I’ve been a strong proponent of FriendFeed since its launch. Its technology, clean interface and “data first, then conversations” approach have made it a highly-successful experiment in social networking for scientists (and other groups). So you may be surprised to hear that from today, I will no longer be importing items into FriendFeed, or participating in the conversations at other feeds.
Here’s a brief explanation and some thoughts on my online activity in the coming months. Read the rest…
In part 1, I described some frustrations arising out of a work project, using the Array Express API. I find that one way to deal mentally with these situations is to spend some time on a fun project, using similar programming techniques. A potential downside of this approach is that if your fun project goes bad, you’re really frustrated. That’s when it’s time to abandon the digital world, go outside and enjoy nature.
Here then, is why I decided to build another small project around FriendFeed, how its failure has led me to question the value of FriendFeed for the first time and why my time as a FriendFeed user might be up. Read the rest…
The API – Application Programming Interface – is, in principle, a wonderful thing. You make a request to a server using a URL and back come lovely, structured data, ready to parse and analyse. We’ve begun to demand that all online data sources offer an API and lament the fact that so few online biological databases do so.
Better though, to have no API at all than one which is poorly implemented and leads to frustration? I’m beginning to think so, after recent experiences on both a work project and one of my “fun side projects”. Let’s start with the work project, an attempt to mine a subset of the ArrayExpress microarray database. Read the rest…
LinkedIn, the “professional” career-oriented social network, is one of those places on the Web where I maintain a profile for visibility. I’m yet to gain any practical value whatsoever from it. That said, I know plenty of people who do find it useful – mostly, it seems, those living near the north-east or west coast of the USA.
My LinkedIn Network
LinkedIn have something of a reputation for innovation – see LinkedIn Labs, their small demonstration products, for example. The latest of these is named InMaps. It’s been popping up on blogs and Twitter for several days. Essentially, it creates a graph of your LinkedIn network, applies some community detection algorithm to cluster the members and displays the results as a pretty, interactive graphic that you can share.
What seems to have captured the imagination is that the graphs indicate communities that are instantly recognisable to the user. There’s mine on the right (click for full-size version). It’s not a large, complex or especially interesting network but when I “eyeballed” it, I was immediately able to classify the three sub-graphs:
Orange – mostly people with whom I have worked or currently work, plus a few “random” contacts: note that this group is hardly interconnected at all
Green – people who work in bioinformatics or computational biology, particularly genomics: two major hubs connect me with this group
Blue – the largest, densest network is composed largely of what I’d call the “BioGang”: people that I interact with on Twitter and FriendFeed, many of whom I haven’t met in person
This confirms what I’ve long suspected: I prefer to network with smart strangers than my immediate peers and colleagues. Or as Bill Joy said, “no matter who you are, most of the smartest people work for someone else.” I’ve seen this misquoted as “where you are”, which makes more sense to me.
Over the holiday, I received an email from WordPress, containing a brief statistical summary of activity at this blog in 2010. Their automated procedures aren’t quite infallible: busiest day was 3 016 views, not 3, but they’ve done a reasonable job.
Even better, they’ve compiled the results into a draft blog post, ready for publishing. So here it is! Thanks, WordPress.
Normal service with original content will resume in due course. Read the rest…