1 / 9

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.

fergal
Download Presentation

From information to data, and back again

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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,since 1600-1700s Public opinion polls, since early 1900s 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, one of first with Library involvement, like Columbia/EDS, 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

More Related