topic:data   17

How GDPR Will Change The Way You Develop — Smashing Magazine
Introduction to the “General Data Protection Regulation” that becomes enforceable law in the EU (and for everyone who handles data from people in the EU) starting in May 25, 2018.
domain:UX  domain:Coding  topic:Privacy  topic:BestPractices  topic:Data  topic:Security  topic:Trust  form:Report  form:CodeOfConduct 
march 2018 by novom
How To Protect Your Users With The Privacy By Design Framework — Smashing Magazine
Introduction the the Privacy By Design Framework that will be come enforceable law in the EU with the “General Data Protection Regulation” (GDPR).
domain:UX  domain:Coding  topic:Privacy  topic:BestPractices  topic:Data  topic:Security  topic:Trust  form:Report  form:CodeOfConduct 
march 2018 by novom
Bussed out: how America moves thousands of homeless people around the country | US news | The Guardian
Quinn Raber arrived at a San Francisco bus station lugging a canvas bag containing all of his belongings: jeans, socks, underwear, pajamas. It was 1pm on a typically overcast day in August.

An unassuming 27-year-old, Raber seemed worn down: his skin was sun-reddened, he was unshaven, and a hat was pulled over his ruffled blond hair. After showing the driver a one-way ticket purchased for him by the city of San Francisco, he climbed the steps of the Greyhound bus.
article  topic:homelessness  topic:data  interactive 
december 2017 by thatspotonthe_t
Calling Bullshit.
An (unironical and currently taught) course on calling bullshit in the age of Big Data.
“The aim of this course is to help students navigate the bullshit-rich modern environment by identifying bullshit, seeing through it, and combating it with effective analysis and argument.”

Syllabus, lecture videos and all…
domain:Social  domain:SelfManagement  topic:Data  topic:Rhetoric  topic:Trust  topic:Wording  form:Course 
june 2017 by novom
Mir geht’s heute 430 | Was 2017 bringt | Dezember 2016 | NZZ Folio
Wenn Krankenkassen ihre Prämien aufgrund von Fitnessdaten der Kund_innen festlegen. Ein Trend, der sich abzeichnet, der bereits im Gange ist.
domain:Social  topic:Privacy  topic:Data  topic:future  topic:Training  topic:Trends  form:Report 
december 2016 by novom
Weapons of Math Destruction: 9780241296813: Books
A former Wall Street quant sounds an alarm on the mathematical models that pervade modern life — and threaten to rip apart our social fabric

“Tracing the arc of a person’s life, O’Neil exposes the black box models that shape our future, both as individuals and as a society. These “weapons of math destruction” score teachers and students, sort résumés, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health.”
domain:Social  topic:Data  topic:Privacy  form:Book 
december 2016 by novom
They Have, Right Now, Another You | by Sue Halpern | The New York Review of Books
The massive amount of data we leave behind is collected, combined, sold, analysed and personalised. The results might not always be correct but what does it matter when we become targets. “It would be naive to think that there is a firewall between commercial surveillance and government surveillance. There is not.”
domain:Social  topic:Data  topic:Politics  topic:Privacy  form:Report 
december 2016 by novom
Ich habe nur gezeigt, dass es die Bombe gibt - Das Magazin - Das Magazin
Wie Psychometrik, angewendet auf Big Data Wahlkämpfe beeinflusst haben, u.a. auch Brexit und Trumps Wahl in den USA. Durch Auswertung digitaler Spuren werden Psychogramme von von der Bevölkerung erstellt, welche Micro-Targeting von nie da gewesener Präzision erlauben.
domain:Social  topic:Data  topic:Privacy  topic:Politics  topic:Sociology  form:Report 
december 2016 by novom
A Website Went Offline And Took Most Of Women’s College Basketball Analytics With It | FiveThirtyEight
Last week, leading into the MIT Sloan Sports Analytics Conference, Sue Bird wrote a piece for The Players’ Tribune about this analytic gender gap, noting, “The disparity between NBA data — even data across all male sports — and WNBA data is glaring. Data for the WNBA is relegated to basic information: points, rebounds, steals, assists, turnovers, blocks. While worthy of being noted, those are the most rudimentary numbers in our game.” There are a few slightly richer sources of data for the women’s professional game — will let you see the true shooting percentage and usage rate for WNBA players, for example — but Bird’s overall characterization of the data disparity is dead-on, and the effect is even stronger in college basketball. That’s true this month more than most.

Until recently, the one repository for advanced statistics such as usage, true shooting percentage, pace-adjusted player statistics and adjusted team ratings for women’s college ball was, a vertical of data company National Statistical. But that source disappeared Feb. 29, when ServerAxis, the company that provided server space to National Statistical’s hosting company, suddenly took all its equipment offline. There are reports that ServerAxis was having financial problems, but the company has so far not responded to requests for comment. National Statistical also declined to comment on the situation on the advice of lawyers as it works to recover its data and bring the site back online.
article  topic:women's.sports  topic:basketball  topic:ncaa  topic:uconn  topic:data  topic:fancy.stats 
march 2016 by thatspotonthe_t
Exploring the Impact of New NHL Coaches and GMs | Hockey Graphs
This project has many parts to it. The first, which I’ll be doing here, is just looking at the breakdown of Scoring Chances For% compared to Coaches and GMs in the early days of their tenure, i.e. right after being hired. Scoring Chances, to simplify things, are basically “more dangerous shots” (click here for a more rigorous definition).

To start, I needed data. I pulled all 30 teams from 2006/07 to 2015/16, and coded each season by what kind of organizational changes happened within. This gave me 331 data points, as there were often midseason coaching or GM hirings to account for.

[Very interesting data-tries to prove a GM is more impactful than a coach and so far seems to succeed. Has only scratched the surface.]
topic:hockey  topic:gm  topic:coaching  topic:data 
october 2015 by thatspotonthe_t
Hey, Nate: There Is No ‘Rich Data’ In Women’s Sports | FiveThirtyEight
Unfortunately, the beauty and breadth of sports data don’t yet extend to women. There are other ways to cover women’s sports intelligently, but the lack of accessible and complete data is incredibly limiting. We’ve struggled with this at FiveThirtyEight — where our job is to tell compelling stories with data — because of how much more difficult it is to find data that is “accurate, precise and subjected to rigorous quality control” like we’ve come to enjoy in men’s sports.
article  topic:sports  topic:women's.sports  topic:women'  topic:data  topic:sexism  topic:underrepresentation  via:Impertinence 
february 2015 by thatspotonthe_t

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