Pandora Pandemic – Scatter/Gather – the value of a robust taxonomy for serving up music people want to hear. The Music Genome Project is paying dividends for Pandora – the iPhone “radio station”.
Pandora Pandemic – Scatter/Gather – the value of a robust taxonomy for serving up music people want to hear. The Music Genome Project is paying dividends for Pandora – the iPhone “radio station”.
July 2009 Metadata Maturity Survey Findings | Earley & Associates – good to see that metadata really does help!
I’ve given the conference a whole page as there were so many fascinating presentations. The conference website has all the proceedings: papers, abstracts, slides, etc., so my write-up is just some of my personal observations. There were two tracks, so I didn’t hear every presentation.
I would like to thank everyone who looked at my poster and for all your support and kind comments.
Do tags work? is a detailed informal study of tagging on flickr, via Taxonomy Watch: Tags – Not so Useful.
In Beyond retrieval: A proposal to expand the design space of classification, Melanie Feinberg argues that classifications are not just about efficient retrieval, but about mapping a conceptual space as an active part of problem-solving or design.
A classification highlights connections and contrasts, and fuzzy boundaries, so seems to me to be an obvious tool to help analysis. Comparing different classifications can also illustrate different aspects of an idea or domain. I am very used to the principle of building classifications, seeing how things fit, looking at the things that don’t fit, throwing the classification away, and starting again. You always learn a lot about the topic you are working with in the process.
There seem to be a lot of classifications in Human-Computer Interaction that are used as checklists (things like the DECIDE framework), rather than retrieval tools. It strikes me that library classifications are the special case, rather than “checklist classifications”, which are very common. But then that is just a question of how you classify classifications.
I went to the ISKO event on Thursday. The speaker, Dave Snowden of Cognitive Edge was very entertaining. He has already blogged about the lecture himself.
He pointed out that humans are great at pattern recognition (“intuition is compressed experience”) and are great satisficers (computers are great at optimising), and that humans never read or remember the same word in quite the same way (has anyone told Autonomy this?). I suppose this is the accretion of personal context and experience affecting your own understanding of the word. I remember as a child forming very strong associations with names of people I liked or disliked – if I disliked the person, I thought the name itself was horrible. This is clearly a dangerous process (and one I hope I have grown out of!) but presumably is part of the way people end up with all sorts of irrational prejudices and also explains why “reclaiming” words like “queer” eventually works. If you keep imposing new contexts on a word, those contexts will come to dominate. This factors into taxonomy work, as it explains the intensity people feel about how things should be named, but they won’t all agree. It must also be connected to why language evolves (and how outdated taxonomies start to cause rather than solve problems – like Wittgenstein’s gods becoming devils).
Snowden also talked about the importance of recognising the weak signal, and has developed a research method based on analysing narratives, using a “light touch” categorisation (to preserve fuzzy boundaries) and allowing people to categorise their own stories. He then plots the points collected from the stories to show the “cultural landscape”. If this is done repeatedly, the “landscapes” can be compared to see if anything is changing. He stressed that his methodology required the selection of the right level of detail in the narratives collected, disintermediation (letting people speak in their own words and categorise in their own way within the constraints), and distributed cognition.
I particularly liked his point that when people self-index and self-title they tend to use words that don’t occur in the text, which is a serious problem for semantic analysis algorithms (although I would comment that third party human indexers/editors will use words not in the text too – “aboutness” is a big problem!). He was also very concerned that computer scientists are not taught to see computers as tools for supporting symbiosis with humans, but as black box systems that should operate autonomously. I completely agree – as is probably quite obvious from many of my previous blog posts – get the computers to do the heavy lifting to free up the humans to sort out the anomalies, make the intuitive leaps, and be creative.
UPDATE: Here’s an excellent post on this talk from Open Intelligence.
People ask me what I think about folksonomies from time to time and now I can direct them to this article which I was delighted to write for the very useful FUMSI (Find, Use, Manage, Share Information).
IPTC Web‘s free-to-use taxonomies for news, including categorisations for images.
A reading list from controlledvocabulary.com. “David Riecks founded ControlledVocabulary.com as a resource to help others learn how best to build controlled vocabulary lists, thesauri, and keyword hierarchies for describing images in databases. He has been involved in many recent standards initiatives as well as being a featured speaker at industry events such as PhotoPlus Expo, the Microsoft Pro Photo Summit, and the first and second International PhotoMetadata Conferences.”
The FT reports that the Local Government Association has banned use of the word “taxonomy” in public documents! “Other words recommended for omission from public documents include “benchmarking”, “place shaping” and “taxonomy”.”
I know the General Public think it’s all about stuffed animals, but to classify taxonomy with “beaconicity” and “coterminious” just adds insult to injury!