Monday, March 30, 2009

Solving organisation underload: rethinking scholarly communications to add new conceptual value

"Open Access is going now," says Jan Velterop. "So I feel I can talk about something else - Beyond Open Access." That 'something' is organisation underload.

Too much of our data is too deeply hidden - we struggle to get the most out of it. Jan suggests the problem is not information overload but 'organisation underload'; a lack of organisational conceptual structures to manage all this information. The information overload aspect is going to increase; think expanding communication mechanisms e.g. blogs, peer-reviewed wikis - and why, says Jan, are these not being initiated by publishers?

He uses water as an analogy for information. When there's just a bit, we take it in (we drink it). When there's too much, we have to devise a means to navigate it - a boat. We need to find ways of presenting knowledge that helps us to do something useful and immediate with it. This means not just publishing articles but creating visualisations of conceptually connected data - "this is where the future lies". And as the communications process changes, we will need to think again about what skills and workflows are required to manage it.

As scientists we have traditionally focussed on the detail; now we complement this with a step back to see the bigger picture of how things are connected. This isn't feasible in the traditional manner of ingesting research, but it's this lateral thinking that produces breakthroughs (revealing new conceptual connections).

Jan talks about Knewco's software that mines data for concepts rather than simply words, and (I paraphrase, but I think the essence is that it) breaks the data down into triples that codify the relationships between lots of different pieces of data. Mapping these connections can reveal a powerful picture but once you scale this to millions of triples there will be redundancy that needs to be removed in order to focus on the valuable connections. This kind of semantic data analysis and mapping can make scientific literature even more useful by helping users find new, valuable sources of information - using the connections between literature to support new browse options in library catalogues and publisher websites.

[I have not done Jan's paper justice and would urge you to check out the wealth of additional interesting comments rippling around the Twittersphere (#UKSG09) - and must acknowledge that if I have managed to grasp his thesis at all it is because this is almost exactly what powers Publishing Technology's pub2web platform, which I have spent a good long time getting my head round!]

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