If I could just add to that, maybe a very literal answer to how some of these things are connected. If you think about something like big data, which is a really new and innovative disruptive way that businesses can be evaluating massive amounts of information, they're using it in ways, for example, to customize the services that you get. So when you go to Amazon or Google and do your search, there's a computer system behind that to help customize it, based on what your past preferences have been. Big data analytics is really becoming one of the fields in Canada where we have strength.
There are very physical ways that some of that information is connected in terms of our digital research infrastructure and the actual pipes that we have in Canada to help move information from, say, a research institution to a business, or to enable a business to get access to the cloud so they're able to use some of these technologies. If you look at something like an organization called CANARIE, which is Canada's research infrastructure backbone, it's the actual physical pipes. That's really important to understand: where the strengths are from a networking infrastructure perspective.
If you think about the ecosystem broadly, and again I'll stay with big data, something that IBM is doing a considerable amount with, CANARIE itself is creating a test bed that allows small businesses—one or two people creating their software in their basement, which could be absolutely anywhere across the country—to go online and get access to the cloud at free or very reasonable resources. It creates a community of individuals who can be located anywhere across the country, who then have access to other researchers in similar areas such as big data.
The ecosystem to support also includes things like incubators and accelerators. Toronto has a very interesting accelerator that focuses specifically on big data, called OneEleven. As you think about what the supports are for these types of networks, those kinds of connections and specialization areas are really important to understand. They underpin some of the work that goes on in universities and colleges, which also helps to create some of these communities and networks so that individuals who are, say, working on something like software can understand and build off the work that others are doing.