Developing Data Literacy Competencies to Enhance Faculty Collaborations

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Developing Data Literacy Competencies to Enhance Faculty Collaborations (Don MacMillan, University of Calgary, Canada). This presentation was one of the 10 most highly ranked at LIBER's Annual Conference 2014 in Riga, Latvia. Learn more: www.libereurope.eu

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  • 1. Developing data literacy competenciesto enhance faculty collaborationsDon MacMillanLiaison Librarian, Biological Sciences, Physics,Astronomy & MathematicsUniversity of CalgaryCalgary, Canada

2. LIBER 2014-Riga 2 3. LIBER 2014-Riga 3 4. CollaborationReinvent information literacy (IL) program integrate genetics & biochemistry contentCourse-integrated library/lab project Biology311 (October) - Biochemistry 393 (February)Investigate the molecular & structural basis ofinherited diseases using disciplinary data550 students per class24 lab sections10 IL workshops in library classroomsLIBER 2014-Riga 4 5. Why Data Literacy?Data-intensive disciplines robustinfrastructure - unique research outcomesBioinformatics tools facilitates discovery &analysis of life sciences dataStudents conduct research using real-worldsolutions using domain repositoriesLibrarian re-skilling enhance our datacompetencies, domain expertise & relevanceLIBER 2014-Riga 3 6. BioinformaticsTools for collection & analysis of complex biological dataIntegrationLIBER 2014-Riga 6InformationLiteracyGeneticsBIOL311GenesBiochemistryBCEM393Proteins 7. Bioinformatics InteroperabilityGeneticsPubMed(Scholarly Literature)OMIM(Database of geneticdiseases)Gene (Nucleotidesequences)BiochemistryProtein Data Bank(Protein Structure)UniProt (ProteinSequence/Function)BLAST & ClustlW(Sequence similarity &Alignment)PyMOL(3D Visualization)LIBER 2014-Riga 7 8. Sample QuestionsGenetics(October)Which chromosomeis your selected genelocated?Obtain data on genestructure, mRNA andprotein lengthBiochemistry(February)Locate your Proteins3D coordinatesWhat effect does amutation have onprotein structure &functionLIBER 2014-Riga 8 9. Gene Data ExampleNCBIs Gene portal links to gene & protein data and PubMed(e.g. Cystic fibrosis = CFTR Gene)LIBER 2014-Riga 9 10. Protein Data ExampleProtein Data Bank (PDB) Repository of 3Dprotein structural data portal to PubMed andrelated data sourcesLIBER 2014-Riga 10 11. PyMOLThree-dimensional (3D) molecularvisualization systemStudents introduce mutations to study impact onprotein structure, function & related diseases(e.g. KRAS mutation causes certain types ofcancer)LIBER 2014-Riga 11 12. Implications for LibrariesData competencies inform domain expertiseandvice versaAlign library activities with faculty needs, datalife cycle, (Jaguszewski & Williams 2013)Librarians need to offer moreexpertisevalue (Kenney (Ithaka), 2014)Collaboration & soft skills critical toleveraging expertise and expanding servicesCreated a more rigorous & sustainable ILprogramLIBER 2014-Riga 12 13. Impact on student learningInnovative learning experience for students data integrates & informs contentStudents able to find real world solutions toresearch questionsStudents will be able to manage and analyzetheir data more efficientlyPeer-reviewed presentations demonstratedeeper understanding of subjectsLIBER 2014-Riga 13 14. Best PracticesMust be course-integrated worth %Develop sequential steps simple tocomplexStudents learn best by doing allowhands-on interactivity & flexibilityTailor relevant data sources to specificquestionsAdvantageous to have consistent deliveryto all lab sectionsLIBER 2014-Riga 14 15. Assessmentn Students prepare poster & presentation (mark and peers)n Peer-Review Marking Rubricn TooFast (Free Assessment Summary Tool)https://www.toofast.ca/LIBER 2014-Riga 15 16. Student feedbackn It was good that we were able to use things that we learned in BIOL311 to understand things in BCEM 393. I think that I learned morebecause I could see how labs and topics in the two courses related toeach othern I liked how the library and computer labs were hands-on. The TAsand library people were there to help us and not just tell us what todo. I think it was more fun and we got more out of it by doing thingson our own instead of following a step-by-step recipe in the labmanualn The presentations gave me the chance to learn many valuable skills.I liked picking the disease to study and doing the project with apartner. I also liked hearing about how other groups went aboutdoing their projects in different waysLIBER 2014-Riga 16 17. Thank You Paldies!Don MacMillanLiaison Librarian, Biological Sciences, Physics, Astronomy &MathematicsUniversity of CalgaryCalgary, Canadamacmilld@ucalgary.caLIBER 2014-Riga 17 18. Bibliographyn Jaguszewski, J.M., Williams, K. (2013). New Roles for New Times: TransformingLiaison Roles in Research Libraries. Association of Research Libraries. Retrievedfrom http://www.arl.org/storage/documents/publications/NRNT-Liaison-Roles-final.pdfn Kenney, A.R. (2014) Leveraging the Liaison model: From Defining 21st CenturyResearch Libraries to Implementing 21st Century Research Universities. Ithaka S+R.Retrieved fromhttp://www.sr.ithaka.org/sites/default/files/files/SR_BriefingPaper_Kenney_20140322.pdfLIBER 2014-Riga 18 19. Resourcesn NCBIhttp://www.ncbi.nlm.nih.gov/n OMIMhttp://www.ncbi.nlm.nih.gov/omimn Protein Data Bankhttp://www.rcsb.org/pdb/home/home.don UniProthttp://www.uniprot.org/n PyMOLhttp://www.pymol.org/LIBER 2014-Riga 19

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