Data is becoming more and more prominent in fields as diverse as political campaigns, healthcare, business metrics and social deprivation. How do we bridge the gap between the data-savvy and the data-shy?
This week, while Hurricane Sandy filled many front pages, several were also devoted to the publication of a study on breast cancer screening. It's nice to see a science and evidence story make the front pages for a change, but are we now any clearer on when screening is helpful?
I spent two days this week at Strata, the Big Data conference that's been run for the last 18 months or so by O'Reilly, and that was held for the first time outside the United States this week.
Given Nesta's remit, I'm keen to make sure that I keep the focus of our Big Data work on innovation. But what does using data for innovation mean? What does it rule out?
Healthcare is an area where the opportunities for data to transform the sector have perhaps been overhyped, but few people doubt that the industry will be transformed by data.
Big Data is a great buzzword - but how many are really innovating with data - and what's stopping those who aren't?
As I go about scoping some new research on big data, open data and some of the opportunities and challenges for innovation, I've been wondering if there's an equivalent to the Uncanny Valley of robotics that governs how comfortable we feel with the data that we share.
Louis Coffait at the Pearson Centre for Policy and Learning has put together a good blog post about using open data to improve education.
Last week, investors, technologists and policy makers converged on NESTA to discuss the future of Industrial Biotechnology in the UK. Industrial Biotechnology deals with all those applications of microorganisms outside healthcare. It creates the opportunity to use alternatives to oil, to reuse waste, and to transform materials with low energy use. Oils secreted by microalgae can be harvested and used as biofuels, while sugar from beet and cane can be transformed
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