PNR Data Science
The NNLM Training Office (NTO) and Southeastern Atlantic Region (SEA) are pleased to host Library Carpentry workshops this spring and provide professional development funds to support travel to these exciting opportunities.
In this two-day interactive, hands-on workshop you will learn core software and data skills, with lessons including:
- Introduction to Working with Data
- Introduction to Git
- The Unix Shell, and
- A brief Introduction to Python
Participants may apply to attend the workshop series in either:
- Baltimore, Maryland – March 19-20, 2020 or
- Salt Lake City, Utah – March 26-27, 2020
To broaden access to this exciting training, we invite applications to cover the costs of travel and attendance, up to $1,500 for Baltimore, and $1,200 for Salt Lake City. Travel costs will be reimbursed after travel occurs.
For more information, please apply here.
Applications Open for RDM 102: Beyond Research Data Management for Biomedical and Health Sciences Librarians (Spring 2020) Biomedical and health sciences librarians are invited to participate in a rigorous online training course going beyond the basics of research data management, sponsored by the National Network of Libraries of Medicine Training Office (NTO). This course will expand on concepts covered in RDM 101: Biomedical and Health Research Data Management Training for Librarians, and threaded throughout will be the librarian’s role in research reproducibility and research integrity and include practice in using Jupyter Notebooks. The course topics include an overview of data science and open science, data literacy, data wrangling, data visualization, and data storytelling.
The program spans 9 weeks from February 24 – April 24, including 5 modules of asynchronous content, a catch-up week, and a synchronous online session during the week of April 20. The format includes video lectures, readings, case studies, hands-on exercises, and peer discussions. Under the guidance of a project instructor, participants will complete a Final Project to demonstrate improved skills, knowledge, and ability to support data science services at their institution. Expect to spend about 6 hours each week on coursework and the project.
Applications are due January 10, 2020.
For questions and concerns, please contact the NTO at firstname.lastname@example.org
DataFlash: NIH Requests Public Comment on a Draft Policy for Data Management and Sharing and Supplemental Draft Guidance
On November 6th, 2019, NIH released a Draft NIH Policy for Data Management and Sharing and supplemental draft guidance for public comment. The purpose of this draft policy and supplemental draft guidance is to promote effective and efficient data management and sharing that furthers NIH’s commitment to making the results and accomplishments of the research it funds and conducts available to the public. Complete information about the draft Policy and draft supplemental guidance can be found on the NIH OSP website.
Stakeholder feedback is essential to ensure that any future policy maximizes responsible data sharing, minimizes burden on researchers, and protects the privacy of research participants. Stakeholders are invited to comment on any aspect of the draft policy, the supplemental draft guidance, or any other considerations relevant to NIH’s data management and sharing policy efforts that NIH should consider.
To facilitate commenting, NIH has established a web portal that can be accessed here. To ensure consideration, comments must be received no later than January 10, 2020.
For additional details about NIH’s thinking on this issue, please see Dr. Carrie Wolinetz’ latest Under the Poliscope blog:
NIH will also be hosting a webinar on the draft policy in the near future. Please stay tuned for details.
Questions may be sent to SciencePolicy@mail.nih.gov.
In honor of National Medical Librarians Month in October, we are featuring librarians in the PNR region who are medical/health sciences librarians as well as those who provide health information to their communities. This week of October 7th, 2019 we are featuring Montana State University’s Sara Mannheimer who is a Data Librarian. Welcome Sara, to the PNR Dragonfly blog!
- Name: Sara Mannheimer
- Position: Data Librarian
- Working organization: Montana State University
- Education history
- BA in Literature from Bard College
- MS in Information Science from University of North Carolina at Chapel Hill
- Personal Background
- Sara takes ballet and modern dance classes and she performed in a local dance showcase last month. Sara also play piano and guitar (but she only performs for her partner and her cat!). Sara was born and raised in Anchorage, Alaska, where she worked as a sea kayak guide in Alaska and the US Virgin Islands in her 20’s, and she still loves being outside—bike commuting, backpacking, camping, and cross-country skiing. Sara is also an enthusiastic extrovert and a believer in the power of community, so spending time with friends is one of her biggest sources of joy.
Q1: It’s an honor to have you with us on the Dragonfly Blog -welcome Sara! My first question is related to the theme of medical librarianship as October is National Medical Librarians month. So, what inspired you to work with medical data?
Thank you! It’s a pleasure to be featured! My work with data began in graduate school at UNC-Chapel Hill, where I studied archives and records management. I got into the world of data archiving through an independent study developing a digital preservation policy for Dryad Digital Repository. During the project, I had invaluable mentorship from Ayoung Yoon (who is now on the iSchool faculty at IUPUI) and Jane Greenberg (now on the iSchool faculty at Drexel). Ayoung was a PhD student at the time, and she collaborated with me on a poster that we presented at the ASIS&T annual meeting. Jane instilled in me a love for metadata and encouraged me to apply to be the Senior Curator at Dryad after I finished my master’s degree. Jane and Ayoung also mentored me by co-authoring a paper describing our digital preservation policy development process. Building on the work I did at Dryad, I decided to move to a tenure track faculty position as Data Librarian at Montana State University (MSU). At MSU, I help with data management planning, coordinate data science workshops, build data-related tools, and conduct research exploring data curation and data ethics.
Working with NNLM-PNR has been a great entrance into medical data. For example, NNLM-PNR just funded a project that will allow me and my colleagues Jason Clark and Jim Espeland to work with a research center on campus to make their restricted health sciences data available to community partners.
Q2: Tell me, how did you get into data science?
I’m still getting into it! I began my learning process through a couple of Data Carpentries workshops—one at the Research Data Access and Preservation (RDAP) Summit in 2015, and one at the National Data Integrity Conference in 2017, and then I trained to be a certified Carpentries instructor last year. But most of the data science instruction in the library is the result of collaborations across campus. I’m partnering with Allison Theobold, a graduate student in the statistics program who teaches workshops as part of her dissertation project. She and her advisor, Stacey Hancock, have helped create a thriving R workshop series in the library that includes introductory and intermediate R concepts, as well as sessions on data wrangling and data visualization. This year, we’ve extended the partnership to include graduate students from MSU’s Statistical Consulting and Research Services in order to continue to sustain the workshops. These statistics graduate students have strong coding skills, and they are amazing teachers for their peers.
In addition to teaching practical coding skills, I have an interest in big data ethics, and I have done some writing and thinking about the ramifications of data science using social media data. And I have also begun to pursue projects that support “collections as data”—that is, computational analysis for digital collections. This work includes initiatives like making the text of our digital archival collections available for download, and mentoring students to create digital scholarship projects using archival collections. This interactive map created by former MSU student Dillon Monday is a good example of a collections as data project.
Q3: In your time as Montana State University’s Data Librarian, what has been your most favorite project to date?
I think my favorite project is actually the first grant I was awarded from NNLM-PNR in 2017! The project took an evidence-based approach to creating a data management planning toolkit aimed at health sciences researchers. After identifying a need to improve the data management planning resources that the library provides to the campus community, I proposed a grant to analyze data management plans from grant proposals at MSU, and then to interview principal investigators about their data management practices.
The research I conducted (with fantastic student research assistant Wangmo Tenzing) showed that most investigators practice internal data management in order to prevent data loss, to facilitate sharing within the research team, and to seamlessly continue their research during personnel turnover. However, it also showed that investigators still have room to grow in understanding specialized concepts like metadata and policies for reuse. I used the research results to inform a data management planning toolkit that includes guidance on facilitating findable, reusable, accessible, and reusable data—for example, using metadata standards, assigning licenses to their data, and publishing in data repositories. If you want to read more, I’ve published a talk and a paper about the project.
Q4: Are you working on anything new and exciting that you would like to share with us?
I’m getting my PhD right now from Humboldt University in Berlin (with advisor Vivien Petras), and my dissertation is a comparative study of qualitative secondary analysis and social media research. I’m still early in the process, but I’m loving the opportunity to take a deep dive into the topic of qualitative and social media data sharing.
Q5: To date, what is your favorite data tool?
I’m really enjoying becoming more literate in R. We use RStudio Cloud in our workshops, and it simplifies the setup process for learners. I’m also keeping an eye on the development of Annotation for Transparent Inquiry (ATI), an annotation tool for qualitative research that’s being developed at the Qualitative Data Repository.
Q6: If you could give one piece of advice/words of wisdom to anyone interested in medical librarianship/data science what would that be?
Collaborate. Our library and academic communities are vibrant and varied, and I’ve done my most impactful work when partnering with colleagues and students. Data librarianship overlaps and connects with many fields, and it’s impossible to have expertise in everything. Working with collaborators allows me to extend my own knowledge, develop better ideas, and provide stronger data services on campus.