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Taking the Pulse of our Members: Creating a Healthy Data Services Environment

Taking the Pulse of our Members: Creating a Healthy Data Services Environment. Wendy Watkins Carleton University Michel Seguin Statistics Canada. Outline. Structure of DLI Survey objectives Highlights National Regional Regional differences Comforts and discomforts Comfort levels

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Taking the Pulse of our Members: Creating a Healthy Data Services Environment

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  1. Taking the Pulse of our Members: Creating a Healthy Data Services Environment Wendy Watkins Carleton University Michel Seguin Statistics Canada IASSIST 2009, Tampere, Finland

  2. Outline • Structure of DLI • Survey objectives • Highlights • National • Regional • Regional differences • Comforts and discomforts • Comfort levels • Discomfort levels • Rx for future development

  3. Data Centres in Canada Before DLI Closest Data Centre

  4. Data Centres in Canada After DLI

  5. Structure of Data Liberation (DLI)

  6. DLI Contacts’ Survey (2008) • Previous survey in 2001 • Wanted to look at the following aspects: • Content of the collection • Peer-to-peer training program • annual training held in each of the 4 regions • national training held in conjunction with Cdn IASSIST • travel expenses covered by DLI • Competencies in providing data services

  7. Survey Objectives • To illustrate how a census of Canadian Data Liberation (DLI) Contacts can: • assess needs of contacts in providing data services • assess the contacts’ satisfaction with DLI Central’s • services to contacts • collection • training • identify self-assessed competencies of data service providers • provide clues to refining the training program to augment competencies relevant to providing data in an academic environment

  8. Survey Highlights

  9. Average Years of Experience as DLI Contact

  10. Universities with Dedicated Data Service

  11. Data Only Minor Role in Small Institutions

  12. Uneven Mention of Data and GIS in Job Descriptions

  13. Attend Annual DLI Training? Canada Yes 86% Never 6% Atlantic Yes 75% Never 25% Quebec Yes100% Ontario Yes 80% Never 5% (1 resp) West Yes 91% Never 0%

  14. Overall Satisfaction with DLI Training (1=Not at all 5=Completely)

  15. Comforts and Discomforts • Respondents given 18 skill areas • Asked to rate competency from 1 to 5 • 1 and 2 = Very competent, somewhat competent • 4 and 5 = Not very competent, not at all competent • Combined 1 and 2 • Combined 4 and 5 • Created comfort and discomfort scales • Marked differences between regions

  16. Top 5 Comfort Levels for Canada(% Very competent and somewhat competent)

  17. Top 5 Comfort Levels for Atlantic(% Very competent and somewhat competent)

  18. Top 5 Comfort Levels for Quebec(% Very competent and somewhat competent)

  19. Top 5 Comfort Levels for Ontario(% Very competent and somewhat competent)

  20. Top 5 Comfort Levels for West(% Very competent and somewhat competent)

  21. Relative comforts

  22. Summary of Comforts • All regions fairly comfortable with the Census • Comfort levels decrease with the complexity of the data (more comfortable with aggregate data than microdata) • Atlantic contacts less comfortable than counterparts in other regions • Fewer than half feel competent outside the Census • Quebeckers most confident of abilities regarding aggregate statistics

  23. Bottom 5 Discomfort Levels for Canada(% Not very competent and not at all competent)

  24. Bottom 5 Discomfort Levels for Atlantic(% Not very competent and not at all competent)

  25. Bottom 5 Discomfort Levels for Quebec (% Not very competent and not at all competent)

  26. Bottom 5 Discomfort Levels for Ontario (% Not very competent and not at all competent)

  27. Bottom 5 Discomfort Levels for West(% Not very competent and not at all competent)

  28. Relative Discomforts“I don’t know my PUMF from my dummy variables and I’m feeling a bit synthetic”

  29. Summary of Discomforts • All regions not comfortable with • data manipulation • providing different software formats • The more complex the data, the greater the level of discomfort • DLI contacts have limited knowledge of data outside the program • Problems with statistical/data literacy appear to be because of fuzzy definitions

  30. Healthy Choices

  31. Training Implications • Different levels of service require different competencies • Develop skills in increasing levels of complexity • Provide growth opportunities for everyone • Make sure there are adequate community supports for smaller institutions • Tailor the training program so that everyone grows • Involve new people and ideas from outside regions in regional training • Explore internships, mentors, lists of experts • Work with IASSIST and CAPDU to develop national training

  32. Next Steps • DLI Education Committee meets next month (June 2009) • Review on-line resource materials • Survival Guide, Training Repository, <odesi> ,etc. • Initiate new Regional Training Coordinators • Review results of competency workshop • Develop curriculum plan to address gaps, build on strengths • Plan the next ‘Train the Trainers’ workshop for Nov. 2009

  33. Questions?

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