Many hours of coalition ‘what ifs’ lie redundant and, rather than drawing up a coalition agreement, the new government are getting back to business. Ministers are this week getting to grips with new briefs or, for many, heading back to their departments to pick up where they left off. And of course this has all happened rather sooner than any of us, and they, expected.
When we think about the types of people who make analytics and big data work, we typically think of highly quantitative or computational folks with hard knowledge and skills. You know the usual suspects: data scientists who can make Hadoop jump through hoops, statisticians who dream in SAS or R, data wizards who can extract two years of data from a medical device that normally dumps it after 20 minutes (a true request). Companies lust after these skills, and they are admittedly important and not easy to find.
It starts like a typical data science job interview - I summarise my resume and they describe their core products. They describe what their data looks like and we have a very interesting chat about the structure of their data. But the interviewer keeps dancing around the topic of what my job will consist of and the whole thing become vaguer and vaguer until I'm forced to ask 'this sounds great but could you please explain what the job actually is?'
The importance of public understanding of science, and of outreach activities more generally, is now widely accepted. Much research funding comes from public sources, so there’s an obligation to ensure that the money is well spent, and that people understand what they are getting in return. Beyond that, a well-informed population is necessary so that people understand the modern world and can make rational decisions about their lives.
Data, and the presentation of data, has always been an intrinsic aspect of elections, from vintage computers the size of a room projecting results based on uniform national swing, to television psephologists brandishing swingometers. Because of their high profile, elections are often used as a showcase for technological and statistical advances. This year is no different, with a variety of statistical and digital tools changing the way we experience elections.