IDEA: Improving Data Engagement and Advocacy

To kick off the season, we're excited to highlight a new resource designed to help researchers strengthen their data management practices. We're speaking with Kristin Briney, the creator of the Research Data Management Workbook—a practical tool packed with hands-on exercises that guide researchers through key phases of the data lifecycle. We’ll explore the workbook's unique exercises and how researchers can use them to build their research skills as well as how data stewards can use the exercises to more efficiently and effectively support researchers. Also included is our sidebar on the upcoming accessibility requirements for data here in the USA. Kristin Briney is the Biology & Biological Engineering Librarian at the California Institute of Technology and author of the books “Data Management for Researchers” (Pelagic Publishing, 2015), “Managing Data for Patron Privacy” (ALA Editions, 2022) with Becky Yoose, and “The Research Data Management Workbook” (Caltech Library, 2023). She has a PhD in chemistry and an MLIS, both from the University of Wisconsin-Madison. Her research focuses on research data management, institutional data policy, and patron privacy with respect to library data handling. Kristin is an advocate for the adoption of the international date standard ISO 8601 (YYYY-MM-DD) and likes to spend her free time making data visualizations out of yarn. Resources Mentioned: Online edition of the Workbook: https://caltechlibrary.github.io/RDMworkbook/ Downloadable edition of the Workbook: https://doi.org/10.7907/z6czh-7zx60 Americans with Disabilities Act Title II Regulations: https://www.ada.gov/law-and-regs/regulations/title-ii-2010-regulations/ Fact Sheet: New Rule on the Accessibility of Web Content and Mobile Apps Provided by State and Local Governments: https://www.ada.gov/resources/2024-03-08-web-rule/

As season 2 of IDEA comes to a close, join us in hearing one last time from our interviewees as we ask all of them a new set of research data management themed questions. How do you measure the success of a researcher engagement activity? What do you think the next big trend in research data management is? What is your favorite form of researcher engagement and why? An episode a year in the making! A big thank you to our guests this season: James Edson, Jeffrey Glatstein, Craig Risien, Erin Barker, Michael Hofmockel, Thomas Serrano, Monika Bargmann, Michael Feichtinger, Emily J. Kate, and Daria Orlowska We'll see you all next season!

The Collections as Data initiative aims to expand the uses of archival data collections by making them more accessible, particularly in forms ready for computationally driven research and teaching. This initiative makes the data from these collections available so that researchers and the public can engage with them. In this episode, we have the pleasure of speaking with Daria Orlowska, Data Librarian at Western Michigan University, about her collections as data work where she not only worked with others to develop structured datasets from historical records, but also leveraged this collection to create data literacy curriculum. Daria Orlowska is a data librarian and assistant professor at Western Michigan University. As a former behavioral sciences research assistant, she bases her data education on first-hand experience with the frustration of managing data. In her current position, Daria advises on data management plans, creates data education resources and experiential workshop, provides consultations on data management, finding secondary data, and data project workflows, and advocates for researcher data needs. In addition, she helps curate datasets from archival collections that serve as data literacy teaching tools for college undergraduates and K-12 students alike. She holds an MSLIS from the University of Illinois at Urbana-Champaign. You can find all three lessons on OSF:- Third grade lesson: https://doi.org/10.17605/OSF.IO/F5HRA - Eighth grade lesson: https://doi.org/10.17605/OSF.IO/5BH92 - Undergraduate lesson: https://doi.org/10.17605/OSF.IO/PHZNK The lessons are licensed under CC0, with the hope that others will adapt, remix, or reuse them. When work on the new Michigan Memories portal completes (https://michmemories.org/), we hope to see them there as well.We used the Record of passing vessels at the South Haven light-station from 1878-1882 log as a basis for all three of our lessons. The original scanned primary source can be found in Western Michigan University's online collection (https://luna.library.wmich.edu/luna/servlet/detail/WMUwmu~90~90~1246014~154475:Record-of-passing-vessels-at-the-So). A transcribed version of this document can be found within Zenodo (https://zenodo.org/records/8044702).

In this episode, Shannon and Briana delve into the recently published NSF funded Realities of Academic Data Sharing (RADS) Initiative's report titled, "Making Research Data Publicly Accessible: Estimates of Institutional & Researcher Expenses." The report provides a retrospective analysis of the costs incurred by six academic institutions in making research data publicly accessible and offers recommendations and considerations for researchers, institutions, and funding agencies.  Report citation: Hoeflich Mohr, Alicia, Jake Carlson, Lizhao Ge, Joel Herndon, Wendy Kozlowski, Jennifer Moore, Jonathan Petters, Shawna Taylor, and Cynthia Hudson Vitale. Making Research Data Publicly Accessible: Estimates of Institutional & Researcher Expense. Washington, DC: Association of Research Libraries, February 2024. ⁠https://doi.org/10.29242/report.radsexpense2024⁠ Realities of Academic Data Sharing (RADS) Initiative: ⁠https://www.arl.org/realities-of-academic-data-sharing-rads-initiative/

In today’s episode, we have the pleasure of speaking with data stewards from the University of Vienna, who’ve created a training program with courses catering to PhD students, technical staff, and specific disciplines. The training covers general data management and specific topics such as support for particular infrastructure. And not only are they offering this training to their community, but they have taken active steps to assess the effectiveness of their training program.  Monika Bargmann is the Data Stewardess for the Faculty of Philological and Cultural Studies at the University of Vienna, Austria. Bringing people and information together and "translating" between diverse groups of stakeholders is the common thread through Monika's nearly 30 years of professional experience. Before joining the University of Vienna in June 2022, she worked as a librarian, archivist, research assistant, lecturer, data manager, and IT project coordinator. Monika holds master-level degrees in Library and Information Studies (FH Burgenland, Austria, and HBI Stuttgart, Germany) and in German Literary Studies (University of Vienna, Austria). She attended the “Data Librarian” and “Data Steward” certificate courses at the University of Vienna. Her professional passion is currently the long-term preservation of websites and web applications. Monika collects fiction with librarian characters, loves trees and forests, and is a Trekkie. Michael Feichtinger works as a data steward at the Centre for Microbiology and Environmental Systems Science at the University of Vienna. In this role, Michael supports researchers with data management and the adoption of FAIR data practices. Since March of 2023, Emily J. Kate has served as the Data Steward for the Faculty of Life Sciences at the University of Vienna. She holds a BA in anthropology and archaeology from the College of Wooster in Ohio and earned her MA and PhD in anthropology and demography from The Pennsylvania State University. Emily describes herself as "scientifically nosey" and enjoys connecting with scientists and developing custom solutions that meet their unique requests. In addition to helping researchers make their data management dreams come true, Emily is an avid baker and loves picnicking on the Danube with her husband, Zachary, and her perfect dog, Zoa. Research Data Management for the Life Sciences Course Zenodo: https://zenodo.org/doi/10.5281/zenodo.10512974 Research Data Management for the Life Sciences Course GitHub: https://github.com/feichtingerm/rdmlifesciunivie Liascript: https://liascript.github.io/

Shannon and Briana discuss the article: A Tiered Model for Data Management, Curation, and Sharing Support in Grant Proposals and Budgets in the Journal of eScience Librarianship. This case study discusses differing levels of support for researchers during projects, challenges arising from the tiered support model, and monitoring metrics from those using the services. Article citation: Johnson, A., (2023) “A Tiered Model for Data Management, Curation, and Sharing Support in Grant Proposals and Budgets”, Journal of eScience Librarianship 12(2), e702. doi: https://doi.org/10.7191/jeslib.702

There are many examples of embedded data curators that different institutions use to support their researchers' data management practices. But no two programs seem to work in the same way, or exist in the same setting. In this episode, we’re going to hear about an embedded data management and curation support service in the context of a US national lab, Pacific Northwest National Laboratory. The Advance Team is a group of librarians, curators, and engineers who work with various projects across the lab to support good data management practices. Dr. Erin Iesulauro Barker is a senior research scientist at Pacific Northwest National Laboratory. She has over 20 years of experience in computational modeling of the mechanical behavior of materials at multiple length scales, developing computational tools for automatically generating digital material samples, and developing highly parallel solver frameworks. Dr. Barker's current research focuses on integrating physical experiments, physics-based predictive simulations, and data analytics in robust frameworks to accelerate scientific understanding, process control, and the adoption of advanced manufacturing techniques in production. This work also encompasses developing a culture of intentional data stewardship, cross-training of materials scientists and data scientists, and building an Artificial Intelligence for Materials Science (AIMS) community across the laboratory and with key university partners. Michael Hofmockel has provided strategic leadership to a dynamic team dedicated to comprehensive research information management. Overseeing major data platforms, including the DataHub Platform, Michael Hofmockel emphasizes user-centered, standards-based continuity across projects, supporting researchers throughout the research lifecycle. Michael fosters collaboration and champions strategic success within the Research Computing Leadership team. Michael significantly contributed to the Advance Team's success by leveraging over three decades of data engineering and research experience. Michael has nurtured an environment conducive to scientific innovation by demonstrating scholarly communication and talent development expertise. Looking ahead, Michael's passion for fostering innovation positions them well to contribute to the ongoing success of the Research Computing Division at PNNL. Thomas Serrano is a Data Engineer at PNNL who does a lot of work involving the creation of data pipelines at the lab instrument level. This can involve moving, storing, or utilizing data in real-time to help with experiments. He graduated from the University of Washington in 2022 with a Bachelor of Science in Informatics with a concentration in Data Science.

Shannon and Briana discuss the article "The Effects of Research Data Management Services: Associating the Data Curation Lifecycle with Open Research Output" published in ACRL. They discuss how institutional contexts can influence a researcher's ability and desire to produce open data products, the impact of investing in RDM services and resources, and whether the data curation lifecycle impacts a researcher sharing their data. Article citation: Pares, N., & Organisciak, P. (2023). The Effects of Research Data Management Services: Associating the Data Curation Lifecycle with Open Research Output. College & Research Libraries, 84(5), 751. doi:https://doi.org/10.5860/crl.84.5.751

Research increasingly requires working with both large amounts of data as well as diverse types of data. Additionally, data reuse is being encouraged as a means to build on previous research and to enable answering larger and more complex problems through combining data sources. So, how can data producers make their data more openly available and reusable? And how can generating data and providing open access to it be an engagement opportunity? The Ocean Observatories (OOI) is a major facility fully funded by the National Science Foundation under Cooperative Agreement No. 1743430 to gather, distribute, and preserve real-time data of the world’s oceans. Their effort is an exceptional example of a project that makes immense amounts of data openly available in understandable ways as well as actively engages users of these data to further reuse potential.  Dr. James Edson is a Senior Scientist at Woods Hole Oceanographic Institution, Applied Ocean Physics and Engineering and the Lead PI of the Program Management Office (PMO) of the National Science Foundation’s Ocean Observatories Initiative (OOI).  Jeffrey Glatstein is the Senior Manager of Cyberinfrastructure and Data Delivery Lead at Woods Hole Oceanographic Institution and the National Science Foundations' Ocean Observatories Initiative (OOI).  Craig Risien is the Project Manager for the National Science Foundations' Ocean Observatories Initiative (OOI) Cyberinfrastructure data center.  Resources Mentioned: https://oceanobservatories.org/ https://dataexplorer.oceanobservatories.org/

For the season finale, we're doing something a little different. As we've interviewed our guests over the course of the year, we've been asking each group same set of four questions, all related to research data management. What makes something an engagement opportunity? How do you define a dataset? What one piece of information do you wish all researchers knew about RDM? And what’s the best data success you’ve ever seen? Now, we bring you the answers. A big thank you to our guests this season: Julie Goldman, Sarah Hauserman, Karl Benedict, Jon Wheeler, Anna Sackmann, Elliott Smith, Amy Neeser, Lena Karvovskaya, Dan Rudmann, Stephanie van de Sandt, Meron Vermaas, Cynthia Hudson Vitale, Shawna Taylor, Jake Carlson, and Jonathon Petters.