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From information to data, and back again

From information to data, and back again. Laine Ruus University of Toronto.Data Library Service 2009-03-13. Overview. The DIKW model and where libraries fit Where data have been (and are still) Data and the reference librarian. The DIKW model. Wisdom Knowledge Information Data.

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From information to data, and back again

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  1. From information to data, and back again LaineRuus University of Toronto.Data Library Service 2009-03-13

  2. Overview • The DIKW model and where libraries fit • Where data have been (and are still) • Data and the reference librarian

  3. The DIKW model Wisdom Knowledge Information Data

  4. Library systems are… • Set up, resourced and trained to locate information that exists • Not set up, resourced or trained to generate information that does not yet exist

  5. Data have been around for a long time • Population census • Public opinion polls, social surveys since early 1900s

  6. …and they have been hiding in… • Early data archives (1940s and on) in local academically-based survey institutions and data archives • Later, national data archives, esp in Europe • 1957 Lucci et al report, suggested libraries as appropriate organizations in which to situate data services • At UBC, Jean LaPonce, 1972, like Columbia/EDS, one of first with Library involvement • in USA, ca 42% of academic services in libraries

  7. North American model • Puts user services close to users, but not close enough; data services usually a discrete entity • Possibility of a quantitative answer should be part of every reference interview • Now possible – convergence of Inet, DDI metadata standard, and rise of 3rd generation interfaces to microdata: SDA, Nesstar, VDC

  8. Requires a new set of skills • The hardware and software are now available to support generation of descriptive and inferential statistics from raw microdata at the reference desk • Requires: • Numeracy: how to interpret statistics • Knowledge how and by whom data are collected • Knowledge how data become statistics

  9. Time to take up Lucci et al challenge • Only data management needs to be a discrete entity • Quantitative reference services should be part of every reference tool basket

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