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A presentation about the strengths and limitations of taxonomies and folksonomies, with a brief history of library automation thrown in for good measure.
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defraggingtaxonomies and
folksonomies
Karen G. SchneiderCollege Center for Library
AutomationTallahassee, Florida
Circ, Holdings, FTE
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
Circulation 1,243,447 1,330,906 1,380,000 1,080,000 1,098,983 1,293,864 1,451,417 1,400,000 1,388,342 1,301,582
Holdings 968,268 998,446 1,029,515 1,086,402 1,116,642 1,146,127 1,210,127
FTEs 238,348 236,256 234,962 235,527 244,558 267,486 285,128 297,795 294,818 287,714
FY9697 FY9798 FY9899 FY9900 FY0001 FY0102 FY0203 FY0304 FY0405 FY0506
library use: and/and/and
a brief history of library automation
“disconnected data silos with non-usable content”
learning from taxonomies
classic problems inauthority control
spell-checkstemmingsynonymsphrases
anachronisms
disambiguation
topic depth (faceting/subdivisions)
lessons from folksonomies
don’t scare off your workforce
in the short term,satisficing trumps
perfecting
In 2006, 400 catalogers at the Library of Congress
cataloged 350,000 “volumes.”
That’s 1,400 records per workday, or 3.5 records
per person, per day.
Tagging is about (re)discovery and (re)use,
not (just) description
Tagging is about building data, not records
folksonomies grow good metadata
90% of Flickr content falls into 6 different types of
facets:
place (40% of tags), events, dates, people,
things/animals, color
Useless critiques of folksonomies
problems commonto taxonomies and
folksonomies
tags * time = crud
scalability (onesies vs. noise)
uber-folksonomies
librarians’delicious collections
CanadianAssumption College
California Law
incentivizing uberization:
handprints and mirrors
AIM/email: [email protected]
twitter: kgsfacebook: K.G. Schneider
doppler: freerangelibrarianblog: freerangelibrarian.com
WorldCat Identity: http://orlabs.oclc.org/Identities/lccn-
n95-110807
![Tag Relatedness in Image Folksonomies · folksonomies. According to the degree of user collaboration, folksonomies are classified in two main categories: broad and narrow [1]. In](https://img.dokumen.tips/doc/110x75/60508dfb391e7c39bf133dec/tag-relatedness-in-image-folksonomies-folksonomies-according-to-the-degree-of-user.jpg)
