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Collaborative Data Mark-up & Distribution

Presented at CASRAI 2013: Reconnect Big Data.

Appreciation to Amber Leahey, the metadata librarian at Scholars Portal, whose 2012 iASSIST slides were very useful in putting this together.

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Collaborative Data Mark-up & Distribution

  1. 1. Collaborative Data Mark-up & Distribution Jacqueline Whyte Appleby Scholars Portal October 17, 2013 CASRAI
  2. 2. Ontario Data Documentation, Extraction Service, and Infrastructure
  3. 3. <odesi> • An online data research tool developed between 2007 and 2009 • Jointly funded by the Ontario Council of University Libraries (OCUL) and OntarioBuys • Developed to serve the Ontario university community, now expanding beyond the province
  4. 4. <odesi> in context is managed by which is a service of which is governed by 21 Ontario university libraries
  5. 5. <odesi> goals • Facilitate discovery, downloading, and analysis of data products • Create a tool that is useful to both experienced and new researchers
  6. 6. <odesi>: where does the content come from? Confidential Microdata available through the RDC Statistics Canada (data producers) Public Use Microdata Files (PUMFs) available through the DLI Other public products available through
  7. 7. <odesi> : where does the content come from? ICPSR metadata Public Use Microdata Files (PUMFs) Available through the DLI Canadian Gallup Polls data Other public products Available through Canadian Opinion Research Archive (CORA) data
  8. 8. <odesi>: the catalogue
  9. 9. <odesi>: the repository
  10. 10. <odesi> in use Broad questions: • “I want to write a paper on women in the workforce…”
  11. 11. <odesi> in use Broad questions: • “I’m interested in exploring on-reserve housing issues.”
  12. 12. <odesi> in use Testing a hypothesis • “How many Ontarians smoke today compared with 10 years ago?”
  13. 13. <odesi> in use Testing a hypothesis • “How many Ontarians smoke today compared with 50 years ago?”
  14. 14. <odesi> highlights • Metadata is bilingual and DDI-compliant • Don’t need statistical software to run many analyses • Surveys also include all supplementary material • New surveys added daily
  15. 15. MarkIt! program • OCUL members (usually data librarians) apply for funding • Funds pay for student employees, who are trained to mark up surveys using DDI 2 standards • 2013-2014: Carleton, U of Ottawa, Queen’s and McMaster are participating, as well as Scholars Portal
  16. 16. MarkIt! program
  17. 17. MarkIt! program best practices • Be flexible; always be ready to shift priorities • Establish best practices and adhere to them • Make QA and editing each others’ work the norm (35% of datasets are marked up at more than one school)
  18. 18. MarkIt! Program expansion?
  19. 19. Next up: Geospatial metadata?
  20. 20. Next up: Dataverse support?
  21. 21. Next up: Dataverse support?
  22. 22. Next up: Dataverse support?
  23. 23. Thank you!