MDLS 2022 Archive

Purdue University & the University of Notre Dame
Online via Zoom and On-Site at Notre Dame
October 5-7, 2022

Session materials are available on the OSF Meetings Archive. Each talk has page on the OSF Meeting Archive with links to presentation slide decks.

MDLS 2022 Schedule

All times are in US Eastern Time
⏺️ indicates a session was recorded

Wednesday, October 5, 2022

Wednesday’s activities will take place in the late afternoon and will either be recorded or reprised later in the event in recognition of Yom Kippur.

On-Site Participant Check-In

3:00 - 4:00

— THEME: DATA MANAGEMENT SHARING POLICY —
Q&A will take place after the last session in each theme block
(please submit questions via Zoom chat or the “raise hand” feature)

Workshop

4:00 - 5:00

Preparing for the NIH DMSP: Researcher Needs and Perspectives
⏺️

Jess Newman McDonald, Research Data & Scholarly Communications Lead at U of Tennessee Health Science Center

Sarah Newell, Assessment & Data Services Librarian at U of Tennessee Health Science Center

Under the Data Management & Sharing (DMS) Policy the NIH requires researchers to prospectively plan for how scientific data will be preserved and shared through submission of a Data Management and Sharing Plan. The author took several steps towards determining a potential role in aiding the campus in complying with the new policy, including: benchmarking against libraries at similar institutions; meeting with campus stakeholders to listen to their concerns; and investigating expertise and resources available from other research support units. To better understand the researcher perspective, data interviews were conducted with a number of researchers from a variety of health science disciplines to determine their awareness of the policy, how/if they currently share research data, what campus data services they utilize, and how the Library can help meet their needs. Anonymized transcripts were collected and coded to discover emergent themes. Select quotations will be discussed as well as potential Library roles informed by these discoveries, existing resources, and librarian expertise. The assessment and preparation will continue to progress as we move closer to the policy’s implementation date. This presentation will cover initial findings from these on-going data interviews, which we expect will be beneficial to other libraries hoping to assess their role and readiness to assist researchers in this area.

Hybrid Social Event - Speed Data-Ing

5:00 - 5:30

A special speed networking event all about working with data! You will have five minutes with each of five randomized attendees to discuss your primary data work experience (strengths) and current and/or next data work challenge (weakness). We hope you’re able to find new contacts and maybe some solutions to your pressing data problems. This event will be reprised on Thursday, October 6.

Thursday, October 6, 2022

On-Site Participant Check-In

9:00 - 9:30

Welcome & Announcements

9:30 - 9:45

  • Dr. K. Matthew Dames, Edward H. Arnold Dean, Hesburgh Libraries and University of Notre Dame Press
  • MDLS 2022 Planning Committee

— THEME: DATA MANAGEMENT SHARING POLICY —
Q&A will take place after the last session in each theme block
(please submit questions via Zoom chat or the “raise hand” feature)

Lightning Talks

9:45 - 10:00

NIH DMS Policy in a Nutshell ⏺️

Katy Smith, Health Sciences Librarian at Medical Center Library, Saint Louis U

The NIH Data Management and Sharing Policy and its Required Plan in a Nutshell. As an experienced librarian, but in a new-to-me health sciences and data services role, I was confused and overwhelmed by the NIH Data Management and Sharing Policy until I attended an MLA training webinar provided by Nina Exner, PhD, MLS (Research Data Librarian at Virginia Commonwealth University Libraries). Inspired and encouraged, I followed her example and further broke down the policy language for my campus colleagues and researchers who appreciated the policy in a nutshell. I hope that this boiled down, nutshell version of the NIH DMSP helps solidify the NIH DMS Policy for you, too!

Preparing Librarians and Researchers for the NIH Data Management and Sharing Policy ⏺️

Lena Bohman, Data Services and Research Impact Librarian at Zucker School of Medicine, Hofstra U
Katy Smith, Health Sciences Librarian at Medical Center Library, Saint Louis U

Concerned librarians and other stakeholders have joined minds to produce guidance materials for libraries and librarians to prepare for the 2023 NIH Data Management and Sharing Policy. Learn what we have developed thus far for librarians to rely upon as we ready to support our researchers under the new policy: Glossary of DMSP terminology; Checklist for Researchers (Pre-DMSP Creation); Checklist for Researchers (Post-DMSP Creation and Pre-Submission); Policy Readiness Checklist for Librarians; Example DMSPs; FAQs; and a Data Repository Finder. These materials will be especially useful for librarians in small medical libraries as they can be used to prepare for the policy and answer researcher questions. Outcomes: Following the lightning round segment, attendees at any point of their careers will identify librarian created and curated sources to prepare ourselves, our libraries, our researchers, and our institutions for the 2023 NIH Data Management and Sharing Policy.

Choosing a Data Repository: Interpreting the NIH DMS Policy ⏺️

Levi Dolan, Data Services Librarian at Ruth Lilly Medical Library, Indiana University

The coming NIH Data Management & Sharing Policy (effective January 25, 2023) asks grantees to explain why they choose to preserve their scientific data in a particular repository, before generating that data. This lightning talk summarizes my efforts to collect, define, and communicate data repository considerations in line with the NIH’s new requirements to support NIH DMS Plan development for our school of medicine’s students, staff, and faculty.

Q&A and Discussion

10:00 - 10:25

Workshop

10:25 - 11:10

Delivering on the Promises: Meeting What They Put in the NIH DMPs
⏺️ (breakouts will not be recorded)

Abigail Goben, Data Management Librarian at U of Illinois Chicago
Tina Griffin, Information Services Librarian at U of Illinois Chicago

Looking ahead to Spring 2023, the first batch of NIH Data Management and Sharing Plans have been submitted. Now, researchers are back in touch asking for librarian help in ensuring they are able to meet the obligations they proposed Using a scenario-driven format, participants will explore a variety of potential institutional contexts and identify opportunities for library engagement, DMP revision, faculty and student education, and campus and community partnerships. Participants will co-create scenario responses in a shared document which will highlight challenges or unique considerations. The goal is to develop a collaborative resource document for attendees to take home as they further prepare for data sharing implementation.

Break

11:10 - 11:20

— THEME: RELATIONSHIP BUILDING —
Q&A will take place after the last session in each theme block
(please submit questions via Zoom chat or the “raise hand” feature)

Lightning Talks & Short Talks

11:20 - 12:10

Hands-on data literacy training for undergraduate students: A survey project
⏺️

Agnes Jasinska, Data Services Specialist, Research Services, Library & IT at Bucknell U

As a data services specialist and a member of the research services team at a liberal arts university, I work to foster and support data literacy on our campus. In this talk, I will outline my successful and ongoing collaboration with a faculty member to design, deliver, and assess a hands-on data literacy training for her students, in the form of a start-to-finish survey project in a 300-level course. Briefly, students worked in small groups to develop survey questions, build and test the survey in Qualtrics, distribute the survey to their peers, analyze and interpret the data, and present their results to the class. In addition to two instruction sessions (on survey development and on survey data analysis), I met with each student group to review their survey draft prior to data collection, and I participated in evaluating their final presentations. To make the learning experience as rich and valuable as possible, students were required to include both closed-ended and open-ended questions in their surveys, yielding both quantitative and qualitative data.

LESSONS LEARNED: Data skills for non-data librarians: There has to be a better way
⏺️

Kay K. Bjornen, Retired, Research Data Initiatives Librarian at Oklahoma State U

An early part of my primary job assignment was to spread the gospel of data to my fellow librarians. I was the first librarian hired for dedicated research data services support and was the only one providing that function. So, without knowing much about my colleagues, I jumped in to offer a pilot program entitled “Developing a Data Culture in the Library,” which was adapted from materials created by the Data Culture Project (databasic.io/en/culture/). The results were less than satisfactory. Some years later I am still not sure how to create a data culture in an academic library but have some thoughts about why this approach failed.

New York Data Carpentries Library Consortium: A Reflection
⏺️

Joshua Finnell, Interim Associate University Librarian at Colgate U
Emily Sherwood, Director of Digital Scholarship and Studio X at U of Rochester

The New York Data Carpentries Library Consortium (NYDCLC) was an association of academic, public, and school librarians who came together to form a community of practice focused on building data skills, including accessing, analyzing, using, and visualizing data. NYDCLC allowed members to share a gold-level membership with the Data Carpentries which resulted in a series of workshops on various data skills. This reflection by its co-founders will give a concise reflection on the successes, failures, and thoughts on academic and public libraries can partner in developing data science skills in partnership.

Creating new data reference models within existing library support structures
⏺️

Whitney Kramer, ILR Research and Data Librarian at Cornell U

How do you create a data-focused reference and instruction program that supports social science programs in a specific school within the larger university while also aligning your work with existing library and data services? In 2019, a liaison librarian at a R1 institution was tasked with creating a data reference and instruction program from scratch in order to support specific social science programs on campus. While there were existing data support services at other campus libraries, most were focused on the physical sciences, and the librarian’s unit had never provided focused data services to its constituents. This talk will provide both new and established data librarians with an overview of the unique, ongoing challenges and opportunities in creating a social science-focused data reference and instruction program from scratch during the pandemic while also fitting it into pre-existing library offerings. Attendees can learn about creating services that are meaningful to your constituents while not reinventing the wheel of existing library services on campus.

Leveraging Data Management: How DMPs Were Critical to the Success of a Four-Year, Multi-University Project
⏺️

Kristin Briney, Biology and Biological Engineering Librarian at California Institute of Technology
Abigail Goben, Data Management Librarian at U of Illinois Chicago

This talk will summarize the project manager’s and data manager’s experiences of creating and using a series of data management plans to keep a 4-year, multi-university grant on track. We will highlight the data management strategies used and the critical role of the DMPs across a variety of research methodologies, researcher experience, and personnel changes. We will share techniques used for ongoing team training and calibration and techniques for assuring compliance and consistency over time. Participants will have access to the final DMPs to use as templates or teaching examples.

Lunch

12:10 - 1:10

Hybrid Social Event - Speed Data-Ing

1:10 - 1:40

A special speed networking event all about working with data! You will have five minutes with each of five randomized attendees to discuss your primary data work experience (strengths) and current and/or next data work challenge (weakness). We hope you’re able to find new contacts and maybe some solutions to your pressing data problems.

— THEME: CURATION AND DOCUMENTATION —
Q&A will take place after the last session in each theme block
(please submit questions via Zoom chat or the “raise hand” feature)

Short Talks

1:40 - 2:30

Supporting Digital Curation in the Arts: Data Management Plans for Documentary Filmmakers
⏺️

Heather L. Barnes, Digital Curation Librarian at Wake Forest U

Documentary films have expanded their reach and popularity over the last few decades. Existing research indicates that independent documentary filmmakers lack access to resources that would ensure the long-term stewardship of their works (AMPAS 2012). This research project examines documentary film production through the lens of digital curation. It describes individual filmmakers’ data practices and proposes a data curation model designed to guide filmmakers and film archives in developing data management plans inspired by those currently used by researchers in the social and physical sciences but customized for filmmakers’ unique workflows. Semi-structured interviews with filmmakers explore use and storage of data; digital workflows; and relevant sites of contextual information/metadata. The proposed data curation model reflects the importance of the growing research data management field and integrates components related to digital storage, copyright, publishing, context, and file organization.

New and Improved: Refining the CURATE(D) model and developing online modules
⏺️

Briana Ezray Wham, Research Data Librarian for STEM at Pennsylvania State U
Mikala Narlock, Director, Data Curation Network at U of Minnesota

The CURATE(D) model for data curation is a useful teaching tool for demonstrating data curation best practices: while practical and structured enough to provide a foundation for learners, it also provides enough flexibility to be adaptive for different disciplines and data format needs. In the past year, the Data Curation Network has undertaken efforts to expand this model, incorporate ethical concerns, and make it accessible online via learning modules. In this presentation, attendees will learn more about the CURATE(D) 2.0 model and the collaborative revision process, as well as have early access to a beta version of the online learning modules. Participants will also be invited to provide asynchronous feedback on the modules during and following the session.

Documentation literacy as a metacognitive skill in computer programming
⏺️

Dominic Bordelon, Research Data Librarian at U of Pittsburgh

Computer programming is a vital activity in modern research, and effective programming requires utilization of software documentation. Although an extensive literature exists about the characteristics, practices, and challenges of software documentation in the development process, the introduction of documentation to novices has apparently been neglected. Documentation literacy is proposed here as a metacognitive skill involved in teaching, learning, and doing computer programming. The concept of documentation literacy can be utilized by instructors in order to raise learners’ awareness of documentation and its value, to develop learner facility with documentation, and to ultimately improve learner performance and sense of mastery. Documentation literacy relates to and builds upon existing concepts of information literacy and metacognition. Practical examples will be given for trainers delivering demonstration, as well as learners’ practice exercises.

Break

2:30 - 2:40

— THEME: DATA SERVICES (PART 1) —
Q&A will take place after the last session in each theme block
(please submit questions via Zoom chat or the “raise hand” feature)

Lightning Talks & Short Talks

2:40 - 3:10

LESSONS LEARNED: Overcoming the challenges in data librarianship
⏺️

Thilani Samarakoon, Biomedical Data Librarian at U of Miami

Data librarianship is an emerging field in academic libraries. As research becomes more data-driven, it generates a high demand for data services. I started working as a Biomedical Data Librarian in an academic library in March 2020. My primary job responsibilities include providing data analysis and visualization help which requires the knowledge of a programming language like R or Python or menu-based software like SPSS or Tableau. As someone new to the field, I had to be self-guided and explore the role, skill set, and competencies required for the position. I participated in various training programs to expand my skills and knowledge to succeed in the current position. I will focus on the lessons learned as I have acclimated to my new role and services. The presentation is targeted at individuals entering the field of data librarianship. I will discuss the onboarding process, available resources, the effort needed, and the learning curve associated with each domain.

Review of Data Services at Academic Libraries
⏺️

Kelly Bilz, Reference/Government Documents Librarian at Thomas More U

This lightning talk describes the process of reviewing data services offered by academic libraries, which I researched to inform the planning of a data literacy LibGuide at my institution, in response to growing demand for data skills in both the classroom and workplace. As a newcomer to data librarianship, the findings would help me identify not only what other libraries offered, but also what common researcher needs were and what modes of service delivery were used. I viewed websites and LibGuides from university libraries with robust data services, including George Washington University, North Carolina State University, and Purdue University, among others. I compiled the types of services offered, the data literacy skills addressed, and the technology provided. I made note of what was directed at students and what was directed at faculty, to better plan my library’s data services in the future. These findings also helped me articulate the demands of these services in terms of IT support, staff time, and training. The next steps are to survey faculty about their needs and what they need their students to know, collaborating with IT about our resources, and partnering with career services to tie data literacy to students’ career paths. This review of services was useful for my institution’s planning efforts, but it will also highlight what other libraries do well for institutions with existing services.

Data services from the ground up: Assessing user needs and building solutions for social sciences instructors
⏺️

Kendra Spahr, Academic Services Librarian at Kansas State U
Laura Bonella, Academic Services Department Head at Kansas State U

While libraries at research universities often provide data services, our library is only in the beginning stages of developing expertise and services in this area. Our institution was part of a multi-institutional Ithaka S+R study exploring the teaching practices and support needs of social sciences instructors teaching undergraduates with quantitative data. We conducted a qualitative research study to understand the experiences of those instructors at our institution. We identified instructors’ purposes for teaching with data and common learning goals. We then used our findings to identify ways the libraries could support their work. Our recommendations included hiring and/or developing librarians with expertise in helping researchers find, access, and use data; being more proactive in identifying and offering support to courses with assignments that require data discovery; and increasing awareness about using data in a legal and ethical manner. In this program, we will discuss what we learned, how our library is building data services from the ground up, and how you can apply some of our methods to your own unique situations. We’ll provide recommendations based on our research and the actions we’ve taken, focusing on support for teaching and learning in the social sciences.

Workshop

3:10 - 3:55

Engaging with qualitative researchers and facilitating qualitative data analysis
⏺️

Jessica Hagman, Social Sciences Research Librarian at U of Illinois Urbana-Champaign

Library data services are a vital part of the campus research infrastructure for researchers across disciplines. The framing of these services, however, can sometimes make it difficult to identify how researchers conducting qualitative projects can make use of those services. This challenge is exacerbated by the variety of research paradigms and methodologies used in qualitative work, which leads to a wide range of approaches to data analysis. Drawing on my own research with graduate students and faculty who conduct qualitative research, as well as experiences teaching courses and workshops on qualitative data analysis, this workshop will offer attendees a framework for working with individual researchers and developing a more robust data services infrastructure that is intentionally inclusive of the diversity of qualitative work. Workshop attendees will be invited to reflect on the framing of their own research data services and consider how such services can be organized and promoted in a way that invites qualitative researchers to the campus conversations about data sharing, management, and analysis. Attendees will also learn suggested questions for engaging with individual qualitative research to assess what campus and library resources and services may be of use to the researcher.

Break

3:55 - 4:05

— THEME: DATA SERVICES (PART 2) —
Q&A will take place after the last session in each theme block
(please submit questions via Zoom chat or the “raise hand” feature)

Panel

4:05 - 4:50

Growing data librarians: Reflections on identifying critical knowledge and skills for research data services
⏺️

Clarke Iakovakis, Scholarly Services Librarian at Oklahoma State U
Kay K. Bjornen, Retired, Research Data Initiatives Librarian at Oklahoma State U
Dani Kirsch, PhD Candidate in Integrative Biology at Oklahoma State U
Kevin Dyke, Maps and Spatial Data Curator at Oklahoma State U

Many academic libraries have strived to provide expertise and resources appropriate for the research data service (RDS) needs of their institutions. However, it is not easy to identify the perfect set of qualifications for RDS positions. A librarian’s MLIS education may not have covered research data tools, workflows, data funder policies and other aspects of the research landscape to a depth sufficient for providing these services. However, due to limited budgets and workforce, it is common for RDS to be covered by library staff as an added responsibility, secondary to their main assignments. Additionally, RDS librarians without an MLIS may be at a disadvantage when trying to fulfill roles such as reference & library instruction, subject liaisonship or using library databases & catalogs. Even in libraries where a strictly RDS role has been defined, persons in those positions may be expected to provide an unrealistically wide range of services, including data reference, data management consultation, statistical and analytical support, data and computational literacy instruction, and FAIR data guidance (e.g. curation, metadata, archiving, discovery). What are the most important criteria for success? Rarely is there a candidate who can cover all these bases. This panel discussion will share the experiences and perspectives of a research services unit leader, a recently retired data librarian, a geospatial data librarian, and a PhD candidate in a STEM field with an insider’s perspective (library GRA) about the “Must-haves and Want-to-haves” for institutions trying to staff RDS.

Break

4:50 - 5:00

Hybrid Social Event - Zoom Scavenger Hunt

5:00 - 5:45

There are up to 30 seats available, but if they fill up spectators are welcome to join in the fun!
Part scavenger hunt, part show-and-tell, participants will have two minutes to find an item in your environment that matches the prompt. After the group returns, each person will have 10-15 seconds to show their item and provide a brief explanation, if necessary. Creativity encouraged—there are no wrong answers! The winner of each round will be selected by popular vote. RULES: 1) An item may only be used one time. 2) Participants must be back with their camera on before the timer reaches zero.

Friday, October 7, 2022

— THEME: DATA TOOLS —
Q&A will take place after the last session in each theme block
(please submit questions via Zoom chat or the “raise hand” feature)

Lightning Talks & Short Talks

9:30 - 10:10

LESSONS LEARNED: Migrating research data from an Islandora to a Figshare-based repository
⏺️

Stefan Kramer, Research Data Librarian at American U

In 2015, a mid-sized private university, as part of a regional library consortium, deployed a new repository based on the open-source platform Islandora for various types of content, including research datasets created by faculty or purchased from external vendors. In autumn of 2022, the migration of much of this content to a repository based on the commercial Figshare for Institutions platform is underway. This presentation discusses reasons for the migration, and lessons learned to date.

00LOCKed Out: Using Cloud Environments in Data Workshops
⏺️

Brandon Katzir, Digital Services Librarian at Oklahoma State U

In this presentation, I’ll discuss the advantages of using cloud-based learning platforms in virtual and hybrid coding and data management workshops. Drawing on diverse experiences using R-Studio, R-Studio Cloud, Jupyter Notebooks, and Google Colaboratory, my presentation discusses some of the pitfalls of using native software and software packages and points out the advantages of a cloud approach. In particular, using cloud-based platforms helps alleviate time-consuming problems of installation, diverse operating systems, lock files, etc. In this lightning talk, I will discuss how using R-Studio Cloud and Google Colaboratory for data workshops helps users quickly adapt to the typical coding environments of R and Python and then replicate those environments on their own systems after the workshop.

General Knowledge, Local Strengths: building local research data skills and knowledge with the General Index
⏺️

Emily Cukier, Science Librarian, Washington State U

In this presentation, I will discuss my experience using a data-driven research project to learn firsthand how to work with data and strive towards best practices. The project summary will include a description of how I found and used local resources to study the frequency of use of gendered honorifics over time in the General Index (https://archive.org/details/GeneralIndex), a public database of keywords, ngrams, and metadata drawn from over 100 million scholarly articles. In addition to discussing my experiences with learning research programming and handling big data sets, I will also speak to the intricacies of working within my campus data ecosystem, highlighting how to build common ground to facilitate conversations with faculty and graduate student researchers.

— THEME: USING DATA FOR YOURSELF —
Q&A will take place after the last session in each theme block
(please submit questions via Zoom chat or the “raise hand” feature)

Short Talk & Lightning Talk

10:10 - 10:35

Using outlook data to document the workload of librarians
⏺️

Samah Alshrief, Data Specialist at Seton Hall U
Chelsea Barrett, Business Librarian at Seton Hall U

Library duties require librarians to be involved in several daily activities that might not be counted in the annual reports or yearly assessments. In this session, we will walk participants through using their MS Outlook calendar as a data collection tool for daily workloads. We will export the data and analyze it in Excel for administrative purposes.

Show me the data: teaching new librarians how to find institutional data for analysis
⏺️

Alexia Riggs, Director, A. Frank Smith Dr. Library Center at Southwestern U

Academic Librarians are often called upon to build cases for accreditation, funding, and relevance using peer comparison data provided by ACRL and IPEDS. New librarians often lack understanding of where to go or how to access institutional data. This presentation will demonstrate the value of mentorship and institutional training to new librarians by reviewing the work completed at a small academic library to model data access methods and develop conversations to communicate openly regarding academic assessment needs.

Break

10:35 - 10:45

— THEME: VISUALIZATIONS —
Q&A will take place after the last session in each theme block
(please submit questions via Zoom chat or the “raise hand” feature)

Short Talk

10:45 - 11:05

Analyzing unexpected success of a data visualization video series
⏺️

Kristen Adams, Science & Engineering Librarian at Miami U
Roger Justus, Data Services Librarian at Miami U

About a year ago, the library created a series of 17 YouTube videos on data visualization. These presented practical skills on making graphs and diagrams in Google’s Sheets and Slides, and Microsoft’s Excel and PowerPoint. They were made to support a Canvas module on data literacy, aimed at STEM students, but open to any student as a virtual workshop, and for faculty to incorporate in their courses. The Canvas module and the YouTube videos were advertised to faculty through email newsletters. Oftentimes asynchronous content like this is created and marketed, but still underutilized. The module has received little use; however, the YouTube video views were very high. The gap between the views and module use, made it clear that the YouTube views were coming from elsewhere, and were indeed more accessible than the Canvas module. This analysis explores which videos in the series were most popular, and delves into YouTube analytics to help determine who was using them and how they discovered them. The results will be used to formulate ideas for other asynchronous data literacy content that could hopefully be just as successful. The session will include not just the findings of this analysis, but also tips for conducting your own analysis using YouTube’s analytic tools.

Workshop

11:05 - 11:50

Making Infographics More Accessible
⏺️

Sandi Caldrone, Research Data Service Librarian at U of Illinois at Urbana Champaign

Infographics are powerful tools in an attention economy. They can communicate memorable messages quickly and clearly, but often are not accessible to the visually impaired and not compatible with screen readers. Using an infographic I created about applying Creative Commons licenses data, I will highlight practical strategies for creating infographics that are easier on everyone’s eyes, and that also translate more easily to accessible text.

Break

11:50 - 12:00

Closing Session

12:00 - 1:00

Lunch

1:00 - 2:00

MDLS Community Meeting

2:00 - 3:00

MDLS is a grassroots organization without a formal organizing body–join the conversation about future MDLS events at this year’s Community Meeting, which is open to all attendees.

MDLS 2022 Visitor Information

A message containing comprehensive participation logistical information was emailed to all registrant email addresses on Monday, October 3, 2022, at approximately 3:00pm EST. Please let us know (mdls-planning-committee@googlegroups.com) if you registered for MDLS22 and did not receive a message on October 3 with the subject, “Midwest Data Librarian Symposium 2022 Event Details–[ONSITE] or [VIRTUAL] Participation (Save this Message!)”

We recognize that there is a great deal to consider when deciding whether or not to attend in-person events at this time. We hope the information below helps your decision-making process. If you decide not to join us on-site, we hope you will join us virtually! - MDLS 2022 Planning Committee

COVID-19

While monitoring development of COVID-19 considerations, we are planning for a hybrid experience in 2022. Below please find COVID-19 guidelines for on-site participants. Updates to the information below will be communicated to on-site registrants at the email address provided when registering.

Immunizations

  • We strongly recommend that on-site attendees are up-to-date with their COVID-19 vaccinations/boosters.
  • We also recommend you consider scheduling your annual flu shot at least 14 days prior to the event so it can have its full effect.

Masking

  • We will follow masking guidance as issued by state and local public health authorities, and will abide by any relevant campus policies that apply to our event.
  • A KN95 mask will be provided at check-in for each on-site attendee.

Meals

  • Please check the on-site participation guide when it is available for meal details.
  • Boxed lunches will be provided Thursday and Friday so that attendees can eat outside or elsewhere as desired.

Room Ventilation

  • The HVAC systems on campus are designed and maintained to the standards of the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). The Hesburgh Library building has been determined to be safely designed to exceed the standard air filtration requirements.
  • Windows are not able to be opened, but we will be able to prop room doors open if desired.

Testing and Tracing

  • We strongly recommend performing a rapid COVID-19 test every morning before arriving on-site.
    • To order free rapid tests, please visit https://www.covid.gov/tests.
    • If you work at an academic institution, you may also be eligible for free tests through your health benefits (e.g., insurance, campus wellness center, campus pharmacy, etc.).
  • If you are not feeling well for any reason or test positive during your visit, we hope that you will remain in your lodging and rest (sessions will be recorded and slides, videos, and transcripts will be posted after the event). If you find yourself in this situation, please contact the Planning Committee so we can check in with you in the event you need assistance.
  • If you test positive or experience symptoms within 48 hours of returning home, please complete this anonymous form to let the Planning Committee know. We will email all on-site attendees to confirm that an on-site participant has tested positive so that we can all know we should take appropriate follow-up measures (testing, etc.).

State and Local COVID-19 Data and Policy Resources

Lodging Recommendations

Location

  • Hilton Garden Inn - breakfast not included - walking (1.1 mi) or shuttle
  • Inn at St. Mary’s - hot buffet included - walking (1.1 mi) or shuttle
  • Ivy Court Inn & Suites - hot buffet included - walking (0.9 mi) but not shuttle
  • Microtel Inn & Suites - hot buffet included - no shuttle
  • Quality Inn - continental included - no shuttle

Transportation & Parking

Directions and Maps

Campus Transporation & Parking

Community Transporation

Dining

  • During the symposium:
    • Please check the on-site participation guide when it is available for meal details.
    • On-site participants will be asked to select boxed lunch options when registering.
    • There is an Au Bon Pain in the Hesburgh Library building (1st Floor Concourse) if you would like to order a beverage or food item separate from the coffee/snack options provided at the event (advance orders can be placed via the GrubHub app on your personal device or on a kiosk outside of dining locations).
    • Please consider bringing a reusable water bottle and/or reusable hot beverage vessel for use during the Symposium to reduce waste.
  • Campus dining options
  • Eddy Street Commons
  • The 10 Best South Bend Restaurants – Yelp

Around Town

2022 Planning Committee

Co-Chairs:

  • Ben Chiewphasa (he/him), Columbia University
  • Chao Cai (he/him), Purdue University
  • Julie Vecchio (she/her), University of Notre Dame

Members:

  • Amy Koshoffer (She/Her), University of Cincinnati
  • Cameron Tuai (He/They), Drake University
  • Chad Kahl (He/Him), Illinois State University
  • Daria Orlowska (She/Her), Western Michigan University
  • Emily Cukier (She/Her), Washington State University
  • Kelsey Badger (She/Her), The Ohio State University
  • Kristen Adams (She/Her), Miami University
  • Leslie Delserone (She/Her), University of Nebraska-Lincoln
  • Mary Murphy (Any Pronouns), University of Wisconsin