Research Data Services at the University of Utah
•Download as PPTX, PDF•
1 like•242 views
Presented for a lunchtime lecture at UC Irvine. Discussed how we are building data services at the University of Utah Marriott Library.
Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Viewers also liked
Viewers also liked (18)
Similar to Research Data Services at the University of Utah
Similar to Research Data Services at the University of Utah (20)
More from Rebekah Cummings
More from Rebekah Cummings (20)
Recently uploaded
Recently uploaded (20)
Research Data Services at the University of Utah
- 1. RESEARCH DATA SERVICES AT THE UNIVERSITY OF UTAH REBEKAH CUMMINGS, RESEARCH DATA MANAGEMENT LIBRARIAN UNIVERSITY OF CALIFORNIA, IRVINE JUNE 24, 2016
- 3. WHAT ARE LIBRARY DATA SERVICES? Services that a library offers to researchers in relation to managing research data. UK Data Services Research Data Lifecycle https://www.ukdataservice.ac.uk/manage- data/lifecycle • Planning • Organizing • Security • Description • Storing • Sharing • Archiving • Intellectual Property
- 4. LEVELS OF DATA SERVICES
- 5. Sayeed Choudhury’s Data Stack Model https://www.youtube.com/watch?v=3MD7KjZF34Y
- 6. MY JOB DESCRIPTION • Develop and provide consultation services on data- related issues. • Develop instructional programming and documentation. • Explore and pilot baseline data services. • Provide professional development opportunities for subject liasions • Maintain expertise on copyright, open access, data management, and preservation. • Participate in University-wide initiatives related to data.
- 7. FIRST STEPS: LAY OF THE LAND
- 8. FIRST STEPS: WEB PRESENCE
- 9. FIRST STEPS: OUTREACH & RELATIONSHIP BUILDING • Subject liaisons • The Kem C. Gardner Policy Institute • The College of Architecture and Planning • The College of Humanities • The Alzheimer’s Institute • Research Administration Training • Entertainment, Arts, and Engineering • Office of Undergraduate Research • Grant development services • VP for Research • Center for High Performance Computing • Health Science and Law Libraries • Individual Researchers
- 10. FIRST STEPS: PROVIDING EDUCATION OPPORTUNITIES • Library workshops • Research Administration Training Series • Undergraduate Research Workshop Series • Graduate student workshop series • Research and Learning Services Forum • Spring Research Series • All Staff – “How to organize digital files” • 1:1 Consultations • Zotero workshops • ICPSR workshops (this fall) • Subject liaison training (this fall) • Monthly Data Journal Club
- 11. FIRST STEPS: PROJECTS / USE CASES • EAE Archiving Task Force • Data Curation Pilot Project • Digital Humanities Working Group • U of U Living Laboratory • Pioneer Diary Project
- 12. FIRST STEPS: NEEDS ASSESSMENT • Campus survey – May / June 2016 • 203 responses • 70% of responses came from faculty • Captured demographics, types of data, data storage and backup, data description, data management plans, data sharing, legacy data, data management issues and services. • Ended survey by asking if they would like to participate in focus groups this fall.
- 13. DIGITAL HUMANITIES WORKING GROUP • Partnership between Marriott Library, College of Humanities, College of Fine Arts, and College of Architecture and Planning. • Interviewed leaders in DH – Miriam Posner, Dan Cohen, Bethany Nowviskie, and John Unsworth. • Discussion topics: space, funding, identity, staffing, and initial projects. • Created a mission statement • Cluster hires / DH Symposium
- 14. NEXT STEPS • Digital Matters Lab – “pop-up” space this fall • Continued assessment of data needs including focus groups • Enhanced suite of data services • Refining workflows and processes • Keep learning…
- 15. LESSONS LEARNED 1. What I can do is dictated by my strengths and weaknesses. 2. Collaboration is key – but it takes for-ev-er. 3. Pick a few key projects on which to focus. 4. Learn from the gold standard of RDM, but do what’s right for your institution.
- 16. THANK YOU! LET’S TALK! Rebekah Cummings Rebekah.cummings@utah.edu 801-581-7701 @RebekahCummings
- 17. QUESTIONS FOR CONSIDERATION • What data services should Research 1 institutions such as the University of Utah and UCI offer to their faculty and graduate students? • What data management activities has UCI engaged in? Are data services local to your campus or provided via CDL? • When should data live at an institutional repository as opposed to a subject based repository? • What impediments have you experienced developing data services? • How are you developing services, pedagogy, and/or research opportunities for digital humanities scholars?
Editor's Notes
- I’m Rebekah Cummings, the research data management librarian at the University of Utah Marriott Library. I’m a fairly recent graduate of library school. Studied data curation at UCLA, interned at the UCLA Social Science Data Archive, my second year I was asked to join Dr. Christine Borgman’s research team studying the data practices of scientists. So I was one of the lucky few data librarians that was actually trained to be a data librarian in library school. The University of Utah Marriott Library in Salt Lake City Utah. Research Institution, 31,000 students, one main library, also a law and health sciences library,
- Not knowing who would be here today, I thought it might be useful to spend a couple minutes talking about what library data services are and what is the motivtion behind them. A definition from an ACRL white paper: http://www.ala.org/acrl/sites/ala.org.acrl/files/content/publications/whitepapers/Tenopir_Birch_Allard.pdf Motivations behind research data management. When we talk about supporting data services, we usually talk about how we can support data through the entire research lifecycle. Planning a research project, best practices when collecting data, describing the data for secondary use, capturing workflows and processes so that someone else could replicate your research, making data as open as possible at the end of a project, finding a repository, linking your data to publications, and helping people find data that they can use in their research.
- Data services can vary greatly from institution to institution based on many factors. available technical infrastructure local expertise the needs of your faculty the support of your administration If you are just getting data services started, these are some of the more basic things that libraries are doing to support the data needs of their reserachers Most libraries graduate from these basic services to mid-level support. At the highest level, you have actual infrastructure for long-term data preservation and data curation, which is markedly different than data storage or data
- Another useful way to think about data services is a progression from simple data storage all the way up to full blown data curation. There are no definitive definitions for these terms but this is a great place to start when considering scaling up data services. Storage – data lives somewhere. Bits on disk, tape, in the cloud. Archiving – some degree of data protection and access, lives somewhere where it can be readily shared with a DOI and suggested data citation. This would still probably require someone to contact a PI if they intended to reuse this data. Preservation – this is the level where data can be reused and interpreted without contacting the original data producer. Curation – adding value to data. Automated metadata extraction, provenance tracking, new query capabilities. Very few people actually do this. ICPSR is a great example of an institution that does actual data curation.
- With that framework in mind, let’s get back to how we’ve actually starting building data services at the U.
- The first thing I did was try to get a sense of the people and services that already existed in my library that could be considered data services. Using the data lifecycle, I thought about who existed in the library and across campus that could support researchers with their data needs. There were two other data librarians on campus and the three of us were well equiped to provide DMP assistance and consultations. Metadata experts that could help with data description Institutional repository that could provide a parking space for data; DOIs, data citations, one impediment was that the IR does not accept submissions over 40 MB so it’s not ideal. Digitization lab for digitizing legacy data and making it available online. GIS services Statistical analysis assistance Qualitative data assistance Reference
- First step: Have some kind of web presence. If people came to the Marriott Library website, there was little that indicated that we had data services besides our lib guides, which were text heavy and packed with information, but not particularly user friendly.
- Started with 30 minute meetings with subject liaisons for social sciences and humanities– Have you ever had a faculty member talk to you about their data? Have you heard them talk about data services that might be useful for them? What types of data do your researchers collect? Do you know if there is a repository for data that is used in their field? How would you like to see my new position support the work that you do?
- Anytime someone was promoting guests for a workshop series, I asked if data management would be a good topic. I started to think of myself as a data evalgelist and I gave the data management talk as much as I could. In the humanities I learned that “data management” doesn’t really resonate with them so much BUT if I pitch it as organizing their research materials using Zotero and EndNote, they were all over it. Another important education opportunity was through monthly data journal clubs in the library. Every month we bring assign a data-related article and bring in guest speakers to talk about their data. We switch off every other month between the sciences and the social sciences and humanities. Most important is that we always dedicate at least half of the session to discusson. We now have between 15-20 people attend DJC every month. In the beginning we had maybe 5-6 people show up. Once we added free food and guest speakers, our attendance tripled.
- Ultimately our goal is to have a data repository and processes for how to archive datasets. So one of the things that has been really helpful is to work with a few groups on campus to pilot data archiving services.
- I’m putting the microphone down now.