Andrew Milsted, a PhD student, enabled an RDF dump of the content in the lab notebook used by Cameron’s group (and others I suspect). The result, a graph that shows each post in the notebook as a node and links between posts as edges. It is a universe of the work going on in the lab, and how that work interacts. It would be interesting to see the dynamics of this graph evolve, and various other ways of visualizing the underlying data and relationships. It would also be cool to put this up on the web as linked data and link it to data outside Cameron’s lab. Might even lead to some very interesting observations and relationships.
This is a simple example, but highlights why it is so important to be able to put data into machine readable formats. RDF is a naturally good model, since it highlights relationships within the underlying data.
As shown here, the digital material can be examined for links and mined in ways that are just impossible today. Linkages between pages, data and comments could be examined. Possible relationships between projects could be highlighted. Areas for collaboration could be determined.
Context can be added to data in order to create a deeper examination of the information created.
The groups that more rapidly embrace these sorts of approaches will be able to turn the creativity cycle faster, increase the rates of diffusion of innovation in the community and find solutions to complex problems that are unsolvable by simply analog approaches.