Football is flooded with datapoints that can give us a unique view of the game. And for the first time, we can judge the quality of a game through the voices of fans.

This data project maps the sound of 75,000 fans inside Bayern Munich’s Allianz Arena. While the noise may appear to be a deafening wall of sound, each individual voice is a unique data point. Through these minute data points, patterns can be drawn and predictions made, painting an increasingly more vivid picture of the happenings on the pitch. By responding to every change of possession, questionable decision or missed chance, the fans give us the perfect lens through which to reimagine the game. So, turn the volume up and check it out.

Mapping a treasure-trove of datasets

Datasearch Google
The web is a treasure trove of data and data repositories, providing access to millions of potentially valuable datasets. To enable easy access to this data, Google has launched Dataset Search, a new tool that gives scientists, data journalists, data geeks, or anyone else the ability to find the data required for their work and their stories, or simply to satisfy their intellectual curiosity. Dataset Search lets you find datasets wherever they’re hosted – whether it’s a publisher’s site, a digital library, or an author’s personal web page. Of course, search tool like this is only as good as the metadata that data publishers are willing to provide, so the search giant is encouraging dataset owners to adopt a common standard for describing their data.

Safety in numbers – data’s checking in
Data is at the heart of Uber’s service. And now the ridesharing tech firm is using data to put safety at the core of its offering too. Uber has long used GPS data to put every trip on the map – where and when you’re riding and who’s behind the wheel. But data can do much more – so the firm has introduced Ride Check. Using data from the drivers phone, Ride Check can flag trip irregularities – from crashes to a long, or unexpected stops during a trip, that could indicate a problem. Both the rider and the driver will now receive a Ride Check notification to check everything is OK.

How do you ‘punch above your weight’? Data

Why is it that our partners, more often than not, tend to match us in terms of age, education, attitudes, and even physical attractiveness? Ever noticed that? There are two theories – the matching hypothesis and the competition hypothesis. The former is the idea that individuals somehow know how desirable they are and pick a mate at the same level. The later assumes that everyone seeks the most desirable partner. The result is that the most desirable people pair off, followed by the next most desirable, and so on. Whatever – the results are largely the same. The only way to tease them apart is to study mating behavior in detail. But that has always been too difficult to do at the scale necessary… Until now. Researchers have mined the data from a popular online dating site to find a new, objective way to measure desirability and to rank individuals accordingly… The byproduct offering an insight into the best way to date someone who’s completely “out of your league”…

How data revealed the saddest number one song of all time

Spotify has collected metadata on each of 35 million songs in its database. It charts the tempo and key, and even the ‘danceability’ of every song. Other measures include energy (how “fast, loud and noisy” a track is) and valance… how happy or sad a song is. Tracks with high valence sound more positive, while tracks with low valence sound more negative (eg sad, depressed, angry)”, according to Spotify. This data is a goldmine for data scientists… who’ve already created a gloom index for Radiohead songs and mined out the most depressing Christmas song of all time… Now, this very data has been used to unearth the most depressing song ever to hit the top of the charts!

Who’s privy to your data relationships?
The average smart phone user touches their phone 2,600 times a day. That’s nearly a million touches a year. Maybe more. Our phones aren’t only tools that allow us to watch media, answer questions, listen to music and forge relationships. They’re also sophisticated monitoring devices that we voluntarily feed with interactions we presume are private. But the relationships we have with our devices are not monogamous. So, who else is privy to these relationships? And what are they using your data for? It’s a question that’s been asked before. But never so thoroughly has it been answered… A team of nine reporters across Europe and the US filed more than 150 personal data requests to more than 30 popular tech companies, ranging from social networks to dating apps and streaming services. They did this both before GDPR was enforced and after… to see if GDPR is truly able to level the playing field between consumers and today’s data barons.

Posted in Media roundup On September 7, 2018 By