The New Science of Sharing

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The free and open exchange of information and ideas will provide astronomers with an unprecedented map of the universe in a fraction of the time it would have taken using conventional methods.

As large-scale scientific collaborations become the norm, scientists will rely increasingly on distributed methods of collecting data, verifying discoveries, and testing hypotheses not only to speed things up but to improve the veracity of scientific knowledge itself. For example, rapid, iterative, and open-access publishing will engage a much greater proportion of the scientific community in the peer-review process. Conventional paper-based scientific journals, meanwhile, will be augmented by dynamic publishing tools such as blogs, wikis, Web-enabled RSS feeds, and podcasts that turn scientific publications into living documents. Projects such as MIT's OpenWetWare are already doing this.

There will always be aspects of scientific inquiry that are painstakingly slow and methodical. But scientific institutions can take steps to encourage mass collaboration. Discarding the outmoded, manual data-permission policies that currently thwart the ability to share data would enable scientific Web services to weave together information from all of the world's databases. Teams of scientists that invest heavily in collecting data, and understandably feel justified in retaining privileged access to it, could apply Creative Commons licenses that stipulate rights and credits for the reuse of data, while allowing uninterrupted access by networked computers.

Rethinking Science

Leading scientific observers already expect more change in the next 50 years of science than in the last 400 years of inquiry combined. As the pace of science quickens, there will be less value in stashing new scientific ideas, methods, and results in subscription-only journals and databases, and more value in wide-open collaborative-knowledge platforms that are refreshed with each new discovery. These changes will enhance the ability of scientists to find, retrieve, sort, evaluate, and filter the wealth of human knowledge, and, of course, to continue to enlarge and improve it. Meanwhile, faster feedback cycles from public knowledge to private enterprise, enabled by more nimble industry-university networks, will allow new knowledge to flow more quickly into practical uses and enterprises.

As mass collaboration takes root in the scientific community, companies have an opportunity to rethink how they do science, and even how they compete. One area in which new open scientific collaborations can pay dividends is in the early detection of disruptive innovations that could threaten a company's product roadmap—or, even better, generate entirely new products and services.

Take Intel (INTC). Accelerating technological change and heightened competition from Asian semiconductor companies have put the heat on the veteran chipmaker. In order to stay ahead, Intel needs to expand into new offerings and find ways to add value to chips, which are increasingly low-cost commodities. The problem for companies like Intel is that the kind of exploratory research required to renew product roadmaps and identify disruptive innovations is the most costly and risky. So like a growing number of businesses in fast-moving, tech-intensive industries, Intel is sharing these costs and risks through an open and collaborative model of industry-university partnerships.

Divinding the Fruits

Sure, industry-university partnerships have existed for centuries. But in the new model, companies and their collaborators don't squirrel themselves away in secretive laboratories and retain proprietary access to all of the data and outputs. Instead, they open up the early-stage research to the world in order to widen participation and accelerate discoveries, while positioning themselves to move strongly and rapidly into a latent market as new ideas and inventions emerge.