That's a wrap on season three of IDEA! As in seasons past, we're celebrating with our interviewees one final time as we ask them a new set of data management questions:

• If your role in research data management had a motto, what would it be?

• What’s the most creative solution you’ve seen to encourage researchers to embrace data management?
• If you could host a workshop on one exciting aspect of data management, what would the focus be?

As always, a big thank you to our guests this season: Kristin Briney, Carla Strubbia, Alessandra Soro, Matt Mayernik, Andrew Johnson, Claudius Mundoma, and Amber Gallant.

We couldn't do it without you!

In this episode, we’re thrilled to welcome Amber Gallant, Data Services Librarian at Royal Roads University, who will be sharing with us details about her innovative project, Byte-Sized Data Encounters. Amber was faced with the challenge of teaching doctoral students with limited time and the unique needs of a largely online program adoptable data management skills and she adopted an extremely creative approach. She used a micro-education approach which reimagined traditional training by weaving in short, engaging, and hands-on activities to spark curiosity, promote practical learning, empower doctoral students with data management skills, and make the material memorable. Together, we’ll explore how this informal, scaffolded model builds confidence and helps students develop data practices.

Amber Gallant is the Data Services Librarian at Royal Roads University. She is interested in data equity and accessibility issues, data justice (or, examining how people are fairly or unfairly represented as a result of their production of data!), data reuse, and exploring sources of secondary data. She brings this work to RRU in discussing data collection and methodologies, among other topics, with faculty and students conducting research. Outside work, she enjoys baking overly complicated desserts, attempting to sample every cheese known to humanity, and exploring the beautiful, unceded lands stewarded to this day by the Lekwungen-speaking peoples.

Resources Mentioned:

Byte-Sized Data Encounters OSF project: 10.17605/OSF.IO/K46C5

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.

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 

How an institution models their research data support services can substantially impact engagement with researchers, including the frequency, duration, or opportunity. In this episode, Shannon and Briana discuss a recent report from the Research Data Alliance Professionalising Data Stewardship Interest Group. They provide a brief synopsis of the nearly 50-page report and highlight some of the most interesting take-aways, with a focus on what survey questions can play into a data professionals engagement plan at their own institution.

Article citation: Ayres, B., Lehtsalu, L., Parton, G., Ádám Száldobágyi, Warren, E., Whyte, A., & Zimmer, N. (2022).RDA Professionalising Data Stewardship -Models of Data Stewardship Survey Initial Report. Research Data Alliance. https://doi.org/10.15497/RDA00075

Dataset underlying report: Ayres, Bill, Lehtsalu, Liise, Kuchma, Iryna, Parton, Graham, Száldobágyi, Ádám, Warren, Eleanor, Whyte, Angus, & Zimmer, Niklas. (2022). RDA Data Stewardship Organisational Models Survey 2021 Output Dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6665306

Content analysis article of US academic data librarian job ads: Khan, Hammad & Du, Yunfei. What is a Data Librarian?: A Content Analysis of Job Advertisements for Data Librarians in the United States Academic Libraries, paper, July 31, 2018. (https://digital.library.unt.edu/ark:/67531/metadc1225772/)

Today, we will be reporting on Researcher Challenges and Experiences with Data Services, published March 27, 2025, by Chelsea McCracken and Ruby MacDougall with ITHAKA S+R.

ITHAKA S+R has worked with 29 US and Canadian institutions over the past 2 years to gather relevant information to improve the coordination of research data services. The project has conducted a landscape survey of data service offerings and conducted interviews with researchers to explore practices and experiences with research data services. 

This report which highlights the results from the semi-structured interview portion of this research, exploring their practices and experiences using research data services.

Article citation: McCracken, Chelsea, and Ruby MacDougall. "Researcher Challenges and Experiences with Data Services." Ithaka S+R. Ithaka S+R. 27 March 2025. Web. 18 June 2025. https://doi.org/10.18665/sr.322388

Researchers are increasingly needing to know about software management, quality, accessibility, and sustainability in support of Open Science efforts and research reproducibility. However, standard practices or principles are not always applied to software and how researchers learn to manage software is often not formalized. In this episode, we will be learning how the Software Horror Escape Room was created and how this game has successfully engaged researchers with the concepts of software management.

Lena Karvovskaya (@LangData) is Vrije Universiteit Amsterdam's RDM and Open Science community manager. Her goal is to create an environment where researchers and support staff at VU Amsterdam can learn about data management and benefit from each other's knowledge. She visits RDM and OS expertise meetings and conferences at home and abroad and takes care of the proper dissemination of the latest knowledge throughout VU Amsterdam.

Dan Rudmann (@dan_rudmann@akademienl.social) is a Digital Scholarship Librarian at Leiden University focused on Research Software and Open Science.

Stephanie van de Sandt is an Open Science / Research Data Management training coordinator at the Vrije Universiteit Amsterdam. As such, she aims to expand the training curriculum at the university by offering new workshops around Open Science, and software and data management.

Meron Vermaas is a Research Software Engineer at the Vrije Universiteit Amsterdam.

Resources Mentioned:

Can you escape the Software Horror Escape Room?: https://nlesc.github.io/softwarehorrorgame/SoftwareHorrorGame.html :

Read about the Escape Room: https://vu.nl/en/stories/making-research-data-management-fun

View the source code here:https://doi.org/10.5281/zenodo.7350528

About the University of Leiden’s Centre for Digital Scholarship:

https://www.library.universiteitleiden.nl/about-us/centre-for-digital-scholarship

About VU Amsterdam’s Research Data Support: https://vu.nl/en/employee/research-data-support

About the the Netherlands eScience Center: https://www.esciencecenter.nl/

Shannon and Briana discuss the article “Data Management Planning for an Eight-Institution, Multi-Year Research Project” published in the International Journal of Digital Curation. They provide a brief rundown of how researchers in this case study leveraged data management plans to support coordination of a complex, multi-institution, and multi-year research project, provide insight into how the provided example data management plans can be used as demonstration and engagement tools with researchers, and discuss distinctions between data management plan policy requirements and the reality of research practice as well as what it means when you have a data management plan that actually informs research project practices. 

Article citation: Briney K,  Goben A, Jones K. (2022) Data Management Planning for an Eight-Institution, Multi-Year Research Project. International Journal of Digital Curation 17(1): PLoS Comput Biol 18(2): https://doi.org/10.2218/ijdc.v17i1.799.

With the rise in data intensive research and institutional, funder, and publishing requirements for data management and sharing, there is a lot of opportunity for education and engagement around how to best address data management during the research process. Researchers are increasingly needing support with how to properly manage their research outputs and develop workflows that support research reproducibility and open science. One common engagement avenue for librarians is education in the form of instruction, consultation, or outreach services. 

Our guests today have worked at their institution to tailor this type of support for their researchers. They wrote about their experiences in a  book chapter titled "Expanding Research Data Management to UC Berkeley Researchers: A Targeted Approach to Outreach and Instruction". It was published in the American Library Association book Teaching Data Management where they outlined 3 case studies exemplifying collaboration with Research IT to develop research data management outreach and instruction strategies that are both targeted and scalable. In this episode we discuss how they identified target audiences, got buy-in from them, and developed the education.

Anna Sackmann is the Data Services Librarian at the UC Berkeley Library. In this role, Anna oversees the Library Data Services Program, which guides scholars to discover, access, share, and preserve data through dataset acquisition, discovery and librarian-led instruction and consultations. She collaborates closely with librarians and other data focused campus organizations in order to provide holistic data support for researchers, faculty, and students.

Elliott Smith is the Emerging Technologies & Bioinformatics Librarian at the University of California, Berkeley, where he supports students, teaching faculty and researchers in Molecular & Cell Biology and Integrative Biology.

Working at the intersection of Libraries and IT, Amy Neeser (@pseudoAMYloid) has experience with data in all aspects of the research lifecycle. As the Consulting + Outreach Lead in Research IT at UC Berkeley, they coordinate the consulting efforts across the Data Management and Research Computing programs to offer a holistic approach to data and computation. Amy also facilitates Research IT's community, partnership, and outreach programs.   Their professional and research interests include interdisciplinary and open digital scholarship, innovative uses of technologies in academic environments, and critical digital literacy. Amy previously worked at the University of Michigan as the Research Data Curation Librarian and at the University of Minnesota in the Biological and Physical Sciences Libraries.

Resources Mentioned:

Check out the Berkeley team's book chapter, "Expanding research data management to UC Berkeley researchers: a targeted approach to outreach and instruction" at https://escholarship.org/content/qt50r821r1/qt50r821r1.pdf. 

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/

As research changes; becoming more data and computationally intensive, it is necessary for researchers to possess strong data management, data information literacy and data science skills. Research Data Service units in University Libraries themselves and in collaboration with disciplinary experts are well suited to offer training that bridges the gap between theoretical knowledge and application-specific or programming skills offering researchers the knowledge and how to to engage in this data and computationally intensive research environment. In this episode, Karl Benedict, a Professor, the Director of the Research Data Services and Information Technology Services programs, and a subject area expert for geospatial data and technologies with the College of University Libraries & Learning Sciences at the University of New Mexico, and Jon Wheeler, the Data Curation Librarian with the University of New Mexico Libraries, will discuss how the Research Data Services team at the University of New Mexico Libraries built a training portfolio to meet the data information literacy and data science needs of their research community. They will highlight how their training portfolio grew to include a variety of technical workshop topics, the diversity of methods they use to deliver these trainings, and how they assess success of these engagement opportunities.

Dr. Karl Benedict (@kbene) has worked since 1986 in parallel tracks of information management, geospatial information technology and archaeology. Within the College of University Libraries & Learning Sciences at the University of New Mexico (UNM) he serves as a Professor, as the Director of the Research Data Services (RDS) and Information Technology Services (ITS) programs, and as subject area expert for geospatial data and technologies. His previous experience includes fifteen years at UNM's Earth Data Analysis Center  (including five years as the EDAC Director), and work for the US Forest Service, National Park Service, and in the private sector conducting archaeological research, developing geospatial databases, performing geospatial and statistical analyses, and developing web-based information delivery applications. In these positions he has developed and managed the development of information technology and data management capacity in support of multiple research and application domains including public health, resource management, hydro-climate research, atmospheric modeling, disaster planning and mitigation, and renewable energy research. Dr. Benedict has translated this experience into both credit courses and workshops that are focused on skill building in data management and analysis and online application development, and his current work as a Carpentries instructor and instructor trainer.

Jon Wheeler is the Data Curation Librarian at the University of New Mexico, where he assists researchers with data management planning, curation, and archiving. As senior personnel on the NSF funded NM EPSCoR SMART Grid Center, Jon coordinates a statewide workforce development initiative focused on building capacity for data science education.

Resources Mentioned

The link to the Github repository where Karl and Jon develop and share their workshop materials is available here: https://github.com/unmrds. 

Information about the Carpentries can be found here: https://carpentries.org/. 

Information about the University of Arizona Research Data Services program can be found here: https://libguides.unm.edu/data

Shannon and Briana discuss the article “Ten simple rules for improving research data discovery” published in PLoS Computational Biology. They provide a brief rundown of what those rules are, what they thought about them, and how this paper serves a dual purpose–great ideas for opportunities to engage with researchers AND acting as an engagement opportunity itself.

Article citation: Contaxis N, Clark J, Dellureficio A, Gonzales S, Mannheimer S, Oxley PR, et al. (2022) Ten simple rules for improving research data discovery. PLoS Comput Biol 18(2): e1009768. https://doi.org/10.1371/journal.pcbi.1009768

A major challenge for researchers in the University setting, is a lack of standardized workflows for research data and a major challenge as data professionals supporting researchers with their research data needs is engaging with researchers at the right time. In this episode, we will be learning more about how Sarah Hauserman, Research Data Manager with Harvard Medical School, Research Computing, and Julie Goldman, the Countway Research Data Services Librarian with the Harvard Library, coordinated a partnership between data professionals in the library, research labs, and information technology departments to enhance institutional data services including creating resources and connecting with researchers during their on and offboarding processes.

Julie Goldman (@jgolds2) is the Countway Research Data Services Librarian with the Harvard Library. Julie collaborates with members of the Harvard Library community on building a data services program that addresses all stages of the data lifecycle. Julie works with students and faculty researchers in the sciences interested in writing data management and sharing plans, and partners with them to plan for the management of their data throughout the lifecycle of their research project. Julie is a certified Carpentries Instructor, involved in Open Access journal publishing, and experienced online course instructor. Through all this work, Julie promotes open science, reproducible workflows, and is interested in broadening scientific communication.

Sarah Hauserman (@lmardmwg) is a Research Data Manager with Harvard Medical School, Research Computing who collaborates with researchers to better organize, manage, and store research data throughout the various stages of the data lifecycle, as well as develop tools and resources to prepare data for sharing and reuse as required by institutions, publishers, and funding agencies. She also oversees Research Data Management seminars educating researchers, faculty, and staff about RDM recommendations for organizing, maintaining, storing, and sharing research data. Sarah earned a M.S. in Archives and Records Management and a M.A. in History from Simmons University. Her previous experience includes working as a Records Management Consultant for the City of Somerville, Massachusetts.

Resources Mentioned:

View RDAP Poster: Research Data Getting Everyone Onboard! (and Offboarded): Coordinating Data Services in the Lab: https://zenodo.org/record/6321216#.Yp5VMXbMKUk  

Access the Onboarding and Offboarding checklists: https://osf.io/pw7ed/

Visit the Longwood Research Data Management: Harvard Biomedical Data Management page: https://datamanagement.hms.harvard.edu

Access the Harvard Longwood Medical Area Research Data Management Working Group: Project Work: https://osf.io/2h65e/

View Medical Library Association project poster: Coordinating Data Services in the Lab: Connecting the Research Lifecycle: https://zenodo.org/record/6462246#.YpDL-i1h2Rs

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.

In this episode, we’re diving into a topic that’s gaining momentum across the research data community—assigning persistent identifiers, or PIDs, to instruments and facilities. As the research ecosystem continues to push toward greater transparency, reproducibility, and FAIR practices, recognizing the role of the tools and spaces where research happens has become increasingly important. But assigning PIDs to instruments and facilities isn’t just about metadata—it’s about creating connections across systems, surfacing valuable research infrastructure, and ensuring proper attribution.

Today, we’re speaking with three representatives from the NSF-funded FAIR Instruments and Facilities Research Coordination Network, Matthew Mayernik, Andrew Johnson, and Claudius Mundoma to hear insights from their FAIR facilities and instruments recent workshops, and explore how data professionals can serve as connectors and translators across stakeholder groups. 

Matt Mayernik is a Project Scientist and Deputy Library Director at the NSF National Center for Atmospheric Research. His work is focused on research and service development related to scientific data curation and digital scholarship topics, including persistent identifiers, metadata, and institutional repositories. He is also the Editor-in-Chief of the Data Science Journal.

Andrew Johnson is Associate Faculty Director for Data and Scholarly Communication Services in the University Libraries and Initiative Director for Research Data Management and Repositories in the Center for Research Data and Digital Scholarship at the University of Colorado Boulder (CU Boulder). His work includes overseeing research data management and curation efforts, open access publishing initiatives, and overall strategy for the CU Scholar open access repository. His research interests focus on emerging services and infrastructure for research data management and curation, open access publishing, and open science, particularly with regard to interdisciplinary and highly collaborative research. Johnson is Principal Investigator for the CU Boulder award that is part of the FAIR Facilities and Instruments collaborative NSF FAIR Open Science Research Coordination Network (FAIROS RCN) project.

Claudius Mundoma is the Director of Shared Instrumentation Facilities in the Office of Vice Provost and Dean of Research at Stanford University. He leads the strategy implementation and evaluation of the Shared Research Platforms initiative as well as oversee planning of future activities that elevate Stanford's shared facilities to the next level. Among many core duties, - collaborate with shared facilities leadership to address strategic and operational issues that impact the community, and support development of new services to advance Stanford’s research and education missions. Previously, led the Core Facilities and Shared Instrumentation team as the inaugural Director in the Research and Innovation at the University of Colorado Boulder. Before that, directed the Physical Biochemistry Facility in the Institute of Molecular Biophysics at Florida State University for nearly two decades.Resources Mentioned:https://ncar.github.io/FAIR-Facilities-Instruments/“Persistent Identifiers for Instruments and Facilities: Current State, Challenges, and Opportunities.” Journal of eScience Librarianship 13 (3): e964. https://doi.org/10.7191/jeslib.964.

In this episode, Briana and Shannon discuss an article that shares a novel development in the research data management engagement and support space - an AI virtual consultant designed by researchers at the University of Mannheim to address the persistent challenges researchers face in implementing FAIR data principles. This represents a groundbreaking approach to simplifying complex data management processes through AI-driven assistance.

Article citation: Shigapov, Renat, and Irene Schumm. "FAIR GPT: A virtual consultant for research data management in ChatGPT." arXiv preprint arXiv:2410.07108 (2024).

Data professionals often ask themselves: how can we make research data literacy and data management training more engaging, interactive, and fun?

In this episode, we explore two highly innovative and creative approaches designed to enhance understanding and transform how researchers interact with key concepts in research data and data management. 

Alessandra Soro (she/her) is a Community Manager working at 4TU.ResearchData: the community for research data and software professionals at the four technical universities in The Netherlands. Over the past few years, Alessandra has been involved in the development of various communities, such as the Community Managers Club and Queer Planet (a community for queer internationals in The Netherlands).

With a background in strategic communication, she develops games, initiatives, and art-related projects to connect people with meaningful (but unattractive) topics, such as data interoperability and civil rights. Alessandra has a creative approach to community building and is passionate about co-creating with members, as she believes that bringing different perspectives is the key to meaningful projects.

Carla Strubbia (PhD) has a background in health science and a strong interest in open science, health information technology, research data management and responsible AI. She specializes in the use of personal and qualitative data in research, drawing from her expertise in RDM best practices. She is passionate about creating engaging resources for researchers, support staff, and PhD candidates, fostering collaboration between participants and experts, and building meaningful networks. Carla’s work combines innovative approaches, such as the Data Hunters project, with critical reflection on design principles for online learning environments.

Resources Mentioned:

Data Hunters Card Game: https://doi.org/10.5281/zenodo.14713229

4TU.ResearchData repository: https://data.4tu.nl/

Nexum; data 4 art project: https://nexumdata4art.com/

In open science, universities are key to fostering adoption of best practices and can encourage these best practices through academic evaluation processes. Promotion and tenure committees are one of these processes. Committees often have the capability to evaluate articles and books, but assessing data and software is a recent development for which there are few guidelines. 

In this episode, Shannon and Briana go through ten proposed simple rules for recognizing data and software contributions.

Article citation: Puebla I, Ascoli GA, Blume J, Chodacki J, Finnell J, Kennedy DN, et al. (2024) Ten simple rules for recognizing data and software contributions in hiring, promotion, and tenure. PLoS Comput Biol 20(8): e1012296. https://doi.org/10.1371/journal.pcbi.1012296

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).