The Mars Phoenix landing has got a lot of coverage around the web, particularly from some misty eyed old blokes who remember watching landings via the Mosaic browser in an earlier, simpler age. The landing is cool, but one thing I thought was particularly clever was the use of Twitter by JPL to publicise the landing and what is happening on a minute to minute basis. Now my suspicion is that they haven’t actually installed Twhirl on the Phoenix Lander and that there is actually a person at JPL writing …

How do we actually create the service that will deliver on the promise of the internet to enable collaborations to form as and where needed, to increase the speed at which we do science by enabling us to make the right contacts at the right times, and critically; how do we create the critical mass needed to actually make it happen? In another example of blog based morphic resonance there has been a discussion a discussion over at Nature Networks on how to enable collaboration occurred almost at the same …

Image via Wikipedia
There have been a number of interesting discussions going on in the blogosphere recently about radically different ways of practising science. Pawel Szczesny has blogged about his plans for freelancing science as a way of moving out of the rigid career structure that drives conventional academic science. Deepak Singh has blogged a number of times about ‘bursty science‘, the idea that projects can be rapidly executed by distributing them amongst a number of people, each with the capacity to undertake a small part of the project.

As I mentioned a couple of weeks or so ago I’ve been playing around with Friendfeed. This is a ‘lifestreaming’ web service which allows you to aggregate ‘all’ of the content you are generating on the web into one place (see here for mine). This is interesting from my perspective because it maps well onto our ideas about generating multiple data streams from a research lab. This raw data then needs to be pulled together and turned into some sort of narrative description of what happened.

This started out as a comment on Peter Murray-Rust’s response to my post and grew to the point where it seemed to warrant its own post. We need a better medium (or perhaps a semantic markup framework for Blogs?) in which to capture discussions like this, but that’s a problem for another day…

‘No data model survives contact with reality’ – Me, Cosener’s House Workshop 29 February 2008
This flippant comment was in response to (I think) Paolo Missier asking me ‘what the data model is’ for our experiments. We were talking about how we might automate various parts of the blog system but the point I was making was that we can’t have a data model with any degree of specificity because we very quickly find the situation where they don’t fit. However, having spent some time thinking about machine readability and the …

More followup on feeds. I’ve set up a friendfeed which is available here. Amongst other things I’ve been trying to aggregate my comments on other people’s blogs. The way I am doing this is creating a tag in Google Reader which I have made public. When I leave a comment I try to subscribe to a comment feed for that Blog, I then tag it as ‘Comments feed’ which aggregates and makes it public as an RSS feed. I then suck that feed through yahoo pipes to find all the …

Following on from (but unrelated to) my post last week about feed tools we have two posts, one from Deepak Singh, and one from Neil Saunders, both talking about ‘friend feeds’ or ‘lifestreams’. The idea here is of aggregating all the content you are generating (or is being generated about you?) into one place. There are a couple of these about but the main ones seem to be Friendfeed and Profiliac. See Deepaks’s post (or indeed his Friendfeed) for details of the conversations that can come out of these type …

Two things last week gave me more cause to think a bit harder about the RSS feeds from our LaBLog and how we can use them. First, when I gave my talk at UKOLN I made a throwaway comment about search and aggregation. I was arguing that the real benefits of open practice would come when we can use other people’s filters and aggregation tools to easily access the science that we ought to be seeing. Google searching for a specific thing isn’t enough. We need to have an aggregated …