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 …

For my holiday project I’m reading through my old blog posts and trying to track the conversations that they were part of. What is shocking, but not surprising with a little thought, is how many of my current ideas seem to spring into being almost whole in single posts. And just how old some of those posts are. At the some time there is plenty of misunderstanding and rank naivety in there as well.
The period from 2007-10 was clearly productive and febrile. The links out from my posts point to …

If you’ve been around either myself or Deepak Singh you will almost certainly have heard the Jeff Jonas/Jon Udell soundbite: ‘Data finds data. Then people find people’. The naïve analysis of the success of consumer social networks and the weaknesses of science communication has lead to efforts that almost precisely invert the Jonas/Udell concept. In the case of most of these “Facebooks for Scientists” the idea is that people find people, and then they connect with data through those people. But what if we built social networks for data, where they could interact, find neighbours, and play games amongst themselves?

Image by cameronneylon via Flickr

This post, while only 48 hours old is somewhat outdated by these two Friendfeed discussions. This was written independently of those discussions so it seemed worth putting out in its original form rather than spending too much time rewriting.
I wrote recently about Sciencefeed, a Friendfeed like system aimed at scientists and was fairly critical. I also promised to write about what I thought a “Friendfeed for Researchers” should look like. To look at this we need to think about what Friendfeed, and other services including Twitter, …

I have long been an advocate of Friendfeed as a great tool for researchers. Here I discuss the new Friendfeed clone built for researchers, ScienceFeed, suggest what it is good for and what its weaknesses are.

…is that someone needs to make money out of them. It was inevitable at some point that Friendfeed would take a route that lead it towards mass adoption and away from the needs of the (rather small) community of researchers that have found a niche that works well for them. I had thought it more likely that Friendfeed would gradually move away from the aspects that researchers found attractive rather than being absorbed wholesale by a bigger player but then I don’t know much about how Silicon Valley really works. …

A couple of weeks ago there was a significant fracas over Daniel MacArthur‘s tweeting from a Cold Spring Harbour Laboratory meeting.  This was followed in pretty quick succession by an article in Nature discussing the problems that could be caused when the details of presentations no longer stop at the walls of the conference room and all of these led to a discussion (see also friendfeed discussions) about how to make it clear whether you are happy or not with your presentation being photographed, videoed, or live blogged. A couple …

There has been a lot written and said recently about the “real time” web most recently in an interview of Paul Buchheit on ReadWriteWeb. The premise is that if items and conversations are carried on in “real time” then they are more efficient and more engaging. The counter argument has been that they become more trivial. That by dropping the barrier to involvement to near zero, the internal editorial process that forces each user to think a little about what they are saying, is lost generating a stream of drivel. …

On Monday I am speaking as part of a meeting on Use Cases for Provenance (Programme), which has a lot of interesting talks scheduled. I appear to be last. I am not sure whether that means I am the comedy closer or the pre-dinner entertainment. This may, however, be as a result of the title I chose:
In your worst nightmares: How experimental scientists are doing provenance for themselves
On the whole experimental scientists, particularly those working in traditional, small research groups, have little knowledge of, or interest in, the issues …

Euan Adie has asked for some help to do further analysis on the comments made on PLoS ONE articles. He is doing this via crowd sourcing through a specially written app at appspot to get people to characterize all the comments in PLoS ONE. Euan is very good at putting these kind of things together and again this shows the power of Friendfeed as a way of getting the message out. Dividing the job up into bite sized chunks so people can help even with a little bit of time, …