When I worked at Penguin Books in the 1990s, I was fortunate to work with an inspirational person whose job it was (from a darkened office deep in London W8) to manage the publishers’ full fiction and non-fiction stocklists. These chunky A4 booklets were printed on a monthly basis and needed to take into account every single available title and its current price as well as available stockpacks and gift-sets.
Although Penguin had a robust in-house stock management IT system, the entire list of books published by Penguin, Puffin and partner publishers like Rough Guides, needed to be translated into meaningful sections and categories via the Penguin Stocklist. This allowed staff in bookshops over the world to find information about the book they needed, and to order it. This was well before you could just ‘look it up’ online. Amazon was still four or five years off its first online offerings.
This was pre-digital, the days of using Tippex for correcting typing mistakes, of relying on mammoth chuntering photocopiers to distribute information, and let’s be clear – golfball typewriters were only just being hauled out of office buildings to die peacefully and heavily somewhere (where did they all go?). Email was for early-adopters only, internal memos still rushing around buildings and to warehouses carried in mail trolleys and vans.
The point is that this one person had an encyclopedic knowledge of Penguin’s back catalogue, which was added to by maybe 150+ titles each month, and yet she knew by heart most of the author’s names and titles. I knew quite a few individual book numbers (ISBNs) myself but nothing could match the details held in Lorna’s head or the accuracy of each of these monthly stocklists. Mistakes were quite unheard of (and unlike today, would have been spotted by similarly obsessive and eagle-eyed book retailers).
The reams of available titles were made sense of by careful categorisation and rolling audits.
These days information management techniques such as this have changed beyond recognition. We expect to see in milliseconds every available image or text around a particular keyword or phrase. Categories went out of fashion when search wowed us.
But now we are shifting from Web 2.0 to Web 3.0, and with a great amount of information just useless noise, the curation of relevant content (‘people tagging things as they publish’) has become hot again via blogs and Twitter hashtags. Tagging helps us promote our stuff, and helps others find what they want, and parcels stuff off for ‘personalisation’ of content in the future.
Online content needs to be categorised to enable syndication, to ensure it is findable and can be connected with other similar content. There is geeky excitement over shared and open data whereby content ‘knows about itself’ for want of a better way of describing it – and can syndicate itself in more ways than originally envisaged. You can imagine lots of scenarios, many of which are happening already in comparison sites, one-stop travel shops etc.
Microformats* already help content editors indicate the type of information pages hold (such as address data or authorship data or event data), allowing the potential for mashups with data on other sites. You only have to look at content aggregated around maps for instance, or Google ‘at a glance’ section regarding local information, to see this kind of ‘machine-readable knowledge’ in action.
What do you use categories for? Anyone who has a blog will know about blog categories for sure. What about Twitter lists – do you create these to help with information overload?
I have lost touch with Lorna T. – the indefatigable Penguin Stocklist guru – but if you’re out there please get in touch if you find this post!
“Microformats are a way of adding simple markup to human-readable data items such as events, contact details or locations, on web pages, so that the information in them can be extracted by software and indexed, searched for, saved, cross-referenced or combined.”
photo credit: Hello Typewriter blog http://hellotypewriter.tumblr.com/
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