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Expressivity vs. Uniformity – social tagging and controlled vocabularies – ASIST Panel

In an immediate follow-up to last week’s panel… here’s another.

What: EXPRESSIVITY VS. UNIFORMITY: Are controlled vocabularies dead, and if not, should they be?
When: 1:00 to 2:00pm April 2nd, 2007
Where: Pleasants Family Room in Wilson Library at UNC-CH
Who: Led by Dr. Stephanie Haas, with panelists Dr. Gary Marchionini, Terrell Russell, Tim Shearer, Christiane Voisin, and Lynn Whitener
Presented by: ASIS&T-UNC

Controlled vocabularies, nomenclatures, LC or MeSH subject headings have a long history in LIS. They make classification, categorization, aggregation, sorting, and other operations easier. But with the rise of folksonomy, recommendors, improved natural language processing techniques and other technologies, are they needed any more, or are they just stifling the creativity of our expression?

This panel was on Monday and the week’s flown by since. I wanted to post my comments and see if any extra controversy could be kicked up after the fact.

For the most part – we didn’t disagree very much. The two (social tagging and controlled vocabularies) seem like different ends of a spectrum and should be able to work together… we’re only at the beginning and we need better tools.

Here’s what I said:

I think nuance and a spectra of understanding are too hard for most people for most things. People want clean lines – they want black and white. If it’s beyond my area of interest or expertise – just give me the answer already! So I think there will always be a place for controlled vocabularies wrought by experts and combed over time. People want the ‘right’ answer.

It’s a simple (read: impossibly complex) question of how high the bar of ‘good enough’ needs to be. And it’s different for every information problem. Each person looking for information has their own biases, their own history, their own level of expertise and will use different words/queries accordingly. As they continue their search, they will, themselves, become more sophisticated and use more in-group or official terminology. That doesn’t make any of the words they used to get that far, incorrect. It just means that all valid paths to the ‘right’ information are valuable.

Likewise, we know that there’s value in having a fixed set of words – for aggregation and analysis, as well as the sense that you’re getting everything the database has to offer.

However, I think we’re entering a new time where many more voices are being heard and recorded – and through all this noise and messiness, we’ll still be able to extract a remarkable order.

What’s up for debate is how dumb that order will look and how much information it will actually provide… Will it truly be the lowest common denominator? I think Gary’s right in that the vast majority of information objects are not worthy of our human attention/time. We’ve got automatic classification, fulltext retrieval, etc. As we move forward, there’s just too much of it. We need to focus our attention on the things that deserve our human attention.

These computers, they’re very good at counting things, you know…

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