Teaching Data Management

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Elaine Martin, D.A., presented Teaching Data Management at Purdue University in September 2013. She demonstrated strategic data management plans and skills librarians will need to help researchers develop a plan for organizing, preserving, and storing their data for easy access and retrieval. Details can also be found at Twitter hashtag #datainfolit.

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  • At UMASS Medical School, we’ve been planning the frameworks for a data management curriculum targeted for undergraduate and graduate health science, science and engineering students.This curriculum has been developed into a series of seven course modules that are designed to be flexible enough to be used with undergrad and graduate students—and for students studying diverse science disciplines.This project is funded through an Institute of Library Services National Leadership Planning grant that we, in partnership with Worcester Polytechnic Institute (WPI) were awarded in August 2010 and through funding from the NN/LM NER.
  • To customize instruction to specific disciplines, we have met with faculty and discussed real life research scenarios that illustrate issues in data management. Education committee librarians and a consultant have written several case scenariost for diverse research settings and subjects. They’ve developed excerpts of them that can be enfolded into specific online modules to illustrate the concepts in those modules. For example, a research case scenario on aerospace engineering illustrates data ownership concepts for data generated via proprietary instrumentation and analyzed with student-created Matlab code.
  • From an analysis of the data management programs that we reviewed in the literature search and the responses to the student and faculty interviews, we were able to identify learning objectives and organize these learning objectives into lesson plans for course modules. This chart shows the course modules that make up the curriculum. Each of these course modules could be delivered in an online format, in person, or hybrid. This modular format allows for flexibility in directing appropriate instruction to specific groups. For example, for a class of undergrads working on their first research project, all 7 modules would be appropriate. Librarians leading a workshop for new faculty might want to deliver instruction on data management plans, security, naming, privacy and restrictions—thus would select modules that covered these concepts. And a medical student collecting personal data would need instruction from the introductory module, module 3 on storage and security, and module 4 on legal and ethical considerations.
  • Here is an example from a biomedical engineering lab that shows how you can add in project information into the file name. Notice that he labels each file with an experiment that links back to the laboratory notebook, so that there could be multiple people in the lab and multiple experiments involving the same sample, but having a systematic approach to labeling and mapping files allows for the efficient retrieval and interpretation of the data.
  • The experiment depicted in this case is the delivery of stem cells on a fibrin microthread to areas of damaged tissue in a rat’s heart. The ultimate purpose is to restore mechanical function of the damaged heart tissue by seeding stem cells that will differentiate into cardiac muscle cells and restore function to areas of heart tissue.What type of research would you describe this case?SimulationObservationalExperimentalDerivedYes it is experimental—and most of the key data sets such as the images and the left ventricular pressure measurements are generated from lab equipment
  • This timeline provides a chronological table of the multiple steps in the experiment that generated data. When you’re reviewing a research case in which there are multiple types of data that have been created—you may find it helpful to sketch a timeline that notes what data was created at what time in the project—this timeline helps you to breakdown the experiment in stages to get a broader picture of the data generated.
  • File formats for the images and for numeric measurements: not mentioned in the case study
  • There are easily up to 10 people involved in analyzing the data of the experiment. One might be analyzing the mechanical function of the heart, one may be analyzing trichrome staining, one may be analyzing images.The data sets are all linked together on an Excel spread sheet. Biggest challenge is tissue sections that are on conventional slides.
  • The various storage places between the digital files, the slides, and the paper lab notebook and surgical log make it difficult to easily access, integrate, and analyze the various data outputs from the experiment.Moreover, look at the security issues. “we back the data sets on an external hard drive someplace” ---where?Files are not password protected. The lab notebook is either in the PI’s office or most often in the lab, which has key card access.
  • Teaching Data Management

    1. 1. Teaching Data Management This project is made possible by a grant from the U.S. Institute of Museum and Library Services and with funds from the National Library of Medicine under Contract No. N01-LM-6-3508. Lamar Soutter Library UMMS
    2. 2. Developing a RDM Curriculum • Phase I: Planning • Phase II: Content Development • Phase III: Piloting and Implementation • Phase IV: Evaluation Lamar Soutter Library UMMS
    3. 3. Phase I: Planning • Interviews • Surveys • Outside Speakers • Educational Committee • Planning Board • Consultants • Literature search Lamar Soutter Library UMMS
    4. 4. Student Interviews • Preference for electronic lab notebooks • Software used with their data - Perl, GraphPad Prism, Filemaker Pro, SPSS, SAS, Nvivo • Data backed up and shared in emails, the cloud (Google Drive, Dropbox) • No standard naming conventions used for directories and/or files. Lamar Soutter Library UMMS
    5. 5. Student Interviews • Lab data protocol changes from lab to lab - usually at the call of the PI. (wet labs vs. dry labs) • Most rely on the network server • Backups were not consistent. Lamar Soutter Library UMMS
    6. 6. Faculty Interviews • RDM Practices are varied • No formal RDM training provided for students • Lab managers and students come and go • Students need a familiar context to learn RDM so that can apply lessons in their own practice This led to the idea of developing teaching cases Lamar Soutter Library UMMS
    7. 7. Customizing Curriculum • Mix and match modules as needed by discipline/course level • Provide lesson plans for diverse modes of delivery: online, in person, hybrid • Case based activities and assessment • Readings • Assignments Lamar Soutter Library UMMS
    8. 8. Research Case Scenarios • Aerospace engineering • Biomedical lab research • Clinical study on hip replacements • African American Perceptions of End-Of-Life Care Photo: CDC/Taronna Maines NASA/Michael SoluriGary Meek/NSF Lamar Soutter Library UMMS
    9. 9. Course Modules Module 7 Archiving and Preservation Module 2 Data: Types, Stages, and Formats Module 6 Data Sharing and Reuse Policies Module 4 Data Storage, Backup, and Security Module 5 Legal and Ethical Considerations Module 1 Overview of Research Data Management Module 3 Metadata Lamar Soutter Library UMMS
    10. 10. Phase II: Content Development • 2012-2013 UMMS awarded NN/LM NER grant to develop the frameworks into a course with module content, lecture slides, activities, and teaching cases • Partners: UMass Amherst, Marine Biological Laboratory and Woods Hole Oceanographic Northeastern University, Tufts University • Designed for flexibility Lamar Soutter Library UMMS
    11. 11. Case-Based Learning • Cases provide the opportunity for instructors and students to explore discipline-specific data management issues • Course modules provide a context of universal data management issues and best practices Lamar Soutter Library UMMS
    12. 12. Module 1 Lesson Plan Lamar Soutter Library UMMS
    13. 13. Module 1 Content Lamar Soutter Library UMMS
    14. 14. Module 1 Slides Lamar Soutter Library UMMS
    15. 15. Regeneration of functional heart tissue with stem cell delivery A data management case study in biomedical engineering research Lamar Soutter Library UMMS
    16. 16. Lamar Soutter Library UMMS Case Analysis using Simplified Data Management Plan 1. Types of data 2. Contextual details (metadata) needed to make data meaningful to others 3. Storage, Backup, and Security 4. Provisions for Protection/Privacy 5. Policies for re-use 6. Policies for access and sharing 7. Plan for archiving and preservation of access SDMP
    17. 17. Lamar Soutter Library UMMS Experiment: delivery of stem cells on a biological fibrin microthread to areas of damaged heart tissue in one rat’s heart Purpose: to restore mechanical function of damaged heart tissue
    18. 18. Timeline of Experiment: Lamar Soutter Library UMMS Collective data from experiment 8 days +: Section heart, tissues on slides, staining, images of tissues, tracking particles on heart 7 day: #2 Surgery: examination, high speed imaging/LVPs, isolate heart and place it in freezer 0 day: #1 Surgery: infarct/delivery of stem cells to damaged heart tissue -1 day: Stem cells in solution with biological suture -2 days: Incubate stem cells with markers SDMP #1 Creating data
    19. 19. Lamar Soutter Library UMMS File Formats Data File Format Images ? Left ventricular pressure measurements ? Home made software MATLAB or C Histology sections Slides—file name based on stain—example .act is actinin stain Contextual Paper lab notebook, animal log Directory that links data sets together: Excel spread sheet SDMP #2 File formats SDMP #3 Storage SDMP #4 Ownership
    20. 20. Lamar Soutter Library UMMS Analyzing the data “There could easily be up to 10 people involved in data analysis and we have not yet found a good way to link all the data.” Dr. Glenn R. Gaudette, PI
    21. 21. Lamar Soutter Library UMMS Data Set Storage Optical images taken during Surgery: (~10,000 images) 1000 images for each data set Hard drive acquisition computer > Drobo backup>hard drive of network computer backed up by institution Left ventricular pressures (numeric) correlating with specific images Same as above Tissue sections Slide boxes—could be in any of 3 or 4 freezers Software ? Images from different stained tissue after second surgery Drobo > DVD backups Contextual data Paper lab notebook (lab, PI’s office), surgical log (with animal) SDMP #3 Storage, Backup, Security
    22. 22. Lamar Soutter Library UMMS Case B Analysis using Simplified Data Management Plan 1. Types of data: Images of heart, LVP measurements, histology slides (tissues), images of slides, software 2. Contextual details (metadata) needed to make data meaningful to others: • experiment # • dates of experimental activities • stem cell line • details about animal (species, age, identifier) • area of infarct • area where stem cells implanted •type of stain used • instrumentation 3. Storage, Backup, and Security: •Hard drive of acquisition computer (initial) •Drobo •networked hard drive (backed up by institution) • DVDs • Slide boxes in freezers
    23. 23. Lamar Soutter Library UMMS 3. (continued): •Lab notebooks/animal surgical logs (some backup when data is transcribed from animal surgical log to paper lab notebook) 4.Provisions for Protection/Privacy: •Files are not password protected •Paper lab notebooks are kept in lab/older ones in PI’s office (key card access to these rooms) 5.Policies for re-use: •Not addressed –need to ask researcher (possiblities: reuse with permission of PI, institutional policies) 6.Policies for access and sharing: •Not addressed—need to ask researcher (possibilities: PI will make accessible after paper publication, will share them immediately, may depend on funding agency reqs. Case B Analysis using Simplified Data Management Plan
    24. 24. Lamar Soutter Library UMMS 7. Plan for archiving and preservation of access • Not addressed—ask researcher (possibilities: convert files in proprietary formats to generic formats, appraisal of data and data versions, decision on where data should be archived (IR or DR) Case B Analysis using Simplified Data Management Plan
    25. 25. Phase III: Piloting • UMMS CTSA Pilot Summer 2013 • Piloting Partners: Oregon State, Tufts, University of Tennessee, VCU, Colorado State • Looking for additional partners • Looking to add cases to curriculum • Expand RDM educational community Lamar Soutter Library UMMS
    26. 26. Train-The-Trainer • Webinar 10/31 on Module 1: Overview of Research Data Management and writing data management plans • On-site Professional Development Day 11/8: Regional Data Management Education Course: How to Teach RDM Using the New England Collaborative Data Management Curriculum Lamar Soutter Library UMMS
    27. 27. Educating Next Gen-Librarians • Partnered with Simmons College Graduate School of Library and Information Sciences • 15-week course covering librarian roles in research data management • Students conduct data interviews with researchers, develop teaching cases, and write data management plans Lamar Soutter Library UMMS
    28. 28. 532G-01 Scientific Data Management • Students learn from researchers’ cases • Scientists share workflows and their data management practices, challenges • Data Management Plans (DMPs) • Data repositories, Open Science, Open Data • Annotating data sets • Preserving and archiving data • Developing library data services and data policies • Research Informationists Lamar Soutter Library UMMS
    29. 29. Phase IV: Evaluation Challenges • Different Modes of Teaching • Different Modules • Different Cases • Different Audiences • Different Instructors • Different Locations • Different Institutions …Focus on the content and its usefulness Lamar Soutter Library UMMS
    30. 30. References Lamar Soutter Library UMMS Gaudette, G. R. 2011. “Keeping a lab notebook in the Gaudette lab.” Unpublished. Gaudette, G. R. 2012. “Data management in biomedical engineering: needs and implementation.” Power point presentation. University of Massachusetts Medical School, Shrewsbury, MA 4 April 2012. http://escholarship.umassmed.edu/escience_symposium/2012/program/9/ Gaudette, G.R. and Kafel, D. 2013. “ A case study: data management in biomedical engineering.” Journal of eScience Librarianship: 1(3): 159- 172. http://dx.doi.org/10.7191/jeslib.2012.1027 University of Massachusetts and WPI (2011). Frameworks for a Data Management Curriculum. University of Massachusetts. http://library.umassmed.edu/imls_grant
    31. 31. For More Information….. Contact: Elaine R. Martin, DA Director of Library Services Lamar Soutter Library University of Massachusetts Medical School Elaine.Martin@umassmed.edu Lamar Soutter Library UMMS

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