The talk was entitled ‘The Web of Human Experience’: I spent a lot of my doctorate looking at User Experience issues, so this was always going to interest me
Enric was interested in the reuse of other people’s experiences in the context of ‘case-based reasoning’ (learning from experience). Examples of relevant experiences include: a restaurant review; a music playlist; a ‘how to’ guide. The web is a good platform for sharing this kind of content, of course, but he felt that despite the a wealth of experience online, it isn’t modelled explicitly on the web. Additionally, we don’t necessarily understand how people browse, filter and use results.
Queries are, of course, deeply context-dependent: the answer to the question “Which are Barcelona’s airports?” depends on your purpose and community of practice — do you want to know about the tiny budget airport that’s miles out of town?
Similarly, queries such as “Which hotels in London have a room on these dates?” need different results depending on context: a business traveller is probably interested in the availability of wifi, while a family planning their vacation may be more interested in proximity to attractions and friendliness of staff. (I was a little surprised he didn’t touch on software agents as a possible approach here.)
He also spoke about implicit knowledge, which caught my attention as it links with my previous work. I think his meaning was different to my own, though: I believe that by ‘implicit knowledge’ he meant knowledge embedded within a community, knowledge that only becomes explicit when multiple people share their indvidual insights.
So, if people constantly trawl the web in search of people’s experiences solving given problems, how can we represent, organise and reuse such content? I don’t think this is a universal problem: for instance, sites such as Tripadvisor provide pretty decent structures as a starting point when planning one’s travels. On the other hand, there really is a lot of unstructured information out there… maybe I need a software agent after all.