The science of Google Wave
What is Google Wave, and how might scientists use it?
It is a communication tool that is essentially e-mail crossed with an instant messenger. You can think of each 'wave' or e-mail thread as a flexible document, which allows collaborators to chat and edit the same version in real time. You can also easily drop rich media such as sound files, charts and videos into the document. So Google Wave could be used for collaborative authoring, to speed up writing papers and grant applications, for example.
However, it is also possible to create automatic programs that buzz around the document, annotating it in ways that are hidden from the human reader. The automated programs, or 'robots', make it possible to link to related scientific documents; mark up text so that, for example, protein names are automatically linked to a protein database; or pull in data from elsewhere and create live graphs that update as the data change.
Might this change the scientific manuscript?
Yes, in several ways. Documents created in Google Wave would be much richer, and one could convert them to the format of a published paper and retain all that annotation.
The real-time authoring and date-stamped recording of contributions also makes for an obvious way to create papers that aren't static, that are updated over time, perhaps in combination with one or many frozen versions of record.
How else can you see Google Wave affecting scientists?
I can imagine that the robots could really come in useful in a laboratory notebook. For example, as data come off a laboratory instrument via a computer, a program could insert them straight into the document. You might have another program that visualises those data for you. These widgets would help you control, monitor and observe an experiment, and even share that wave with someone else as a template for their experiment. Scientists could share their experimental processes in a way that's hard to do at the moment.
What have you actually done with the tool so far?
Relatively few people, perhaps 10,000, have had access to the developer sandbox so far, and perhaps only 100 of those are scientists. It is early days we're at the playing stage.
I have made a robot that recognizes chemical names when triggered by the right text input, searches for information about them on ChemSpider [an open-access search for chemical information such as molecular structures], and can turn weights into molarities. Euan Adie, a product manager in Nature's web publishing group, has developed a 'references' robot that can search the PubMed archive of journal papers for related terms, and turn that text into correctly formatted citations.