Best of both worlds

A folksonomy is an information retreival tool created by allowing users to 'tag' information resources with whatever words they want to remember them by.

The folksonomy approach is very different from the controlled vocabulary approach (taxonomies, classifications, thesauri, ontologies).  The debate between advocates of the two approaches has, unsuprisingly, been polarised.

For the views of people on both sides of the debate see Clay Shirky's Ontology is overrated  and the robust response of Peter Merholz  Clay Shirky's viewpoints are overrated

The Librarians Guide to Etiquette has put a humorous spin on this polarisation.  It told librarians that they could induce panic into their library committees by making  the following suggestion:

''What if we eliminated the use of costly Library of Congress Subject headings in favour of patron-initiated tagging and social bookmarking in our catalogue?''

The Penn Tags project at the Library of the University of Pennsylvania (Penn) gives an interesting way out of this divide.   The library is allowing their users to add their own tags to catalogue entries, and thus generate their own reading lists.

The result is that searchers have two new ways into the catalogue:  as well as the classification and search routes offered by the catalogue itself you now can search on:

• the words that fellow readers have tagged catalogue entries with
• the reading lists of fellow readers, students or lecturers.

This combination of classification and folksonomy could have powerful applications within organisations.   We do need classification structures in our intranets and record systems.  But folksonomies are good at two things that classifications are not good at, namely:

• coping with the diversity of language used by different people in the organisation
• incorporating emerging subjects and new areas of interest

At Penn library the tags that users apply to catalogue entries will have a similar relationship to classification terms in the catalogue as do non-preffered terms to preffered terms in a thesaurus.  They will link the language(s) that people actually use in the University to the necessarily artificial language of the classification.

And when new topics emerge that are of interest to people in the University, these topics will be reflected in the words that students and lecturers use when they tag those resources in the library that are relevant to that topic.