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 (@[email protected]) 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.