A two-track mind: sharing data, now and later

This is Ben Werdmuller's second report from the Data Sharing Summit in Richmond, CA, which aimed to address the issue of interoperability between social networks. Part one can be found here. Ben is the CTO of Curverider and one of the leads behind the Elgg open source social networking framework.

The second day of the Data Sharing Summit was smaller than the first. Many of Friday's participants decided that they'd prefer to spend Saturday with their friends and loved ones; at least one spent it surfing in the San Francisco Bay.

This smaller group had a far greater number of researchers rather than service providers, and this highlighted a split in the social networking community. While the startup service providers are keen to find solutions that will work for them as soon as possible, larger organisations and companies - Boeing and AOL were both present - have their sights set on a further-flung future.

The Higgins Data Model, provided by the Higgins Project, provides a glimpse into a distributed social web. Describing itself as "a software development framework that will enable users and enterprises to integrate identity, profile, and relationship information across multiple systems," it allows for sites to work together even if they don't speak the same languages and protocols.

The demo the project gave was very promising; however, it's currently impossible to take this model and plug it into a service. Following the summit, a number of service providers are collaborating and attempting to share profile information using simple, currently available technologies. It's less ambitious than Higgins, and ultimately will be less powerful, but the difference is, it can happen now. Another group has broken off to try and develop Stuff I've Done, a standard for aggregating actions a user performs on all the networks they belong to.

If data sharing is going to occur, it's likely to be the more innovative, agile companies that push it forwards. Because these tend to be smaller and have fewer resources, the less expansive, more immediately useful technologies are the ones that will succeed. Then, once users begin to see more control over their data, the larger companies will begin to see the benefits and the research will come into its own. In five years, we'll all look back on the world of Facebook-like data silos and wonder why we put up with it.