IDEA: Improving Data Engagement and Advocacy

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/

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.

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.

With the increased focus on research reproducibility and transparency, new policies, practices, and principles have been established for research data management. As this area has and continues to rapidly change, we have also seen the development of research data management services to support researchers in adopting or adapting practices to meet these new expectations. But what form have these service models taken and what works and what doesn’t?

Many RDM support service models initiated in Libraries, but have discovered that to fully support researchers a multi-stakeholder service model is necessary because research practice and researchers’ questions require expertise across research data management, IT, research computing, and security. And while many examples of these multi-stakeholder service models exist, there are still gaps as well as potential to improve on existing models.

In this episode, we will be reviewing an article published in the Journal of eScience Librarianship on February 15th as part of the 2022 Research Data Alliance and Preservation (RDAP) Summit special issue. The article is titled “There’s no “I” in Research Data Management: Reshaping RDM Services Toward a Collaborative Multi-Stakeholder Model” and was authored by Alisa B. Rod, Biru Zhou, and Marc-Etienne Rousseau.

Article citation: Rod, A. B. & Zhou, B. & Rousseau, M., (2023) “There's no "I" in Research Data Management: Reshaping RDM Services Toward a Collaborative Multi-Stakeholder Model”, Journal of eScience Librarianship 12(1), 1–17. doi: https://doi.org/10.7191/jeslib.624

A lot of engagement work with researchers centers around supporting their efforts to make the data underlying their research publicly available. It’s a critical step to advancing science and increasingly a requirement from different funders and publishers. Institutions have responded by developing and offering a variety of services to support their researchers. So how well are these services working? And how much are they costing?

The Realities of Academic Data Sharing, or RADS, Initiative is investigating these questions. Their project, supported by an NSF EAGER grant, is looking at three research questions: Where are funded researchers across these institutions making their data publicly accessible and what is the quality of the metadata? How are researchers making decisions about why and how to share research data? And finally, what is the cost to the institution to implement the federally mandated public access to research data policy?

Cynthia Hudson Vitale is the Director, Scholars and Scholarship at the Association of Research Libraries.

 Shawna Taylor is the Project Manager for the Realities of Academic Data Sharing (RADS) initiative at the Association of Research Libraries (ARL). In addition to managing the RADS project, Shawna is part of the research team of RADS, is an active member of the DCN, serving on numerous committees and interest groups, and contributes to other ARL work related to public access of research data.

Jake Carlson (@jrcarlso) is the Director of the Deep Blue Repository and Research Data Services (DBRRDS) department at the University of Michigan (U-M) Library. DBRRDS oversees the Library’s two institutional repositories: Deep Blue Documents, for articles, dissertations, presentations and other human-readable materials, and Deep Blue Data, for data sets and other machine-readable materials generated by the U-M community. Carlson’s work centers on developing and supporting services to publish materials of scholarly value that do not have a home in traditional publication structures, including research data, following FAIR and ethical practices. Carlson has authored or co-authored more than 20 articles on research data services in libraries. He is a co-editor, with Lisa Johnston, of the book "Data information Literacy: Librarians, Data and the Education of a New Generation of Researchers" published in 2015 by the Purdue University Press.

Jonathon Petters (@jon_petters) As Assistant Director of Data Management and Curation Services, Jonathan Petters supervises a team that provides research data management planning, training, and curation support, and including geospatial data services, to researchers across Virginia Tech through the University Libraries.

Resources Mentioned:

More info about the RADS initiative: https://www.arl.org/realities-of-academic-data-sharing-rads-initiative/

Data Services at Virginia Tech: https://lib.vt.edu/research-teaching/data-services.html and https://data.lib.vt.edu 

Shannon and Briana discuss the article “Promoting and Enabling Reproducible Data Science Through a Reproducibility Challenge” published in the Harvard Data Science Review. They provide a brief rundown of how the authors ran their reproducibility challenge, what lessons they learned from the challenge participants, and their arguments for why universities—their data science centers and research support units—have a critical role to play in promoting “actionable reproducibility." 

Article Citation: Liu, J., Carlson, J., Pasek, J., Puchala, B., Rao, A., & Jagadish, H. V. (2022). Promoting and Enabling Reproducible Data Science Through a Reproducibility Challenge. Harvard Data Science Review, 4(3). https://doi.org/10.1162/99608f92.9624ea51

Reproducibility Resources from MIDAS: https://midas.umich.edu/reproducibility-resources/

Introducing IDEA, the podcast about Improving Data Engagement and Advocacy. Hosted by Briana Wham and Shannon Sheridan. In our episodes, we’ll be bringing you interviews from real world data professionals who are engaging their researchers in new and novel ways. We’ll also be reviewing the literature and keeping you up to date on what’s getting published that’s worth a read. Or, in your case, a listen. We hope you’ll join us as we talk with our colleagues and see what’s working…or what’s not in the wider world of research data management. Our theme music is by Scott Holmes and a big thanks to the Research Data Alliance Interest Group “Engaging Researchers with Data” for supporting our work.