For managers of computer labs, this technology eliminates a slew of nitty gritty management problems without good solutions. When a shared computer is idle, do you take action after 5, 10, or 15 minutes? If you wait too long, you annoy users who are waiting for their turn, and you invite unauthorized users to sneak into someone else's session. If you act too soon, you ruin the experience for the current user. Should you immediately log off an idle user or do you lock the screen for a while before logging off? Again, you balance the interests of the current user against those of the next user. Which software do you install where? Installing all software on every computer is usually too expensive. But if each computer in the lab has its own configuration, how do you communicate those differences to the users? The ultimate challenge of the shared computer is how to let students install software that they themselves are developing while keeping the computer relatively secure, usable to others, and free from pirated software.
Amazon has solved all of this and more. With cloud-based computers, there is no such thing as an idle computer, only idle screens. Shutting down a screen and turning it over to another user does not ruin a session in progress. It is more like turning over a printer. The cloud-based personal computer is configured for one user according to his or her requirements. Students and faculty can install whatever software they need, including their own research software. As to the usual suite of standard applications, cloud services like Adobe Creative Cloud, Google Apps, and Windows Azure have eliminated software installation and maintenance entirely.
The potential of cloud computing in the Information Commons is more than substituting one technology with another. Students and faculty suddenly have their own custom computing laboratory with an unlimited number of computers over which they have complete control. One can imagine projects in which cloud-based computers harvest measurements from sensors across the globe (weather-related, for example), read and analyze the news, and data mine social networks. All of this data can then be fed to high-performance servers running research software for analysis and visualization.
Currently, retail pricing for a cloud-based personal computer starts at $35 per month. This is already a very good price point, considering that it eliminates the hardware replacement cycle, software maintenance, security issues, etc. One can also add and drop computers as needed. Moreover, this is a price point established before competitors have even entered the market.
When computing and storage become relatively inexpensive on-demand commodity services, computing labs are no longer in the business of sharing computing devices, storage, and software; they are in the business of sharing visualization devices. Currently, Information Commons provide large-screen high-resolution monitors attached to a computer. As large-scale, high-performance, big-data projects grow in popularity across many disciplines, there will be increasing demand for more advanced equipment to visualize and render the results. Today's computing labs will morph into advanced visualization labs. They will provide the capacity to use multiple large high-resolution screens. They may provide access to CAVEs (CAVE Automatic Virtual Environment) and/or additive-manufacturing equipment (which includes 3-D printing). The support requirements for such equipment are radically different from those for current computer labs. CAVEs need large rooms with no windows, multiple projectors, and a sound system. Additive manufacturing may be loud and may require specialized venting systems.
For managers of Information Commons, it is not too early to start planning for this transition. They may look forward to getting rid of the nitty-gritty unsolvable problems mentioned above, but integrating these technologies into the real estate currently used for computing labs and libraries will require all of the organizational and management skills they can muster.