Re tooling for data management-support
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This document summarizes Sherry Lake's presentation on re-tooling libraries to support data management. Some key points: - The University of Virginia restructured its research support model in 2010 to focus on data management and created the Scientific Data Consulting Group. - Other models discussed include groups at Purdue, Johns Hopkins, Cornell, Wisconsin, and Rutgers that provide data management consulting and services. - Re-skilling existing staff involves training librarians through courses, workshops, and data interviews to build expertise in areas like data formats, metadata, and data management plans. - Multiple areas of competency are important for supporting research data, including information science, computer science, domain expertise, management
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Re tooling for data management-support
- 1. Re-Tooling the Library: Staffing to Support Data Management Sherry Lake July 30, 2012 University of Florida Data Management Workshop
- 2. Outline The UVa Scientific Data Consulting Model Other Models Takeaways Re-skilling
- 3. Scientific Data Consulting Group December/January 2010: rethinking the earlier research support model (due to budgetary pressures, changes in organizational priorities, emerging demand in research community) Spring 2010: decision to focus on data May 2010: close of Research Computing Lab, start-up of the Scientific Data Consulting Group (SciDaC) 3
- 4. Developing the SciDaC Model… Take what we learned in the RCL experience and apply it to the focused demands around data Steps: Conduct a stakeholder analysis Make a short term plan (12 months) Develop clear priorities Include Subject Librarians
- 5. Stakeholder Analysis (abbreviated) Internal External • Researchers • Funding agencies • Graduate Students • Broader research • Grant Administrators community • Deans • Broader Library/Institution • VP/CIO community • VPR • “The Public” • OSP • UL
- 6. Short Term Plan Survey Office of Sponsored Programs to match grant holders with regulations Educate/engage subject librarians Build political awareness/support Build partnerships with local/national/international groups
- 7. Clear Priorities 1. Data Interviews/Assessments with science and engineering researchers 2. NSF Data Management Plan Requirement preparation and development of policies and workflow 3. Institutional Repository Data Working Group
- 8. How to make this work… Librarians as partners • Consult with and advise researchers • Provide leadership to the institution • Work with existing data organizations In order to succeed, librarians need to: • Build and develop specific expertise • Facilitate communication
- 9. Training Librarians UVa Library Staff Model Scientific Data Consultants Subject Librarians Training Model Brown Bag Data Curation Discussions Data Interviews Goals and Objectives Build Data Literacy Create Collaborative Opportunities Establish the Library for Data Preservation
- 10. Brown Bag Topics University Libraries Data NSF DataNet Program Consulting Growth Model Data Interview Method Importance in Sharing and Caring UVA Institutional Repository for Research Data New Developments in Citing Data Data Preservation Funding Recap of First Three Data Models Interviews Group Facilitation: Planning Data Overview of Data Archiving and Services & Setting Responsibilities Sharing for Science and Engineering Considerations for Data as Science Data at Uva Intellectual Property The Data Interview Latest News on NSF Data The Data Interview Top 10 Management Plan Why is Data Management Science & Engineering Data Needed? Liaison Summary of Duties
- 14. Partnering with UVa Health Sciences Library Adjunct member of SciDaC in a “residency” Spend 10 -12 hours/week in SciDaC offices Served as a liaison between SciDaC and HSL Participated in SciDaC activities Interviews Data Management Plans Helped create NIH data management template Presentation by Andrea Horne at the MLA Annual Meeting 2012, Dealing with Data: Partnering to Support E-Science and Data Management on Campus
- 15. Purdue University Libraries D2C2: Distributed Data Curation Center http://d2c2.lib.purdue.edu Centered in the Research Department of the Purdue University Libraries Comprised of four core researchers Work closely with subject specialist liaisons in discipline areas throughout the Libraries Actively engage researchers to address problems of data curation in distributed environments
- 16. Purdue University Libraries Business Information Specialist: Develop interdisciplinary collaborations and research opportunities with faculty to meet the University’s and the Libraries’ strategic directions. Geographic Information Systems Specialist Advocates for best practices of geospatial data management, including using open source formats, appropriate documentation and use of metadata to enable downstream sharing of research data.
- 17. Johns Hopkins University Data Management Services http://dmp.data.jhu.edu Outgrowth from the Sheridan Libraries’ work on the Data Conservancy Comprised of two consultants and one manager Provide services and support to JHU PIs to prepare data management plans for proposals Provide research data archiving services once an award has been made
- 18. Cornell University Research Data Management Service Group https://confluence.cornell.edu/display/rdmsgweb/Home Jointly sponsored by the SR VP for Research and the University Librarian Has a faculty advisory board and a management council RDMSG Consultants provide: Single point of contact Guidance on data management planning Unified web presence Reference to Cornell’s appropriate services
- 19. University of Wisconsin - Madison Research Data Services http://researchdata.wisc.edu/ Collaboration between: • UW-Madison Libraries • The Graduate School • DoIT • School of Library and • CIO office Information Studies Data management plan help Consultations Training and education Referrals (data storage, security)
- 20. Rutgers University Ruresearch http://rucore.libraries.rutgers.edu/research/ Team: programmers, developers, data specialists, metadata librarians, and subject liaisons Consulting on Data Management Plans and data best practices Permanently archiving data in the RUresearch data portal Work on larger and more complex data needs in grant- funded projects
- 21. Takeaways 1. Investment is critical: infrastructure is important, but staff/services are critical 2. Gradual integration: doesn’t have to be creation of a new unit/center/etc., just needs to be a coordinated effort with a plan 3. Collaboration is fundamental: no single part of the institution has all the necessary expertise, focus on organizing the right people 4. Communicate: do your homework, come up with a message, get the team on the same page, and spread it far and wide (and over again)
- 22. Martin Lewis, U Sheffield Nine areas to be active in relation to research data
- 23. Admin, Problem-solving, Risk- Personal taking, Self-development, Time management Budgeting, Business acumen, Contingency planning, Project management, Service marketing Management Collaboration, Communication, Managing Interpersonal expectations, Negotiation, Relationship- building, Teamwork, Training Library/ Access rights, Collection management, Discovery tools, Information organisation, Intellectual Info Science property, Reference consultation, Service provision Competencies for data management Computer Data formats, Database design, Information modelling, Interface design, Operating systems, Programming, Science/IT Servers, Software maintenance, Systems administration Terminology, Methodologies, Domain expertise Standards, Techniques, Workflows © Information School / University of Sheffield 2012
- 24. Re-Skilling Existing Staff ICPSR Summer Course Applied Data Science: Managing Research Data for Re-Use Data Curation Curriculum Search database of programs and courses covering data curation and closely related fields Borgman, UCLA Information Studies Syllabus for Data, Data Practices, and Data Curation
- 25. RU Research Data Team Training Data Management Training to Support Faculty Research Need Each course divided into modules: Tools: data model, metadata, ontologies Data Management: data preservation, data reuse, life cycle of data Still developing content for more modules
- 26. Dorothea Salo Online Courses Research Data Management Across the Disciplines (LIS 341) Content available online Designed and developed by Wisconsin Research Data Services Online version Digital Curation course (LIS 855) Introduction to Research Data Management Sept 10-Nov 30 http://www.slis.wisc.edu/continueed-DataMgmt.htm
- 27. Questions? Sherry Lake Senior Scientific Data Consultant, UVA Library shlake@virginia.edu Twitter: shlakeuva Web: http://www.lib.virginia.edu/brown/data References: Hunter, C., Lake, S., Lee, C., & Sallans, A. (2010). A Case Study in the Evolution of Digital Services for Science and Engineering Libraries. Journal of Library Administration, 50(4), 335-347. doi:10.1080/01930821003667005.
- 28. References Corrall, S (2012), Skills Which Librarians Need, presentation at “Clarifying The Roles Of Libraries In Research Data Management: A Discussion Day To Find Creative Solutions”, RL UK http://www.rluk.ac.uk/content/clarifying-roles- libraries-research-data-management-discussion-day-find-creative-solutions Lewis, M. (2010) Libraries and the management of research data, in McKnight, S. (ed.), Envisioning Future Academic Libraries Services: Initiatives,Ideas and Challenges, 145-168, Facet Publishing. Many other Links on Zotero: https://www.zotero.org/groups/ufloridatraining/items
- 29. Image References Title Slide 1. http://www.flickr.com/photos/grantloy/4577061495/ By grant_loy 2. http://www.flickr.com/photos/catchesthelight/3187651801/ By catchesthelight 3. http://www.flickr.com/photos/stevenm_61/2673806520/ By StevenM_61 4. http://www.flickr.com/photos/gregory-moine/4302464123/ By Gregory Moine 5. http://www.flickr.com/photos/54485353@N05/5784339186/ By janna487
Editor's Notes
- As the Research Computing Lab, located in the Charles L. Brown Science & Engineering Library, our main use came from undergraduates (needing software and software installation help) and graduate students. We did offer short courses on data analysis software (SPSS, SAS, R, MatLab) , on data management, and best practices for collecting data. Aiming to provide support across the entire scientific research data lifecycle Staff with expertise in: DataQuantitative data, statisticsModeling, visualizationScientific publishingEmphasis on consulting, not drop-off servicesAs we were looking to see how to build upon what we did in the RCL, we looked at the trends.Based on the trends and challenges in my previous talk.The transition between the RCL and SciDaC was easy for us as we already had the skills and the decision was made based on experience the past 4 years. He had campus relationships we had made from the RCL. In our opinion, it was the consultancy part that we needed to focus on now. With this new collaboration, we know what we can do well and we refer to what we don’t. We could focus on good competencies (baseline expertise) and rely on others for the rest.The creation of our new group was just about the time the NSF announced its Data Management Requirement.
- We now had a purpose and the support of Library’s AULs. So we started formerly (officially) developing the Scientific Data Consulting Group (SciDaC). To start with we took what we learned in the RCL “experience” and applied it to a more focused support around data. We knew we had the VPR, CIO and OSP on our side, but we needed to figure out the stakeholders who were driving the research and who would the researchers listen to. We started with a short-term plan…. About 12 months, with 3 clear priorities. We made a decision to provide “consulting” and not “services”. We were a team of 2 and couldn’t solve everyone’s data management, but we could figure out who could provide the services, where the researchers could go for help. Our team of 2 also were not subject specialists, we needed to include our Subject Librarians. With all these people involved, SciDaC, researchers, Stake holders, Subj. librarians….Communication was very important!
- Here’s an abbreviated list of stakeholders: Internal - those who should be aware of the importance of managing, sharing and preserving research data at UVa and External – those who were requiring management, sharing and preservation of data. Also important to us were our colleagues at other institutions, supporting data in the library was very new, we had much to learn from each other. Like we are doing here at this colloquium.
- Here’s the outline of our short term plan. We got the last 5 years of grant awards. We used the information and sorted the data many ways to figure out who had the most money, least money, greatest number of grants, who had received grants consistently, where did the money come from (granting agencies)… we then looked to see what the sharing/data policies were. We couldn’t do this alone, we needed more bodies and the subject expert. We had to engage our subject librarians and educate them on the importance of data management. We had already started building awareness and support, but we needed to involve other stakeholders. Using conferences, e-mail lists and casual contacts we set out to build partnerships with local/national and international groups. Administratively, we got the commitment for a new full-time position. I went from part-time to full-time. We then had 2 dedicated persons in the library. Since we didn’t have any overhead, we needed a budget for travel to conferences, to present papers and posters. We needed to be in with the other groups (IDCC, Purdue, Cornell) that had already started Data Services in the library. Collaboration with external partners with similar needs and problems was key. And we needed our AULs to back us up to talk about the support our group can give, to help us open doors to the other internal resources we needed.
- Key to our success is setting Clear Priorities. Setting them and making sure everything we do fits them. Picking just a few allowed us to focus and to constantly communicate their importance. These continue to be our priorities. We have not changed them since we started.Our Priorities are: )still are)Data Interviews/Assessments with science and engineering researchersNSF Data Management Plan Requirement preparation and development of policies and workflowInstitutional Repository Data Working Group
- We haven’t done this by ourselves, we couldn’t, it’s only 2 of us!! To make all of this work (our priorities on supporting data management) we needed to include our subject Librarians. They are the subject experts, SciDaC is not. They are seen as leaders and are good at working with organizations. But in order to succeed in a Data Research world, they need to understand the data landscape and be able to talk to researchers about the importance of data management and help them figure out the best way to share and where to share their data. They need to be in on the whole research lifecycle not just the beginning (with research/topic help) or the end (collection building written works), but be an important resource through the research.
- This slide is what we refer to as our SciDaC training model. Our model of “Re-tooling” the subject Librarians to meet emerging demands of scientific data management. It consists of SciDaC as the center of the hub. Our subject Librarians surround the hub and are the interface between SciDaC and the University Departments, the outside hubs. The model focuses on 2 main activities – “Data Curation Brown Bag” discussions and data interviews. Each Brown Bag session focuses on a very specific topic (i.e., the NSF data management plan policy, the NSF DataNet Program, etc.) offers a short presentation and white paper, and then concludes win an informal discussion. Through this process, we hope to gradually help traditional subject librarians develop literacy in issues and trends taking place in the emerging data curation space . The sessions are expected to help subject librarians become conversant in the issues and promote the discussion among their departments and faculty as they interact with them. In parallel, the sessions also prepare the subject librarians as partners for the data interviews. The goal of the Data Interview is to develop an understanding of how our science and engineering researchers mange their research data and initiate a discussion about how to simplify processes and improve practices. As I discussed before, the Subject Librarians are part of their faculty’s Data Interview. A final report is then distributed to ALL subject librarians helping give them a better understanding of research data processes beyond their own fields.
- Do you see any benefit over one way (centered) approach or the other?Which way would work here at UF?
- The “elevator speech” slide. Included after the presentation.
- Those at MLA this Spring might have attended the session “Smells Like Team Spirit: Partnerships to Move Your Library Forward”Health Science Librarian was ready for a career change and acted upon discussions between SciDaC and supervisor.Good timing to change or create a new position (Research & Data Services Manager)Andrea did a little more, she came over to our offices and participated in our activities as well as training. This internship (residency) allowed Andrea to work directly with us to gain knowledge and skills around data issues and ultimately contribute to the team’s activities including data interviews and data management plan consultation.We got to extend our interviews into the SOM. Participated in DMP reviews and brought expertise and relationships with SOM grants to help with NIHAndrea has now involved other health sciences library staff in data management activities, including data management plan reviews and data interviews.
- As I showed you in the previous presentation, Purdue Libraries were at the forefront of Research Data Services in the Library. Led by James Mullin and Associate Dean Scott Brandt, they created the Distributed Data Curation Center.
- Not sure how JHU incorporates liaisons?According to IASSIST presentation, they are still investigating the JHU cultures (including “Library colleagues”) to introduceData Management Services
- Jointly sponsored by the Senior Vice Provost for Research and the University LibrarianAbout 11 consultantsAdvanced ComputingSoftware architect6 Librarians (research data sciences, research librarian Medical library)Library policy advisorIT security
- Data management plan helpWe can help draft a plan to meet requirements from NSF and other funders.We can also review your plan and suggest improvements.ConsultationsData workflow and process improvement in your department, research unit, or laboratory.File-format and metadata standards that fit your research and your community.Digital preservation and archival concepts, to help you avoid losing your work.Advice on data sharing and reuse rights, to maximize your influence and credit.Database design advice and data modeling suggestions to get the most from your data.Training and educationWe will train your trainers in data-management best practices.We also train you and your lab, customizing our approach to what you want to accomplish.We come to research-methods courses to train the next generation of researchers.We bring our expertise to your symposium, brown-bag, or meeting.ReferralsStorage and backup solutions, on campus and off.Data-security experts, particularly in the Office of Campus Information Security.
- According to a rough classifcation, the team consists of three data specialists, three metadata specialists, four subject liaisons, two programmers, and four cyberinfrastructure developers. The team is not a policy-making or deliberative body. Its function is to work on data projects (structuring data, ingesting into RUcore, and ensuring correct presentation of data). Those from public services were happy and surprised to learn of the technical capabilities of RUL, and were now able to make referrals. prepare them to talk with faculty and others in the university, both about specic projects, and larger policy issues relating to data. In order to be member of the team, need to have gone through the training courseInternal Data Management Course (I’ll talk more about later).
- Here are the things to take away from this presentation for those wanting to start support for data management or curation at your library: You must: invest in staff and services, it doesn’t have to be creation of a new unit/center/etc., just needs to be a coordinated effort with a plan and clear limited number of priorities; you can't do it by yourself you need collaboration within your institution and external partnerships; no single part of the institution has all the necessary expertise, focus on organizing the right people and the last point is COMMUNICATE: do your homework, come up with a message, get the team on the same page, and spread it far and wide (and over again).
- here are several areas where libraries can and should be active in relation to research data. In most of these areas, they will want to work in partnership with other campus agencies, notably IT services, but also research offices and those responsible for research governance (such as a Pro-Vice Chancellor for Research). Nine such areas can be grouped handily into a pyramid, for ease of reference, but this is intended to be neither exhaustive nor definitive. In general, the activities lower in the pyramid are areas of early engagement, and which may be appropriate for the highest number of university libraries regardless of the scale of the research base of the parent institution.
- Corrall, S (2012), Skills Which Librarians Need, presentation at “Clarifying The Roles Of Libraries In Research Data Management: A Discussion Day To Find Creative Solutions”, RL UK http://www.rluk.ac.uk/content/clarifying-roles-libraries-research-data-management-discussion-day-find-creative-solutions
- What if you don’t have the skills needed to start services like this. How can you train, re-train your existing staff?ICPSR 1st year Good course because of its mix of participants.This workshop is for individuals interested or actively engaged in the management and curation of research data, particularly data scientists, data managers and analysts, librarians, archivists, and data stewards and curators.Curriculum Searchdata was compiled as of the Fall of 2011. Unless specifically requested to update, the information is as of that date.
- To build the skills of its Data Team, an internal Research Data Management course was developed under the leadership of Grace Agnew, Associate University Librarian for Digital Library Systems. Data Management Training to Support Faculty Research Needs is the course's title, and its primary goal. The initial core of the course grew from Grace's experience teaching digital library metadata to Rutgers' School of Communication and Information students. Designed to give librarians and staff the tools and contextual knowledge needed to handle data in each of their respective roles. The course is team taught. Each of our in-house experts presents on their area of expertise. Grace coordinates the metadata portion of the course; Ryan coordinates the data management portion of the course. Two hour class sessions plus group homework assignments and discussion. Initial plan for at least monthly meetings. Some gaps in meetings due to busy schedules!
- Research Data Management Across the DisciplinesLIS 341 (1 credit)When: Week of June 12, 2012 (5 mornings; homework in afternoons)Instructor: Dorothea SaloThis course prepares graduate students (including research assistants and dissertators) to look after research-generated data responsibly.Dorothea has also made available herSyllabus: LIS 855, Digital curationLink available in Zotero listIntroduction to Research Data ManagementThis course will prepare liaison librarians, scholarly-communication librarians, systems librarians, and digital librarians to help academic libraries take their rightful place in research-data management. Whether your library has just started to think about supporting researchers or has an established program in place, you will learn where researchers' difficulties lie and how librarians can help.