Bookmarked The Anatomy of a Data Story by Nicole Hitner (datafloq.com)
It’s not the graph that makes the data interesting. Rather, it’s the story you build around it—the way you make it something your audience cares about, something that resonates with them—that’s what makes data interesting.
According to Ben Wellington, there are four features of a great data story:

Connect with people

If you don’t have a question to answer or artificial intelligence to point you to an interesting trend, you’ll likely have to do some data discovery and exploration to find a story worth telling.

Try to convey one idea

When designing your visuals, take clarity and conciseness over sizzle—but also consider what it is you want to emphasize … Anytime you can give your audience a more familiar point of reference, it can help drive an idea home.

Keep it simple

Once you have all your facts and figures, the first step in telling their story is considering your audience. After all, if your goal is to make the story resonate with the audience, you’ll need to consider its members’:

Explore a topic you know well.

When there are multiple campaigns designed to resolve the conflict and multiple ways of looking at each campaign, there can be a lot of data to review. In these cases, focus only on the visualizations that are essential to the narrative, or the story will dissolve into a humdrum boardroom presentation.


BONUS – Delivery

Consider your tone. Humor can utterly transform a story, but so can poignancy and earnestness. Giving the story some kind of tonal emphasis can give it the edge it needs to stand out from the rest.

via Tom Woodward

Liked Google and Facebook are watching our every move online. It's time to make them stop by Gabriel Weinberg, CEO and founder of DuckDuckGo (CNBC)
Google, Facebook hidden trackers follow users around the web at alarming rates, says DuckDuckGo's CEO Gabriel Weinberg. To make any real progress in advancing data privacy this year, we have to start doing something about them. Not doing so would be like trying to lose weight without changing your diet. Simply ineffective.
Listened IRL Podcast Episode 10: Face Value from irlpodcast.org
From Snapchat filters to Apple’s Face ID, biometric technology plays a growing role in our everyday lives. What do we actually give up when we upload our face to these apps? Steven Talley shares his experience as a victim of mistaken identity. Joseph Atick, a forefather of facial recognition technology, reckons with its future. We head to to China, where biometric data is part of buying toilet paper. And artist Adam Harvey investigates how racial bias seeps into big data sets.
In this episode of the IRL Podcast, Veronica Belmont leads a conversation about mistaken identity, the Art and Culture selfie and increase in the collection of biometric data in China.

Glynnis MacNicol questions what we are giving up in using our face to log-in to our phone or sharing online. He suggests that we should become face-less:

Everyone get your faces offline. Yes, I can’t … What evidence is there that this is a good idea? I mean, really? Is there literally any evidence that this is going to benefit us? Let me ask you, why would you post a selfie?

That has me again thinking about the use of such platforms as Facebook and Instagram to share school-based images.

For Adam Harvey, it comes back to race:

I tell people that facial recognition is really racial recognition, plus some additional metadata.

In an article in the New Yorker, Joy Buolamwini suggests that this is a coded gaze:

Just as the male gaze sees the world on its own terms, as a place made for men’s pleasure, the coded gaze sees everything according to the data sets on which its creators trained it.

This is very much a part of the discussion of ethics in the new machine age.

Bookmarked More on the mechanics of GDPR (Open Educational Thinkering)
Note: I'm writing this post on my personal blog as I'm still learning about GDPR. This is me thinking out loud, rather than making official Moodle pronouncements. 'Enjoyment' and 'compliance-focused courses' are rarely uttered in the same breath. I have, however, enjoyed my second week of learning from Futurelearn's
Doug Belshaw breaks down a number of points associated with the GDPR. During TIDE, he also makes the point that this will set a precedence moving forward in regards to the collection of data so will therefore have an influence on everyone. Eylan Ezekiel also provided a useful discussion a few months a go.
Bookmarked Fitness tracking app Strava gives away location of secret US army bases by Alex Hern (the Guardian)
Data about exercise routes shared online by soldiers can be used to pinpoint overseas facilities
Alex Hern reports that Strava data inadvertently reveals a number of supposed military secrets. In response, Bill Fitzgerald also provides some interesting commentary on Twitter:

Arvind Narayanan also wrote a series of tweets:

Listened Digital dystopia: tech slavery and the death of privacy – podcast by Jordan Erica Webber from the Guardian
Jordan Erica Webber explores whether our privacy has been compromised by the tech giants whose business models depend on harvesting and monetising our data. We speak to cyborg rights activist Aral Balkan; the executive director of UK charity Privacy International Gus Hosein; and to Kevin Kelly, founding executive editor of Wired magazine and author of The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future.
In the first episode of our four-part miniseries, Jordan Erica Webber asks whether our digital selves are owned by tech firms in a new form of slavery? One of the interesting points made was that in the past, people were often private in public spaces, whereas today things have been reversed, where we are public in private places.
Bookmarked Google Maps’s Moat (Justin O’Beirne)
Google has gathered so much data, in so many areas, that it’s now crunching it together and creating features that Apple can’t make—surrounding Google Maps with a moat of time
Justin O’Beirne discusses the addition of ‘Areas of Interests’ to Google Maps. He wonders if others, such as Apple, can possibly keep up. The challenge is that these AOIs aren’t collected—they’re created. And Apple appears to be missing the ingredients to create AOIs at the same quality, coverage, and scale as Google.

O'Beirne's table demonstrating the difference between Google and Apple

Google’s is in fact making data out of data:

Google’s buildings are byproducts of its Satellite/Aerial imagery. And some of Google’s places are byproducts of its Street View imagery.

For a different take on Google Earth’s 3D imagery, watch this video from the [Nat and Friends]:

https://youtu.be/suo_aUTUpps

Reply to Chris Betcher and Location Tracking

I am wondering if this is the way of the future Chris? Are we coming to a time when insurance companies, car manufacturers or platforms collect our data whether we like it or not? It is baked into the Maps API infrastructure. I worry with the way that data is shared whether some of these companies even need our explicit permission anymore? Take for example the recent analysis of tracking on Android:

The tracker allows marketers to use machine learning to discover personas, uses cross-device ID, and even uses behavioral analysis to guess when a user is sleeping, and a probabilistic matching algorithm to match identities across devices.

What is disconcerting is that it may not be the application designed for location which provides a company with location information.