, Shawna; Wham, BrianaAs funding agencies and publishers reiterate research data sharing expectations, many higher-education institutions have demonstrated their commitment to the long-term stewardship of research data by connecting researchers to local infrastructure, with dedicated staffing, that eases the burden of data sharing. Institutional repositories are an example of this investment. They provide support for researchers in sharing data that might otherwise be lost: data without a disciplinary repository, data from projects with limited funding, or data that are too large to sustainably store elsewhere. The staffing and technical infrastructure provided by institutional repositories ensures responsible access to information while considering long-term preservation and alignment with international standards. To ensure continued access to invaluable research data, it is essential that publishers and funding agencies recognize institutional repositories as responsible and reliable data sharing solutions.Item Exploring the Reuse of DCN-Curated Data(Data Curation Network, 2024) Guerra, Jodecy; Taylor, Shawna; Narlock, MikalaFrom the blog post: "As a spring 2024 intern with the Data Curation Network (DCN), I had the opportunity to explore how data curation enhances data reuse. While the DCN effectively tracks its datasets using Digital Object Identifiers (DOIs), Mikala explained the network had not yet explored how, and if, datasets curated through the DCN are used or reused. My project in the spring aimed to investigate the extent of (re)use among DCN-curated datasets, emphasizing the importance of data curation in facilitating this process."Item The Importance of Data Ethics in Data Interpretation(Data Curation Network, 2024-08-15) Cunningham, TonjaReflections from NCDS Intern. From the intro: "As a newly minted MLS graduate, I embarked on the Spring 2024 National Center for Data Services (NCDS) / Data Curation Network (DCN) internship with a quaint perspective on data. I believed that data, particularly research data, existed as an objective collection of facts and figures, shielded from human biases. However, my internship experience has dispelled this notion. Data and research do not exist in isolation; they are shaped by the biases, assumptions, and limitations of those who generate, collect, analyze, and, most importantly, interpret it."Item Enabling data reuse: The imperative of data curation(2024) Narlock, Mikala R.Data sharing has long been viewed as essential for open scholarship, as a bulwark against misinformation and poor scientific practice. Increasingly, data sharing is becoming mandated, by funding agencies and publishers, leading to an increase in data sharing via generalist, institutional, and disciplinary repositories. In this deluge of data, and in a world of AI and Machine Learning, it is imperative that researchers and academic communities move beyond data sharing to data publication in trusted data repositories to enable future (re)use. Mikala Narlock, Director of the Data Curation Network, will provide a short overview of the current state of data sharing, highlighting the importance of data curation and opportunities for re-curation, and end with a call to action for individuals and communities.Item Value of Curation Webinar Slides(Data Curation Network, 2024) Lafferty-Hess, Sophia; Luong, Hoa; Marsolek, Wanda; Wright, SarahWhat is the impact of data curation? Do curated datasets have greater measurable value than non-curated datasets? How do researchers perceive the importance and value of the work performed by data curators? These are questions members of the Data Curation Network have been investigating. Through funding from the Alfred P. Sloan Foundation, we have been researching from different perspectives the value data curation provides. Members of the DCN conducted two surveys, one focusing on the repository managers and one on the researchers’ perspectives. The results overwhelmingly demonstrate what we felt all along: researchers value the work of data curators. This webinar dives into the collected data and invited active discussion.Item Championing Institutional Data Sharing Efforts(Coalition for Networked Information, 2024) Carlson, Jake; Narlock, Mikala R.Data repositories are an essential component of the emerging infrastructure that is needed for sharing, stewarding and preserving research data at scale. However, the landscape of data repositories is uneven, fractured, and evolving. In the absence of widespread domain repositories, many academic libraries have stepped in to fill this gap through developing institutional data repositories (data IRs) to meet the needs of researchers located at their host institution. However, much like domain repositories, data IRs are evolving at an uneven rate in isolation from one another. With the federal government’s recent release of community guiding documents such as the Desirable Characteristics of Data Repositories (DC-DR) and the Nelson Memo, the time is right for data IRs and data service providers to explore areas where they could collaborate more closely to develop consensus around best practices for providing data services and how we might better connect our individual infrastructures. The Data Curation Network (DCN) recently received funding from the NIH in support of developing community-centered approaches in advancing institutional data services and data IRs, to be developed at the Summit for Academic Institutional Readiness in Data Sharing (STAIRS). At STAIRS, attendees will assess the current state of institutionally based data services and data IRs, discuss areas of service and infrastructure that would benefit from cross-institutional approaches, and explore ways in which we could strengthen collective alignment with the DC-DR, the Nelson memo and other emerging initiatives. In this pre-recorded video, we will describe the work done by the DCN in exploring the need for greater alignment across institutions and share information about the upcoming STAIRS workshop, including how to apply to attend.Item DCN Response to Implementation Plan to Increase Public Access to USDA-Funded Research Results(Data Curation Network, 2024) Data Curation NetworkThe Data Curation Network submitted a response to the USDA’s Implementation Plan to Increase Public Access to USDA-Funded Research Results (Notice 2024-01673). With special thanks to Leslie Delserone (University of Nebraska-Lincoln), Laura Hjerpe (University of Virginia), Sherry Lake (University of Virginia), Matthew Murray (University of Colorado Boulder), and Jon Petters (Virginia Tech) for their comments and suggestions that are the foundation of this feedback.Item DCN Response to Best Practices for Sharing NIH Supported Research Software(Data Curation Network, 2024) Data Curation NetworkThe Data Curation Network submitted a response to the National Institutes of Health Best Practices for Sharing NIH Supported Research Software (RFI NOT-OD-24-005). With special thanks to Madina Grace, Laura Hjerpe, Greg Janée, Sherry Lake, Vicky Rampin, Nicholas Wolf, and Rachel Woodbrook for their comments and suggestions that are the foundation of this document.Item Annual Report 2023: End of Year Highlights of the Data Curation Network(2024-01-31) Data Curation NetworkThis report showcases the numerous endeavors the DCN supports, including information about our members, our shared expertise and community of practice, research efforts, and governance. Highlights from the year include four in-person workshops, our first in-person All Hands Meeting since 2019, and a continued focus on the community that is the heart of the DCN.Item DCN Response to NSF Public Access Plan 2.0(Data Curation Network, 2023) Data Curation NetworkThe Data Curation Network submitted a response to the National Science Foundation Public Access Plan 2.0: Ensuring Open, Immediate, and Equitable Access to National Science Foundation Funded Research. This response drafted by many individuals, including Sherry Lake, Ricky Patterson, and Vicky Rampin.Item Make it explicit: Surfacing Power and Ethics in the CURATE(D) Protocol(2023) Woodbrook, Rachel; Taylor, Shawna; Dolan, Lana Tidwell; Murray, Reina Chano; Narlock, Mikala R.; Calvert, ScoutIn 2018, the Data Curation Network (DCN) developed the CURATE(D) model, a standardized set of steps for curating research data with an eye toward the FAIR and CARE principles. The CURATE(D) model has proven to be a useful teaching tool for demonstrating data curation best practices; while practical and structured enough to provide a foundation for learners, it also provides enough flexibility to be adaptive for different disciplines and data format needs. The CURATE(D) model has been revised over the years to integrate feedback and keep pace with the evolving data curation profession. In the past year, the DCN has undertaken efforts to rework this model to be responsive to ethical and power considerations highlighted by data sovereignty and data justice movements. This has meant revising the guidance to make explicit the tacit, power-laden assumptions regarding data appraisal and selection criteria, sharing decisions, and the iterative nature of curation. In this presentation, attendees will be invited to compare the previous and current versions of this model, will learn about the revision process, and have the opportunity to provide feedback on the model. Presented at IASSIST 2023 in Philadelphia, PA.Item We're all in this together: Readying IRs to support federally funded research(2023) Carlson, Jake; Narlock, Mikala R.In 2023, during the Year of Open Science, the Data Curation Network will host collaborative workshop series to prepare US academic institutional repositories to align with the Desirable Characteristics of Data Repositories for Federally Funded Research (DC-DR). Issued by the National Science and Technology Council in May 2022, these guidelines promote a set of consistent attributes for researchers and funding agencies in selecting a suitable repository for sharing and preserving their data, findings and other research outputs. The release of the DC-DR and the White House Office of Science and Technology Policy Memo, “Ensuring Free, Immediate, and Equitable Access to Federally Funded Research,” is an opportunity to develop a common set of policies, standards and practices to better connect all types of data repositories. Both are important documents but neither provide a clear direction for repositories to implement the high-level guidance they provide. This is especially important for Institutional Repositories (IRs), which serve many disciplines and may be tasked with demonstrating alignment with different federal agencies’ requirements for federally funded research. IRs are critical infrastructure in supporting researchers who do not yet have disciplinary based repositories to use in meeting federal data sharing requirements. In order to ready US-based academic IRs to demonstrate alignment with the characteristics, the DCN hosted a series of virtual learning opportunities and an in-person workshop. In this presentation, we will report out on our progress thus far and invite feedback from participants. Presented to the Digital Library Federation 2023 Forum.