– We need to divorce the idea of innovation from startups. Innovation is as much about existing, large institutions as it is smaller, new ones. Instead of talking about start-ups, we should focus on R&D policy—and make sure that it is size-agnostic.
– We need to be able to collect, share and analyze data across institutions for the purposes of innovation. This means creating open data standards, especially in the public sector. Proposals like the EU Open Data strategy and work done on Data.gov are encouraging.
– Some of the data we will need to analyze is going to be personal data, so we need mechanisms to support consent in the innovation process. This is why projects like the one John Wilbanks is leading, Consent to Research, are so important.
– Analyzing the large sets of data that will drive a lot of this innovation will mean using the cloud. It’s just not cost-effective to expect everyone to run their own data centers for this type of computation. We need to reduce barriers to access these cloud services, such as restrictions on cross-border data flow. The APEC Pathfinder project is one encouraging effort to achieve this goal.

Google’s Betsy Masiello offers some framing thoughts for the future of data and innovation, in response to an interview with Mark Pagel on Edge.org.

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