The web and its organization fundamentally challenges the idea of the research record as a single document or record and removes the constraints created by a physical record or document to enable a multifaceted, multifunctional, and multimedia laboratory notebook. The web itself has evolved from its original form of linked static documents to dynamic services and sites populated by objects created by their users and content automatically aggregated and re-published in new contexts and new forms. The vision of the web as a dynamic network of addressable objects and their relationships can be traced right to its earliest origins in the early 1990s but it is only now being realized.

Fully exploiting the infrastructure and functionality of the web to create a web-native laboratory record requires re-thinking the traditional view of the laboratory notebook as a linear narrative of events. By creating individual addressable objects that refer to physical samples and materials, laboratory or computational processes, and data files, it is possible to create a dynamic record that can be directly linked into the growing semantic and linked data web. The web native laboratory notebook is a combination of the web of data and the web of things. If the best available services are used for each kind of object then the actual laboratory record can be reduced to a feed describing the relationships between these objects and functionality that has been specifically designed around those objects can be fully exploited.

The beauty of this approach is that it doesn’t require users to shift from the applications and services that they are already using, like, and understand. What it does require is intelligent and specific repositories for the objects they generate that know enough about the object type to provide useful information and context. What it also requires is good plugins, applications, and services to help people generate the lab record feed. It also requires a minimal and arbitrarily extensible way of describing the relationships. This could be as simple html links with tagging of the objects (once you know an object is a sample and it is linked to a procedure you know a lot about what is going on) but there is a logic in having a minimal vocabulary that describes relationships (what you don’t know explicitly in the tagging version is whether the sample is an input or an output). But it can also be fully semantic if that is what people want. And while the loosely tagged material won’t be easily and tightly coupled to the fully semantic material the connections will at least be there. A combination of both is not perfect, but it’s a step on the way towards the global data graph.

The technical challenges of implementing this vision are formidable. Authoring tools are needed, along with well designed repositories; a whole infrastructure of services and tools for pushing information between them. In this context the announcement of the Google Wave protocol is a very interesting development. The functionality that is described has an enormous potential to make the implementation of many of these tools much easier. The proof of this will be in the development of useful functionality within this platform. Google has the brand awareness and expertise to make such a revolution in online communication technology possible. They have set the agenda and it will be a very interesting story to follow.

The view of the laboratory record as a distributed set of objects on the open web is closely linked with the agenda of the Open Research Movement. The presumption is that the gains made by wiring your own ideas, samples, and results into the wider information graph, far outweigh the losses. Only limited gains could be made by adopting this architecture but keeping the content closed off from the wider web. Thus its adoption and development depends closely on the users view of the future of scientific communication. If you accept the vision of open communication and the idea that it will make your own research more competitive then this is a path to follow. The web was built for the sharing of data amongst research scientists. We are only just learning how to that effectively and efficiently.

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