I really enjoyed London Online this year. A perfect overlap of my current paid work interests – CMSs and publisher solutions – and my academic interests – taxonomies (software and content) and records management. It was great to say hello to Squiz and see them doing so well – we contracted them to set up an open source CMS-driven website that is working splendidly for us. I was fascinated by VWI-media‘s taxonomy based -solution to managing RSS feeds and enjoyed hearing about semantic search and classification techniques, like those offered by Endeca. I also talked to some interesting people from Lexis Nexis and the IMF!
I have started a collection of acronmys and abbreviations. These are mainly to do with Records Management.
CMS – Content Management System; Content Management Software
DRM – Digital Rights Management
ECM – Enterprise Content Management
EDM – Electronic Document Management
EDRM – Electronic Document and Records Management
ERMS – Electronic Records Management Strategy
IM – Information Management
KM – Knowledge Management
PDM – Product Data Management
RM – Records Management
Edited by Alan Gilchrist and Barry Mahon (Facet; 2004). There were a couple of chapters on taxonomies. The book provides a very easy to read selection of essays from industry practitioners covering a range of IA themes. Problems for multinational taxonomies included the differences in English language usage and company structure between US and European companies.
In arguing for investment in IA, (page 196) “reducing search time and frustration, enhancing knowledge sharing, are goals whose performance can be measured. Reducing the risk of litigation or of losing customers may also be used as sound arguments.”
Here’s a handy definition of a corporate taxonomy, from TFPL:
“TFPL takes the view that a ‘corporate taxonomy’ can be viewed as an enterprise-wide master file of the vocabularies and their structures, used or for use, across the enterprise, and from which specific tools may be derived for various purposes, of which navigation and search support are the most prominent.”
I found this to be a useful article on usability issues.30 Usability Issues To Be Aware Of | Know-How | Smashing Magazine
There is a handy glossary and a lot of comments. I particularly liked the way you can assign meaning by juxtaposition. I come across this all the time in text and it’s interesting to see it works just as well – if not better – purely visually.
I’ve recently had fascinating conversations with two professional taxonomists – one at EDS and one at the BBC – and both use very different but imaginative and innovative combinations of folksonomic and traditional taxonomic procedures.
All the best taxonomists advocate consulting as much as possible with your users, which is obvious, and a folksonomy is pretty much a glorified mass user consultation exercise. But why stop with the consultation stage?
You still get an awful lot of noise to your signal in folksonomies and the best way to clear that is still to apply some trained thoughtful evaluation – the principles of taxonomy. The combined approach gives you the best of both worlds – gather the tags as a folksonomy (you still need a critical mass of taggers), and then do a bit of pruning and tidying to make them work properly. Ideal!
This was a dinky little podcast on
A fairly light and simple introduction but with a couple of good examples.
I particularly liked the description of information architecture as the art of digital librarianship.
First person: ‘Folksonomy’ takes power from expert librarians, an article by David Bowen of Bowen Craggs & Co in the Financial Times‘s Digital Business section on November 7th highlights some of the advantages of having a well-crafted carefully structured taxonomy instead of relying on folksonomies. He says that folksonomies are great in some cases, but that really valuable information is by definition specialised and therefore doesn’t get read by enough people for mass social tagging to be helpful.
I think there are two key limitations to the usefulness of the folksonomic approach. Firstly, you need loads of people. If you don’t have a huge number of people actively tagging – and only huge mass market websites do – you don’t generate a large enough data set to get a decent signal-to-noise ratio. Secondly, it has to be of no consequence if chunks of your content are never found due to weird or bad tagging. This is fine for Flickr, say, where people just want any old picture, not to see all the pictures. It’s not so great if you want to make sure you have checked every one – that you’ve looked at all the relevant legislation, for example, not just the first couple of laws that happened to pop up.
I went to the ISKO UK conference Ranganathan Revisited on Monday sponsored by Factiva, which was very interesting indeed. There were 5 presentations – two on classification theory, a fascinating insight into how Factiva sort and output the thousands of news reports they process every day, an introduction to a very interesting new meta-analysis energy portal for monitoring trends in reporting, and a demonstration of Aduna’s Autofocus software that gives a visual representation of searches. One of the interesting and perennial themes that came up in conversations was the difference in approach of computer scientists from people with an information and library skills background. Some people seem to think of this as a battleground, but I like to think the best ideas emerge at the confluence of different paths.
No taxonomy blog would be complete without a link to this:
Understanding information taxonomy helps build better apps.
It seems to be the article that everyone comes back to (or starts off with). A clear and simple explanation of how taxonomies form the backbone of most information architecture. I also noted a couple of good points about how the semantic web won’t run without them – a topic I intend to return to!