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2022 Summit

The RDAP Summit provides a venue for reaching across disciplines, institutions, and organizations to learn about common solutions to issues surrounding research data management. Attendees of the summit have multiple opportunities to expand professional networks and acquire practical knowledge and skills that can be applied to their own work and projects.

The 2022 summit was held virtually.

2022 RDAP Summit Planning Committee

Conference Planning Co-chairs

Tess Grynoch and Amelia Kallaher

Conference Planning Committee

Chao Cai, Hannah Calkins, Emily Kilcer, Jesse Klein, Rachel Martinez, Reid Otsuji, Ashley Thomas, Amy Yarnell

2022 RDAP Summit Sponsors

FigShare, SPARC (New Venture Fund), International Association for Social Science Information Services and Technology (IASSIST), Iowa State University Library, labArchives, University of Arizona Libraries, University of Wisconsin-Madison iSchool, University of Illinois Libraries, Virginia Tech University Libraries, NIH - National Library of Medicine, National Center for Data Services, and University of Wisconsin-Madison Libraries

2022 RDAP Summit Program 

Monday, March 14

12:00 pm - 2:45 pm: Workshop 1: Open Science Data Curation, Preservation, and Access by Libraries


Mark Call, Bryan Newbold, Jefferson Bailey, and Nici Pfieffer

Researchers, communities, and stakeholders alike are aligning on the need for and the importance of open infrastructure for supporting the production, distribution, and stewardship of public research. Commercial barriers, combined with a proliferation of data sharing platforms, contribute to a fragmented environment in which data, research outputs, as well as curation and long-term stewardship, are hampered by a lack of technical integration across the research lifecycle, reliability of access, and coordination with local library expertise and services. This fragmented environment impedes research reproducibility and scientific resilience. The Center for Open Science (COS) and the Internet Archive (IA) have combined forces to provide open, cooperative infrastructure for ensuring long-term access and preservation of research outputs from across the lifecycle. Harnessing COS’s Open Science Framework (OSF) with IA’s expertise in scalable digital archiving and global access technologies, these mission-aligned organizations have collaborated on archiving COS’s public registrations data for digital preservation and perpetual access via the Internet Archive. In this workshop, participants will gain skills to implement reproducible open science practices with OSF registrations, learn best practices for filtering and discovering registrations of interest using both OSF and IA platforms, and explore methods for extracting bulk registration data for further scientific inquiry and research.

12:00 pm - 2:45 pm: Workshop 2: Research Data Skills Building Community Support in the ESIP Data Management Training Clearinghouse


Karl Benedict, Director of Research Data Services in the University Libraries at the University of New Mexico

Nancy Hoebelheinrich, Principal of Knowledge Motifs LLC and Editor of the DMTC

Karl Benedict and Nancy Hoebelheinrich will showcase the newly enhanced capabilities of the Data Management Training Clearinghouse (DMTC) for searching, providing assessment feedback to resource creators and searchers on specific resources, and submitting and reviewing quality descriptions for learning resources. Workshop participants will have the opportunity to use the DMTC in hands-on practice with the new system, both to gain experience with the DMTC as a tool for their own teaching and learning, but also explore how the DMTC and its content can be used to support them as they work with their diverse communities. Based on both their experiences with the new DMTC and the experiences and needs they bring as teachers and learners, we will engage workshop participants in discussions about how to better support them as members and leaders of research data teaching and learning communities. The outcome of these discussions will contribute to further planning and development of the DMTC in meeting the expressed needs.

2:45 pm - 3:15 pm: Break

3:15 pm - 6:00 pm

Workshop 3: Design for Engagement, Inclusion, and Impact: Data Literacy Lesson Planning to Make a Difference


John Watts, Megan Oakleaf, Heather Charlotte Owen, and Tiana Johnson

Data librarians are always teaching—data literacy lessons for students, professional development for colleagues, and programming for faculty across multiple disciplines—often without formal training in instructional design or lesson planning. Without formalized training, data librarians might feel underprepared to design instructional episodes for students, faculty, or coworkers. Librarians, both those new to teaching and those with substantial instructional experience, must also continuously seek to improve their pedagogical practices, increase inclusivity in instructional spaces, and design equity into learner engagement.

A template for teaching prompts librarians to follow best practices for educational equity and inclusion, plan efficiently, and make considered decisions to ensure that time spent with learners is relevant and meaningful. This session presents a lesson plan template for data instruction that embeds backward design, inclusive teaching check-ins, and other instructional best practices. Examples will be shared from a range of data and information literacy contexts.

In this workshop, presenters will 1) begin by outlining the value of lesson planning for data instruction and reviewing lesson plan components along with examples from instructional scenarios. Next, attendees will 2) work in small groups to explore core elements of pedagogical best practices embedded in the template, including backward design, enduring understandings, learning outcomes, inclusive teaching practices, and learner assessment. Groups will unpack these concepts and return to the main session to share takeaways and questions. After clarifying their understanding, attendees will join a presenter-moderated breakout to 3) use a guided worksheet to draft lesson plans for their own teaching individually and then share their drafts with a partner for feedback. Finally, attendees will return to the main session to 4) consider opportunities to incorporate lesson planning into their teaching practice and explore options for self-reflection and ongoing lesson development.

Tuesday, March 15

12:00 pm - 1:20 pm: Welcome and Opening Keynote

Radical Inclusion for the Future of Data- and Computationally-intensive Social Science Research Support


Amelia Kallaher, Cornell University, Data Literacy Librarian

Tess Grynoch, University of Massachusetts Chan Medical School, Research Data & Scholarly Communications Librarian

Keynote speaker:

Claudia von Vacano, Cornell, Executive Director

Through a series of real-life cases and examples, Dr. Claudia von Vacano illustrates how the datafication of everything has changed the social science research landscape. She argues that open-source tools and methods and open science are making a computationally- and data-intensive research community an essential component of the larger university-based research ecosystem. The challenge, she posits, is building a radically inclusive professional learning community. Universities are among the most elite and hierarchical institutions and are selective and exclusionary. There is a caste system at play that doesn’t benefit knowledge creation in a world where many of our newest members of the community possess the most facility with technology and new forms of knowledge management. Dr. von Vacano describes her diverse Data Science Fellows program and how it adapts in different university contexts and responds to this significant challenge. At the center of the Data Science Fellows agenda are ethics, fairness, and empowerment through peer education.

Dr. Claudia von Vacano is serving as the Executive Director of the Cornell Center for Social Sciences, which is a large organization that provides research grants, grant writing assistance, research support, workshops, consulting, data services, and research IT. She is the Founding Executive Director, Senior Research Associate and Principal Investigator of D-Lab and Digital Humanities at UC Berkeley and is on the boards of the Social Science Matrix and Berkeley Center for New Media. She has worked in policy and educational administration since 2000, and at the UC Office of the President and UC Berkeley since 2008. She received a master’s degree from Stanford University in Learning, Design, and Technology. Her doctorate is in Policy, Organizations, Measurement, and Evaluation from UC Berkeley. Her expertise is in organizational theory and behavior and in educational and language policy implementation. The Phi Beta Kappa Society, the Andrew W. Mellon Foundation, the Rockefeller Brothers Foundation, and the Thomas J. Watson Foundation, among others, have recognized her scholarly work and service contributions. Currently, she is directing the NSF Improving Undergraduate STEM Education, which is led by UC Berkeley’s P.I. David J. Harding and co-P.I. Rodolfo Mendoza-Denton—conducting research on diversity in data science. She is also the co-P.I. of the Measuring the Hate Speech Project with Professor Chris Kennedy.

1:20 pm - 1:30 pm: Break

1:30 pm - 2:30 pm: Presentations Session 1


Ashley Thomas, Countway Library, Harvard Medical School, Digital Initiatives and Accessibility Librarian/RDMLA Coordinator

Developing an Inclusive Research Culture through Research Mentee and Mentor Training


Amy Koshoffer, Assistant Director of Research and Data Services, University of Cincinnati

Rebecca Olson, Informationist for Business & Social Sciences, University of Cincinnati

This presentation describes the development and application of two University of Cincinnati programs to promote inclusive research culture for both students and professors. After attending this panel presentation, attendees will learn how to partner with those involved with undergraduate education and how RDS professionals can encourage healthy mentor/mentee relationships to create similar programs at their own institution.

Historically approaches to building research mentoring relationships were ad hoc. These approaches had unintended negative consequences that disproportionately impact novice researchers in historically excluded groups. Over the past four years, members of theUniversity of Cincinnati Research and Data Services team collaborated with theUniversity of Cincinnati Director of Undergraduate Research to develop and facilitate programs aimed at creating an intentional inclusive research culture through standardized training and appropriate resources and tools. The first program, the Undergraduate Summer Research Learning Community is a ten-module program covering topics such as research culture, mentorship expectations, communication skills, conflict resolution, research ethics as well as data management and identifying valid evidence and designed to empower all students interested or involved in research. The facilitators pay special attention to how to improve the overall research readiness for students, particularly for students from historically excluded groups. One theme highlighted throughout the program is guidance for the mentee in navigating the power differential that exists in mentee mentor relationships. The second program, based on the University of Wisconsin CIMER training, targets the other side of the research mentoring relationship, the mentor. Research mentorship training highlights the mentor’s responsibility and obligation in developing the inclusive culture using three main principles, aligning expectations, creating an inclusive culture, and fostering independence. The two main program goals are to develop productive, mutually satisfying mentoring relationships for both the mentee and mentor and improve the overall research culture at the University of Cincinnati.

Building Capacity for Data Services among Health Sciences Information Professionals


Peace Ossom-Williamson, Associate Director, National Center for Data Services, Network of the National Library of Medicine

Data services has been a growing service component for health sciences libraries over the past decade. However, there is still a great deal of unrealized potential in this area as well as growing needs driven by new requirements from funders, publishers, and institutions. In particular, the new NIH requirements for data management and sharing that will take effect in January 2023 are likely to create significant pressure on health sciences libraries to support researchers in meeting these requirements. Efforts to build the capacity for providing data services within health sciences libraries have come from individuals, professional societies, and governmental institutions. In 2021, the NNLM National Center for Data Services was formed to coordinate these efforts was created. A central aim of this center is to coordinate with regional organizations to develop and disseminate trainings, curricular resources, and curated pathways for learning. Trainings and resources developed will be informed by current research in equity and inclusion and principles of accessibility. Instructors, mentors, examples, and activities will reflect diverse perspectives with emphasis on underrepresented voices and stories. In particular, offerings will be informed by the regional organizations who work directly with health information professionals and the public in regions that reflect needs distinct from common focuses. Through these partnerships, this organization will be in a position to serve a national audience. Considerations in data ethics would serve as a guiding principle for all resources so that, for example, training in data science skills would always be accompanied by communication around the existence, effects, and potential mitigation strategies of bias and inequities in data. Similarly, trainings on data management and sharing would include discussion of issues around sensitive and data ownership.

Data Professionals and Data Responsibilities in the Research Data and Computing Workforce


Christina Maimone, Research Data Services Lead, Northwestern University

Ashley Stauffer, Research Program Analyst, Penn State University

Additional authors:

Timothy Middelkoop (Internet2), Patrick Schmitz (Semper Cogito)

This presentation will share results from a 2021 IRB-approved survey of research data and computing professionals in the United States that includes data from 563 respondents in a variety of roles. The survey provides data on individuals' demographic characteristics, career background, current job responsibilities, views of the research data and computing profession, and sense of their own inclusion, recognition, and future in the field. It is essential data for understanding where our profession stands currently, determining what work needs to be done to build an inclusive future for the research data and computing domain, and setting measurable goals for the field.

In addition to discussing the overall results of the survey, we will share how the 5% of respondents who reported spending a majority of their time on data-related activities compare to other respondents. We will additionally share analysis of the additional 67% of respondents who spend a minority of their time on data-focused activities. The analysis will include an assessment of what parts of the community are likely missing from the survey results, and how the results compare to the other limited quantitative information available about the research data and computing profession. Finally, we will examine differences in compensation, position level, and position type across demographic groups with sufficient respondents for analysis.

Survey results can be used to inform initial understanding of the nascent field of research computing and data, including the variety of roles, responsibilities, and levels of compensation within the RCD profession. Results help establish a baseline understanding of gaps that exist for diverse representation within the profession and how we may be able to enhance efforts aimed at diversity, equity, and inclusion within the field.

2:30 pm - 3:00 pm: Break and time with sponsors

Use this time to take a break and/or visit our sponsors pages by selecting Sponsors from the main navigation menu.

3:00 pm - 4:00 pm

Lightning Talks Session 1


Ashley Thomas, Countway Library, Harvard Medical School, Digital Initiatives and Accessibility Librarian/RDMLA Coordinator

An Assessment of Sharing Practices in Repositories for Machine Learning Objects


Stephanie Labou, University of California San Diego , Data Science Librarian

Abby Pennington, UC San Diego, Research Metadata Librarian

Ho Jung Yoo, UC San Diego Library, Curation Analyst

There is a pressing need to establish best practices for data curation professionals in response to the increasing prevalence and application of machine learning (ML) across disciplines. Broad sharing of ML outputs - which are resource intensive to create, requiring large amounts of training and test data, processing power, and specialized programming knowledge - can make future research more efficient and reusable. However, formal community-accepted guidelines and recommended practices for documenting and sharing ML objects are sparse within library-centric professions and across data repositories. In this talk, we will discuss an ongoing project to better understand current practices for sharing and reuse of ML components (data, code, workflows, etc.). A core part of this project is an in-depth analysis of ML objects from a selection of repositories that specialize in ML research workflows and outputs, as well as several generalist repositories including Figshare and Zenodo. By analyzing the metadata of ML objects extracted via API and web scraping, we aim to address a variety of questions relevant to reusability, such as: What is the most commonly used license for ML components? How often are training datasets, necessary for measuring ML model performance, included with an ML object? Is clear documentation of the software environment used provided? Answers to these questions are merely the first step in better understanding the landscape of ML objects, in the context of reusability. In addition to assessing how ML objects are being shared, we will also leverage the FAIR Principles to identify and classify the minimum viable metadata that makes an ML object and/or project reusable for a standard practitioner. We look forward to feedback from and discussion with the RDAP community.

Certifying a Centrally-Managed, Multi-Institutional Data Repository: The CoreTrustSeal Journey with Scholars Portal Dataverse


Alicia Cappello, Queen's University, Research Data Management Librarian

CoreTrustSeal (CTS) Certification has become the "go to" certification for research data repositories worldwide. In 2020, Scholars Portal, the operations division of OCUL, knew that certifying their Dataverse repository was an important aspect of its continued growth and success across Canada. Scholars Portal officially launched their project to become CTS certified in January of 2021.

Scholars Portal Dataverse is slightly unique as the software and infrastructure are centrally managed, but each participating post-secondary institution is responsible for managing their individual collections, including the creation and implementation of institutional-specific policies and procedures. This setup has a considerable impact on the CTS certification application procedure, and what the various parties involved are responsible for.

As CTS certification is not yet set up to differentiate between specialist repositories, generalist repositories, and technical repository service providers, Scholars Portal needed to develop an application method that would allow participating institutions to apply for certification while also satisfying CTS requirements. The end result was the Scholars Portal Dataverse CTS Certification Cohort; a group of participating institutions interested in pursuing CTS certification collaboratively.

This presentation will provide an overview of the Scholars Portal Dataverse CTS Certification project, with a specific focus on the development and collaboration of the Cohort. This overview will also introduce the methods used by Scholars Portal to assess the gaps between needed and existing policies and procedures, as well as the methods used to determine the responsible party (i.e., Scholars Portal vs. Participating institutions) for each gap. The presentation will also introduce additional collaborations between Scholars Portal and both the Dataverse North Policy Working Group and the Digital Research Alliance of Canada.

Developing Diverse Data Librarians: Construction of a National Internship Program


Peace Ossom-Williamson, Network of the National Library of Medicine, Associate Director, National Center for Data Services

As data librarianship grows as a field, it is apparent that, much like the broader library community, opportunities are not evenly distributed, and people of racial and ethnic minority groups continue to be underrepresented. Therefore, equity and inclusion make up a central aim of [Center Name] created to develop librarians' and libraries' data services. The [Center] was formed in July 2021, and immediately began efforts toward this central aim. In this lightning talk, the presenter will describe the paid internship which provides data training, project experience, and professional networks for LIS students from historically excluded racial and ethnic groups. The approximately 10-week summer internship partners interns with libraries who have concrete, completable data projects. The students will be asked to present at an internal showcase at the end of the program, and encouraged to submit their work to a conference. The aim of the internship is to provide LIS students (and other students of color who may be interested in librarianship) with an introduction to data librarianship while building skills in project management and completion as well as presentation skills. Through this internship of mentored learning, interns will be embedded into the tasks and complexities of data librarianship, while being provided ongoing guidance for success. Ultimately, they will take away awareness and recognition of whether they are interested in data librarianship, and they will have practical experience for seeking employment in the field, as well as connections to librarians working in the field.

The presenter will describe how the internship was developed and how the [Center] used best practices, resources, and participation in the [University] Leading the Charge program to initially construct an internship program and steps that have and haven't worked well at initial stages of development. The presenter will describe their ongoing participation in the Leading the Charge program and plans for assessment. They also plan to provide updates annually on adaptations, changes, and improvements made to the internship.

From Communities, For Communities: Cataloging Community-Based Participatory Research Data


Sara Mannheimer, Montana State University, Data Librarian

Community-based participatory research strategies are used at Montana State University (MSU) to co-create research data with Native American and rural communities in the American West. To increase benefit and minimize harm to participating communities, the MSU Library has partnered with the NIH-funded Center for American Indian and Rural Health Equity (CAIRHE) to create metadata records for restricted data, thus making the data available to community members while maintaining the confidentiality and sovereignty of the data. This project can serve as a model for other libraries wishing to build similar partnerships.

The Library's partnership with CAIRHE addresses four challenges:

1. Sensitive data. The data relate to sensitive topics in community health and they are co-created with small communities, which makes deidentification difficult.

2. Data sovereignty. In accordance with Indigenous data sovereignty principles, data belong to Indigenous communities where research is conducted. This means that publishing data in a repository with restricted access may not an appropriate solution - doing so may put the data into the hands of institutions with whom the communities do not have relationships.

3. Trusted data storage. It is common that small, rural communities in Montana don't have the resources to store and preserve data locally. CAIRHE is trusted by its partner communities, so storing data using MSU infrastructure is the best solution in this particular case. However, appropriate members of communities must be able to access the data.

4. In-progress data. In-progress data need to be available to communities to support time-sensitive community efforts such as grant proposals and public health initiatives.

This lightning talk provides an overview of the process of collaborating with CAIRHE and customizing MSU's data catalog, including outreach, communication, curation strategies, and lessons learned. Collaborations like the one at MSU can help members of communities who co-create research to find, request, and access appropriate data.

Moving Beyond a Transparency Model: Creating Data Visualizations that Empower Communities Speaker:

Subhanya Sivajothy, McMaster University, Data Analysis and Visualization Librarian

Among data justice organizations and policy reports, transparency is often one of the first calls that is used to demand accountability from governance structures as well as corporations. This often extends into the creation of visualizations, as many assume that transparency will create much needed awareness; however, these visualizations can often be highly disempowering to those whom it seeks to represent. This method of approaching data visualization removes agency from both the designer as well as the end users because it assumes that the data itself can tell something about the world.

Alternatively, feminist methodological arguments have critiqued this assumption of intrinsic objectivity. Through feminist methodologies and experiences working with communities, this talk will discuss some tips on creating data visualizations that can mobilize data to push back against unequal power structures and empower communities through data science. I will briefly present on alternative data visualization paradigms such as: creating human scale visualizations, employing counter-data, mutual visibility and examples of participatory methods in data visualizations.

Open Data vs. Equitable Risk in Human Subjects Research


Monica Ihli, University of Tennessee Libraries, Assistant Professor

Open data has become widely accepted as critical to the advancement of knowledge. Initiatives such as specialized data archives have demonstrated success in reconciling open data efforts with the need for protection of human subjects research data. For example, best practices for publishing data about people generally provide guidance on treatment of indirect identifiers such as geographic characteristics or birth year cohort. However, a more concrete understanding of the statistical relationship between distribution of sample attributes and risks to participant confidentiality is useful for defining ethical data collection and data management practices. More specifically, race and gender are often not uniformly represented in study samples. While the issue is frequently discussed in the context of generalizability of findings across a population, this presentation uses a simple application of probability theory to highlight the inequitable levels of confidentiality risk which could assumed by participants in whose racial, gender, or sexual identity places them in the minority.

Piloting a Digitization Workflow for Analog Agricultural Data


Ali Krzton, Auburn University, Research Data Management Librarian

In the summer of 2021, the head of the Department of Entomology and Plant Pathology contacted the Research Data Management Librarian seeking advice on what to do with the paper records, including original data, of two professors emeriti. In cooperation with the Agriculture Librarian, the Special Collections Librarian, and the Library Archivist, the collection was assessed and the files physically transported to the library. The data can be safely preserved in their original form within Special Collections. However, the department head and librarians all agreed that digitization, which would make the data more accessible and permit machine-readability, is the ideal solution. The Agriculture Librarian and the Research Data Management Librarian will select a subset of the paper records to scope out the time, effort, and level of expertise needed to digitize the data, translate it into machine-readable formats, and add appropriate metadata. Important questions about the process include determining the amount and type of training needed for different stages of the workflow, whether there are any steps where efficiency could be improved through automated processes, and how it can be scaled up to allow for processing the entire collection. The department head requested that we share recommendations for best practices and procedures with him as he works to develop a data archiving policy for the department. Recognizing that more faculty will retire and leave cabinets full of paper data, the librarians are eager to experiment with methods that could make this data FAIR before the problem becomes unmanageable and irreplaceable work is lost.

Revising and Rethinking Asynchronous Data Literacy Modules: Addition of Practical Data Visualization Skills for Students of all Abilities


Kristen Adams, Miami University Libraries, Science & Engineering Librarian

Previously a group of librarians created a set of data literacy modules. These were designed to be online asynchronous, taken either in unison or separately, mostly for STEM disciplines with hopes of being useful outside these areas too. This flexibility was intentional from initial planning, so they could be plug-and-play for faculty to incorporate into their courses or helpful to students looking for a self-paced workshop. There was interest in incorporating the modules into a graduate program consisting of predominantly non-traditional students. However they desired some practical skills, particularly in the data analysis and visualization modules, to complement the mostly theoretical concepts already presented. After some rethinking, a set of over 15 videos were created explaining the graph type and anatomy, then showing how to make the visualization, using data that was not STEM based, mostly in GoogleSheets and Microsoft Excel. The videos were incorporated into the module, making them more inclusive for learners at all levels; they are also freely available on the Libraries' YouTube channel so they are not locked away within the module. In sharing these with other librarians, they've been linked to from STEM and non-STEM LibGuides - furthering their reach. The videos have gotten decent use, despite not yet being fully incorporated into the program that requested them. Moving forward, future data literacy materials the librarians create will be more mindful of students of all abilities and not miss out opportunities to help learners from wherever they are starting from. The format of future learning materials may also be reconsidered - incorporating a mix of larger modules and videos on specific skills.

4:10 pm - 5:00 pm: Social: New members event

Katie Barrick, Science Librarian and Data Curator, University of Minnesota

The RDAP New Members Event is an opportunity to learn more about the organization, current leadership, and connect with other new members. Please join us for some fun and a chance to win prizes!

Wednesday, March 16

11:00 am - 11:50 am: Social: Kickstart day 2 of the Summit with other Summit attendees


Jennifer Darragh(Moderator)Duke University, Senior Research Data Management Consultant

Megan O'Donnell (she/her)(Moderator)University Library

Wei Zakharov(Moderator)Purdue University, Assistant Professor of Libraries and School of Information Studies

Topics and activities:

Discussion: Pets of Zoom

Discussion: Pandemic Cooking Adventures

Virtual Walk (chat while on the move and/or share what you saw most recently on a walk through your neighborhood. What's blooming? Any interesting critters that have crossed your path?)

Discussion: Mentoring undergraduate research (Attendees who are mentoring or interested in mentoring undergraduate research are welcome to join.)

Have a suggestion for a discussion topic or activity you would like to lead during this social? Let us know by contacting one of the organizers in Whova or emailing

12:00 pm - 1:00 pm: Lightning Talks Session 2


Reid Otsuji, UC San Diego

DataPro - A Tool for Characterizing and Communicating Research Data Risks and Responses


Dessi Kirilova, Senior Curation Specialist, Qualitative Data Repository

Additional authors:

Diana Kapiszewski (Georgetown University; Qualitative Data Repository) and Colin Elman (Syracuse University; Qualitative Data Repository)

Social scientists conducting human participant research must meet two potentially conflicting ethical obligations: protecting participants and being transparent about their research. In this presentation we will discuss our plans for an interactive online tool to help scholars meet both of these expectations. The project will still be in its initial stages at the time of the presentation.

The "Data Profile" tool (DataPro) will synthesize (a) current approaches to describing data sensitivity and identifying the risk of sharing sensitive data, and (b) existing repository-based strategies for mitigating risk. The tool will serve scholars in two ways:

1. Providing guidance - DataPro will help researchers to accurately characterize the sensitivity of their research data; identify the nature and degree of risk to human participants if the data are shared; and understand and select strategies for mitigating any such risk;

2. Creating documentation - DataPro will help researchers to communicate their assessment of data sensitivity, risk, and planned measures to mitigate risk to relevant institutional stakeholders (funders, ethics committees, journals) during the research lifecycle.

In the presentation, we will introduce the starting outlines of a practice-oriented framework structuring and identifying synergies among a range of strategies and tools that facilitate the ethical sharing of sensitive human participants data. In addition, we hope to be able to report the preliminary results of an online survey of researchers in five disciplines from about 35 research-intensive institutions in the US, fielded to gather input to inform the proposed tool's functional specifications. In brief, respondents are being asked when, why, and how a tool of this sort might facilitate the ethical sharing of human participant data.

The project and proposed presentation fit several of the themes of the 2022 RDAP summit. We will illustrate a new project and a new service tool for research data, and discuss how the DataPro tool can contribute to reshaping research practices at institutions of higher education.

Encouraging Adoption of FAIR Principles via Institutional Research Data Policies


Clara Llebot, Data Management Specialist, Oregon State University Library

Diana J. Castillo, Business/Social Science Data Librarian, Oregon State University Library

The FAIR principles were created with the goal of enhancing the reusability of research data, and to give guidance to data creators, curators and publishers on how to make data Findable, Accessible, Interoperable and Reusable. In addition to being good for science, implementing FAIR, along with other principles such as CARE, can lead to making data access more equitable and ethical. In order to implement these aspirational principles, incorporating FAIR into research data policies at all levels (funder, publisher, and institutional), is vital. In this talk we will explore the role of institutional research data policies in enabling and encouraging researchers at their institutions to generate FAIR data. We identified the research data policies in place for “very high research activity” institutions (as defined by Carnegie classification) in the United States. We created a list of 31 criteria, based on the FAIRsFAIR project criteria for policies and on the previous work of Briney et al (2015) and evaluated the 42 policies. We will discuss how different policies have elements that support the FAIR principles; for example, we will examine the existing models regarding data sharing, and how data sharing is allowed, encouraged or required in these policies. Other criteria that we analyzed include the research infrastructures and repositories mentioned in the policies, references to data protection and to data management plans, and support for compliance. We will present specific examples that will inform participants about the options that other universities have chosen for their policies. These examples will provide a framework for those working with their institutions to create or update an institutional research data management policy. At this time, institutional policies are not being used as a tool to facilitate the adoption of FAIR. This presentation will show some first steps that can be taken in that direction.

Enhancing Research Data Services for Undergraduate Students through a Data Fellowship Program


Nick Ruhs, Florida State University, STEM Data & Research Librarian

With the increase in data being produced and made available to researchers and the general public, there is a growing need to build awareness about how to evaluate and work with data in the context of an evolving and more diverse workplace. As a part of this shift, employers often expect new graduates to have skills in data literacy and data analytics. However, classroom instruction often focuses on specific tools and methods rather than on general data literacy skills, such as how to critically evaluate and interpret data. While the latter set of skills can be gained through involvement in research projects, many students (particularly undergraduate students) do not conduct research during their academic career. This presents a unique opportunity for academic libraries to fill in the gap via data literacy instruction and data services for undergraduate students. This presentation will describe the creation of a data fellowship program for STEM undergraduate students at Florida State University (FSU). The program provides undergraduate "data fellows" at FSU with the opportunity to teach, collaborate, and engage in open conversations with their peers and library colleagues on projects related to data literacy, data science, data ethics, and open data. These opportunities position the fellows to serve as advocates for critical data literacy on campus and provide them with skills that position them for post-graduation success. Current projects and initiatives will be discussed, along with insights and perspectives from the initial phases of the program. The presentation will conclude with a brief overview of future plans and goals.

InvenioRDM: An Open Source Development Community Experience


Sara Gonzales, Data Librarian, Northwestern University

Additional authors:

InvenioRDM distributed development team and Lars Holm Nielsen (InvenioRDM Product Manager, CERN)

Research Data Management (RDM) platforms play a critical infrastructure role in today's open science ecosystem, empowering discovery and access, while supporting interoperability and more equitable scholarly practices. InvenioRDM is a turnkey, born-interoperable RDM repository and data index to empower FAIR data, discovery, credit, and reuse of a wide range of digital artifacts and data - enabling best practice workflows and opportunities to understand the activities and people needed to drive knowledge forward. InvenioRDM is built upon a strong multi-national collaboration, which includes the European Organization for Nuclear Research (CERN) with extensive experience gained through Zenodo, Northwestern University, and >20 other partners representing academic, research, funding, and industry collaborators from Europe, Asia, Africa, and North America. This highly collaborative software development effort is complemented by investments in the InvenioRDM community, including outreach activities, working groups, and opportunities for democratic contributions to all discussions of features, modules, and customizations. To facilitate this collaborative approach, the InvenioRDM team features a community manager role to lead meetings and gather feedback on questions related to metadata and user experience. Launching this role led to community-based project meetings that have been as vigorous and productive as those devoted to coding. Through community meetings, the team has agreed on things like controlled vocabularies to populate the subjects field, adoption of the COAR Open Access vocabulary, and helpful groupings of licenses based on resource type. In the community meetings we have also encouraged and benefitted from partner presentations, and from a coordinated effort on usability testing. In this presentation, we will outline the InvenioRDM project and progress, the launch of the community-based initiative within the InvenioRDM project, "on-ramps" for collaborators, documentation and implementation resources for local adoption teams, and efforts to sustainably support a collaborative and dynamic software and community.

Librarians Participating in Faculty Research Grants: Considerations for Time, Compensation and Scope of Work


Jennifer Chaput, STEM Librarian, University of Connecticut Library

Renee Walsh, STEM and Data Management Librarian, University of Connecticut

The two research data librarians at an R1 university were asked to participate in the application process for an NIEHS Superfund grant as co-PIs on the Data Management and Analysis Core (DMAC). At this institution, librarians do not have faculty status and are members of a different professional union that has boundaries for weekly hours and additional compensation. These librarians also have a split role as subject specialists and research data services and are not full-time data librarians. The library does not have a history of librarians participating in grants in this capacity, and the application process raised many questions about how this process is administered for university staff versus faculty. Assumptions about the librarians' availability and compensation were made by grant PIs (Principal Investigator), and a realistic picture of what the library could offer was presented in response. The librarians were also asked to assist in writing a grant proposal for services not currently in place and that might include services in areas where we they do not have either experience or skills, or are outside of their job description and scope. This lightning talk will discuss how the librarians handled conversations on time and compensation, how they wrote their portion of the grant for inclusion of current services along with potential services that do not yet exist, and how they used their current knowledge and skills to provide a solid foundation on funder mandates, campus resources, and data management practices in the grant application. This grant has not been awarded yet, and may not be before the 2022 RDAP Summit, so this talk will only discuss the application process.

Reconstructing Data Services: A Matrix Team Approach


Florio Arguillas, Research Associate, Cornell University

Claudia von Vacano, Executive Director, Cornell

Yolanda Xue, Senior Data Science Fellow, Cornell Center for Social Sciences

In response to new directions at our university, our local data center faced a complex reorganization, consolidation of services, and the incorporation of new leadership. Our new director advocated for a new approach within our organization that included the incorporation of graduate students as data sciences fellows. The graduate student fellows are primarily Ph.D. students from a variety of disciplines across the university and were hired in the summer of 2021. In the fall semester, we hired five senior data science fellows who are on full fellowships and eight data science fellows who work five hours per week.

As our original staff team of data support experts is small and over-committed, these new fellows have added capacity for our consulting support. In addition, they have helped to refresh our services and workshop offerings. While many other data service units have hired graduate students, our team has taken a more inclusive approach by using matrix teams to rebuild our service areas. Using this approach, all service teams (data services, consulting, workshops, and compute resources) are open to all members of the team. Our five senior data science fellows serve as conduits between core staff and the larger data science fellow group and our future undergraduate cohort. Through this new model, we hope to draw on our graduate students' knowledge of data science while providing them opportunities for professional-level experience in planning and leadership.

This presentation will discuss the implementation of the program, our approach to matrix teams, the new service offerings, and how the transition is going. While this approach may seem particular to our institution, we will talk about the transferability of this approach in other contexts. The presenters will include a core staff member and a senior data science fellow.

TDM Licensing: What to Know


Mary Ellen Sloane, User Services Librarian for Basic and Applied Sciences, Professor, Middle Tennessee State University

As libraries approach and embrace providing text and data mining services to users, collection managers seek to understand licensing terms and restrictions. This lightning talk will provide a timely overview of current terminology and practices in licensing text and data mining products and services from vendors.

There's no "I" in RDM: Reshaping RDM Services Toward a Collaborative Multi-Stakeholder Model


Alisa Rod, Research Data Management Specialist, McGill University

Biru Zhou, Senior Advisor Research Data Management, McGill University

Additional author:
Marc-Étienne Rousseau

New digital technologies have profoundly transformed academic research across all disciplines, necessitating the evolution of corresponding research data-related services. This presentation will discuss and reflect on a reshaped service model for research data management (RDM) at a Canadian university founded on collaboration between multiple stakeholders. This initiative, along with a newly formed team dedicated to RDM service provision, is a joint effort by the institution's Vice-Principal Research, Library, IT Services, and Research Ethics units.

The McGill Digital Research Services (DRS) team assists researchers in navigating the increasingly complex digital research ecosystem by providing advice and support on activities related to RDM, research software, and advanced research computing. The presenter will discuss new collaborative services such as "query the panel" sessions where researchers across all disciplines are welcome to bring their questions about data sharing, data security, software vetting, or data management topics. This presentation will also highlight the use of Jira's service desk software as a backend user management system to triage researcher questions so that they reach the appropriate campus unit and are addressed in a timely manner.

1:00 pm - 1:15 pm: Break

1:15 pm - 2:15 pm: Presentations Session 2 (Track A)


Chao Cai, Purdue University, Assistant Professor

Building a Data Lifecycle Management Toolkit to Support Diversity Scholarship


Rachel Woodbrook, Data Curation Librarian, University of Michigan

There are increasing demands on researchers to continue refining their data practices, including requirements for data sharing coming from federal and other funders. However, support to appropriately manage and assess data (e.g., for sharing) is nonstandard and inconsistent, often relying on the resources of specific institutions, mentors, or individual experience. This is likely to have a disproportionate impact on scholars doing work with data on sensitive populations or that otherwise require extra care, as well as those scholars from underrepresented backgrounds, without well-resourced institutional affiliations, or who otherwise face structural barriers in their work.

Acknowledging that resolving these issues requires larger shifts in the research infrastructure, this presentation will discuss the content and creation of an openly-available toolkit of data lifecycle management resources to support diversity scholarship (scholarship that advances understanding of identity, difference, culture, representation, power, oppression, and inequality). While things have started shifting in recent years, there are still not enough easily accessible resources that explicitly integrate DEIA (and similar) concerns into the full spectrum of data management.

The toolkit creation process included original research conducted in collaboration with a campus organization for diversity scholars to identify needs and gaps in support, as well as an environmental scan of existing resources which were evaluated and selected based on set criteria. The end result is a curated set of resources relevant to diversity, equity, inclusion, and accessibility considerations for data management in multiple disciplines. The presentation will also briefly discuss the role of this partnership in conducting the research and in plans for sharing the toolkit with researchers, as well as plans for sustainability and engaging scholars in revision of the toolkit moving forward.

Bring Your Own Data (BYOD) Working Groups: A New Service to Multiply Staff Impact and Create Community


Colby Witherup Wood, Senior Data Scientist, Northwestern University

Additional author:

Christina Maimone, Northwestern University

Research data professionals have limited time to assist researchers one-on-one, and remote work has reduced or eliminated casual interactions with researchers at workshops or other events. Remote work has also impacted researchers, reducing opportunities to get advice from both research data professionals and peers, as well as interfering with the structure and accountability needed to make progress on their data projects.

Beginning Spring 2020, we introduced a new remote service offering: Bring Your Own Data (BYOD) Working Groups. Working Groups are small (3-6 researchers) multi-level (student, postdoc, faculty, research staff) interdisciplinary groups built around a loose data topic (Python, R, data visualization). Led by one staff member, groups meet once a week for 8 weeks, with each meeting lasting 30 to 60 minutes. At meetings, participants share their weekly progress, state the work they intend to complete in the upcoming week, and get feedback from both the staff member and their peers on any data hurdles they are facing.

By creating a community of multi-level data users, BYOD Working Groups leverage community knowledge to broaden the spectrum of methods that researchers can get help with. They address the whole researcher by making room for discussions about productivity and accountability, and they greatly reduce the amount of time researchers spend spinning their wheels when faced with data or coding challenges. BYOD Working Groups also benefit the larger community as they increase data literacy, increase data communication literacy, encourage interdisciplinary knowledge exchange, and contribute to more equitable within-discipline knowledge inheritance.

In our presentation, we will detail the observed benefits and measured outcomes of BYOD Working Groups at our university. We will provide administrative tips for organizing, running, and monitoring the groups, and we will discuss why you might want to create a similar service at your own institution.

Empowering Student Activists through Data Literacy


Ariel Hahn, Data Management Librarian, Cal Poly Pomona

Alyssa Loera, Digital Services & Technology Librarian, Cal Poly Pomona

In this presentation, we will discuss the creation of a new data literacy program at our public institution. Currently, we are in the early stages of envisioning a series of data workshops intended to support students needing data-centric information for their social justice campaigns. We plan to explore what data is and how to use it, the basics of power-mapping and publicly accessible databases, and the value of FOIA. This workshop series will be informed by and marketed in collaboration with other partners on our campus - including faculty, student cultural centers, and select academic centers. Our presentation will offer a look into the planning and collaboration process as well as the core components of each lesson. If successful, we plan to reproduce this series and potentially build out a guide or toolkit so it can be replicated by other libraries. We see the 2022 summit as an opportunity to share this project while it is still in its infancy and, hopefully, gain further insight by engaging with the RDAP community on the topic.

1:15 pm - 2:15 pm: Presentations Session 3 (Track B)


Ashley Thomas, Digital Initiatives and Accessibility Librarian/RDMLA Coordinator, Countway Library, Harvard Medical School

Expanding the Table: The Role of Library Data Professionals in Data Governance


Abigail Goben, Associate Professor and Data Management Librarian, University of Illinois Chicago

Kristin Briney, Biology & Biological Engineering Librarian, California Institute of Technology

Heather Coates, Digital Scholarship & Data Management Librarian, IUPUI University Library

As research data management and sharing has become ubiquitous, the need for data governance - coordinated decision-making around research data across all levels of an institution - has come to the forefront. Data governance is needed to address immediate and changing issues such as emerging funder policies as well as the ongoing challenge of researchers leaving an institution.

Data governance often falls under the purview of information technology units. However, this technocentric approach may conflict with the values and real world aims of university research, resulting in policies and practices that create additional barriers. Due to the traditionally hierarchical nature of research institutions, there is a need for broader engagement and representation in governance structures. Currently, data governance typically reflects the priorities and perspectives of those who are white, able-bodied, and male. While this is evolving, there is a specific need to identify and include the communities who have been previously excluded from decision-making and to ensure their participation in order to anticipate potential governance problems across a range of scenarios.

Due to their familiarity with working across disciplines and throughout their organizations and expertise in areas like data sharing and preservation, library data professionals should be key partners in data governance processes. At our institutions, each of us has observed common challenges and witnessed the need for more participatory data governance practices. Seeing these issues, as librarians working with data, we've raised our voices and used our established credibility to bring together the disparate groups and to ensure library expertise is utilized when policy and practice decisions are being made.

This presentation will explore current challenges in research data governance stemming from the dominant technocentric approach. We seek to extend the conversation and to identify opportunities for our community to advance more transparent and collaborative data governance practices.

The Impact of "Academic Capitalism" on “Belongingness”: Institutional Data’s Impact on Diversity, Equity and Inclusion


Nastasha Johnson, Associate Professor of Library Science, Purdue University Libraries and School of Information Studies

Megan Sapp Nelson, Associate Head/Professor, Purdue University Libraries and School of Information Studies

Additional author:

Katherine Yngve

The theory of academic capitalism impacts the data regarding students that is selected for inclusion in data sets that are used to predict academic success. Given the data that is collected at the individual level at most higher education institutions, we propose that the current data sets collected are inappropriate for evaluating “belongingness”, a key metric that many institutions are trying to assess. The failure to collect the correct data is directly tied to academic capitalism’s focus on students as both a market and a product. This presentation provides an introduction to academic capitalism, to institutional data as an asset of the organization, and problematizes the use of deficit-focused data to predict asset-focused characteristics such as belongingness as an outcome.

Making Libraries for Everyone: Building a Reproducible Workflow to Assess Classification


Lindsay Gypin, Data Services Librarian, University of North Carolina Greensboro

Inarguably, libraries function as systems of oppression. From a lack of diverse or representative collections, to inequitable hiring practices in a predominately white profession, libraries are not for everyone. Underneath these surface level issues, library classification systems in use today are built upon outdated eurocentric patriarchal heteronormative ideals. While the foundation of librarianship centers on this harmful ideology, issues of exclusion will perpetually pop up. How can librarians reorganize catalog metadata to build more inclusive libraries? This was the driving question that led me to apply to the Frictionless Data for Reproducible Research Fellows Program in 2021. This fellowship trains early career research professionals to become champions of reproducible research by using open source Frictionless code and tooling. During the fellowship, I have learned about reproducible research, including data publishing best practices, how to include machine readable metadata, and how to validate data. This new knowledge has been instrumental in my goal to create an accessible workflow to analyze library classification metadata to uncover instances of systemic oppression. As an early career research librarian at a minority serving institution, I see first-hand the effects of having an antiquated eurocentric classification system. Critical cataloging has been well-researched in the field of librarianship, but library catalog metadata hasn't been analyzed with a textual analysis lens. Using the skills I have developed in this fellowship, I am creating a reproducible data workflow to explore the library catalog as a system of oppression, with a goal that librarians at other institutions can reuse this data workflow. This presentation will share the lessons I've learned during the Frictionless Data for Reproducible Research Fellowship, and how research librarians can harness open data to affect positive societal change.


2:15 pm - 2:55 pm: Poster Session 1

10 Curation for Reproducible and FAIR Things

by Limor Peer, Florio Arguillas, Thu-Mai Christian, Tom Honeyman, and Mandy Gooch

Assessing the Big Picture: Coordinating the completion of the CARCC Research Computing and Data Capabilities Model

by Lora Lennertz

Analysis of U.S. Federal Funding Agency Data Sharing Policies: Highlights and Key Observations

by Patricia Condon, Reid Boehm, Hannah Calkins, Jonathan Petters, and Rachel Woodbrook

Building a shared open research data repository community in Canada

by Meghan Goodchild and John Huck

Data Everywhere: Aerospace, Industrial Engineering and Mechanical Science Faculty Experiences

by Chris Wiley

Extracting the data from graphs – a review

by Monica Carroll

Factors Affecting Deposits in Data Repositories

by Michele Hayslett and Matt Jansen

A Guide to Responsible and Inclusive Data Ethics

by Nancy Shin and Lynly Beard

Leveraging Research Networks to Inform Education on Data Sharing Practices

by Daria Orlowska and Hannah Gunderman

The Open Science of Deep Learning: Three Case Studies

by Chreston Miller, Jacob Lahne, and Leah Hamilton

Show me the data! Implications of data sharing practices demonstrated in published research at a medical university

by Kimberly MacKenzie and Tess Grynoch

Visualizing Usage and Publication Data to Inform Impactful Collection Decisions

by Pei-Ying Chen and Sarah Siddiqui

2:15 pm - 2:55 pm: Break and time with sponsors

Use this time to take a break and/or visit our sponsors pages by selecting Sponsors from the main navigation menu.

3:00 pm - 4:00 pm: Presentations Session 4


Amy Yarnell, Data Services Librarian, Health Sciences and Human Services Library, University of Maryland Baltimore

Actually Accessible Data: A Call To Action


Sebastian Karcher, Associate Director, Qualitative Data Repository

Abigail Goben, Associate Professor and Data Management Librarian, University of Illinois Chicago

Randy Colón, PhD Student in Disability Studies, University of Illinois at Chicago (UIC)

In a 2015 article, Wendy Walker and Teressa Keenan highlighted the importance of providing "truly accessible research data": research data that are not merely available, but accessible to all users, including those with disabilities. In the 6 years since, the conversation about accessible research data that Walker and Keenan hoped to start has, mostly, not occurred. As funder, journal, and disciplinary norms and mandates have foregrounded obligations of data sharing and opportunities for data reuse, the need to plan for and curate data sets which can reach researchers and end-users with disabilities has become even more urgent. As academic institutions and repositories face exponentially growing data curation and preservation needs, it is critical that we identify opportunities to improve data to facilitate use by all interested parties, rather than further reinforcing ableist practices.

This presentation is both a call for, and a description of, first steps towards, "Curating for Accessibility." We begin with a survey of the landscape of curation guidelines and standards that finds very little consideration of accessibility for people with disabilities. We briefly explore the disability studies literature and the need for advocacy and representation of disabled scholars as data creators, subjects, and users. We then suggest three sets of minimal good practices for truly accessible research data: 1) Ensuring web-accessibility for data repositories, 2) ensuring accessibility of common text format, including those used in documentation, and 3) enhancement of visual and audiovisual materials. We point to some signs of progress towards truly accessible data by highlighting exemplary practices by repositories, standards, and data professionals.

The presentation ends with a call to action: Accessibility -- in the sense of making data usable by all reusers -- needs to become a mainstreamed component of curation practice, included in every training, manual, and primer.

Applying a Critical Lens across the Research Data Life Cycle to Foster Greater Data Inclusivity: An LGBTQ+ Case Study


Berenica Vejvoda, Research Data Librarian, University of Windsor

This proposal begins with the premise that data inclusivity plays a critical role in eliminating invisibility of, and discrimination against, marginalized groups. A second guiding assumption is that inclusivity affects all stages of the research data life cycle—from the planning phase to data dissemination and re-use. Thirdly, this presentation will establish that research data management is not a neutral process and, rather, is situated in a wider social, political and cultural context. Using the LGBTQ+ population as a case study, a critical lens will be applied across the research data life cycle to discuss how research data management strategies can become more inclusive and representative of the LGBTQ+ community. In critiquing each stage of the research data lifecycle the proposal will address key inclusion strategies as they relate to, for example: data capture of critical LGBTQ+ issues and knowledge gaps; inclusive methodologies, instruments and study design; involvement of LGBTQ+ people in data collection processes and outcomes; the adoption of appropriate metadata standards; inclusive dissemination; and ensuring research outputs are readily available to key stakeholders who affect change through policy and further research. Finally, this presentation will discuss how data professionals might use a critical lens to advise researchers on more inclusive data management practices for data relating to marginalized groups. That approaching research data management with a critical lens is challenging will be recognized. However, it is hoped that this case study will illustrate that researchers can ask critical questions across all stages of the research data life cycle when they are motivated by the intent to change social realities and to address social inequities from the outset of their research projects.

From "Best" Practices to Inclusive Practices: Critical Approaches to Data Structures


Negeen Aghassibake, Data Visualization Librarian, University of Washington

Data can elevate, empower, and uplift, but it can also erase, disempower, and harm when used in ways that are not inclusive and thoughtful. However, before having conversations about how we use data, it is important to consider the way our data is even structured: Who set up those structures? What were their biases?

Data is fundamentally about and constructed by people, even though it may be abstracted on many levels from those who contributed their information (whether voluntarily or involuntarily) and those who shaped it. Oppression often centers itself in and shapes our data and data structures, perpetuating further marginalization and erasure of minoritized groups.

As an example, Abigail Echo-Hawk states that "[o]ne of the ways that there is a continuing genocide against American Indians/Alaska Natives is through data. When we are invisible in the data, we no longer exist" (1). A related example is the flattening of identities based on single-select or binary structures for capturing demographic information. What are the consequences of our decisions on how we structure data and how we combine different groups of users to provide anonymity or significance? Who do we exclude when we make decisions based on the largest number of people or dominant groups? What are the impacts?

This presentation would build on critical approaches to data that are already being discussed in libraries and related fields in order to ask questions about how data is (or is not) being critically examined in these spaces. It would ask those who work with data to implement critical perspectives to interrogate not just how we use data, but how we structure it in the first place.

1. Secaira, M. (2019), "Abigail Echo-Hawk on the art and science of "decolonizing data," Crosscut, available at:

4:10 pm - 5:00 pm: Social: Games night

Jennifer Darragh, Senior Research Data Management Consultant, Duke University

Megan O'Donnell (she/her), University Library

Tess Grynoch, Research Data & Scholarly Communications Librarian, University of Massachusetts Chan Medical School

Thursday, March 17

11:00 am - 12:00 pm: Social: Kickstart day 3 of the RDAP Summit with other Summit attendees

Megan O'Donnell (she/her), University Library

Jennifer Darragh, Senior Research Data Management Consultant, Duke University

Have a suggestion for a discussion topic or activity you would like to lead during this social? Let us know by contacting one of the organizers in Whova or emailing

Games room

Pandemic hobbies

12:00 pm - 12:40 pm: Poster Session 2

What best practices exist to support database and digital collection migration?

by Joseph Rockne Starks, Michael Lenard, and Andrea K. Thomer

Copy/Paste vs. Customization: A Qualitative Analysis of NIH Grantees’ Data Management Plans to Shape Future DMP Support

by Levi Dolan, Elizabeth C. Whipple, and Heather Coates

Getting Everyone Onboard! (and Offboarded): Coordinating Data Services in the Lab

by Sarah Hauserman and Julie Goldman

Identifying and evaluating access-limited data sources in Canada: Recommendations for improving data discovery

by Kevin B. Read, Jeremy Geelen, Grant Gibson, Amber Leahey, Lynn Peterson, Sarah Rutley, Julie Shi, Victoria Smith, and Kelly Stathis

Mix and Match: Building Flexible Data Visualization Modules

by Tess Grynoch, Negeen Aghassibake, Alisa Rod, and Angela Zoss

Practices of Big Data and Data Science Researchers at the University of Virginia: An Ithaka S+R Local Report

by Jennifer Huck and Jackie Huband

Relating Data Reuse to Curation Decisions and Funding Models

by Sara Lafia, Libby Hemphill, Amy Pienta, Dharma Akmon, and Andrea Thomer

Research Reproducibility in Health Sciences Libraries

by Mark MacEachern and Sara Samuel

State of Open Data 2021: Focus on Motivations for Sharing and Credibility of Open Data

by Andrew Mckenna-Foster

Undergraduate science coursework as embedded data librarianship

by Dominic Bordelon

A Usability Study of a Self-Deposit Data Repository Service

by Zhihong Xu, John Watts, Laura Sare, and Sarah Bankston

What’s Your Function? Collaborating with the Commercialization Office to Track and Market a Research Dataset

by Lynnee Argabright and Sam Zelick

Have a suggestion for a discussion topic or activity you would like to lead during this social? Let us know by contacting one of the organizers in Whova or emailing

12:00 pm - 12:40 pm: Break and time with sponsors

Use this time to take a break and/or visit our sponsors pages by selecting Sponsors from the main navigation menu.

12:45 pm - 1:45 pm: Panel: Data Support Services Needs in the DIY Era


Dylan Ruediger, Senior Analyst, Ithaka S+R


Neelam Bharti, Senior Librarian, Carnegie Mellon University

Susan Ivey, Director, Research Facilitation Service, North Carolina State University

R. Benjamin Gorham, Case Western Reserve University

This panel will highlight findings from a recent national study of research practices of researchers working with big data. Our findings suggest that many researchers prefer to learn new skills and tools using internet resources and tutorials rather than the more structured, often in-person, workshops and trainings offered by university libraries. The reasons for these preferences vary: some researchers expressed concerns that library workshops were not advanced enough to meet their needs, while others valued the convenience of internet searches and external, web-based resources, which are seen as offering immediate answers to specific questions that arise during the research process. In an era when high-quality online materials and communities to support self-learning are readily available, what research support services can libraries offer to complement these offerings and respond to unmet needs? This roundtable brings together librarians from four research-intensive universities to discuss the emerging support needs of data-intensive researchers and consider how university libraries and other university units can most effectively meet them.

1:45 pm - 2:00 pm: Break

2:00 pm - 2:50 pm: RDAP Journal Club

Led by the RDAP Education & Resources Committee, join us for a special Summit edition of the RDAP Journal Club! All attendees are invited to read the selected article for this journal club, as chosen by popular vote:

Led by the RDAP Education & Resources Committee, join us for a special Summit edition of the RDAP Journal Club! All attendees are invited to read the selected article for this journal club, as chosen by popular vote:

Exner N, Carrillo E, Leif SA. Data Consultations, Racism, and Critiquing Colonialism in Demographic Datasheets. Journal of eScience Librarianship 2021;10(4): e1213.

You're still welcome to bring your own reading to discuss as well and you will have the option to propose it as the group reading for a future month. We ask only that you can relate it to data work and that it not be your own research. Give us a short introduction (3 minutes) to the work and tell us what was great (or needs more investigation!).

Haven't read any articles or books lately? No worries! Come and listen and engage with others looking to discuss data related research.

The Journal Club is open to all RDAP members and RDAP Summit attendees.

2:50 pm - 3:00 pm: Break

3:00 pm - 4:00 pm: RDAP Business Meeting and Closing


Tess Grynoch, Research Data & Scholarly Communications Librarian, University of Massachusetts Chan Medical School

Amelia Kallaher, Data Literacy Librarian, Cornell University

Come find out more about what RDAP has been up to in the past year and our plans for the coming year from the different committees that advance the RDAP mission.

The RDAP Business Meeting is open to RDAP members and RDAP Summit attendees.


The RDAP community brings together a variety of individuals, including data managers and curators, librarians, archivists, researchers, educators, students, technologists, and data scientists from academic institutions, data centers, funding agencies, and industry who represent a wide range of STEM disciplines, social sciences, and humanities.


Mailing Address:
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Columbus, OH 43220



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