G Suite Updates: Google Fusion Tables to be shut down on December 3, 2019

G Suite Updates: Google Fusion Tables to be shut down on December 3, 2019. “Google Fusion Tables was launched almost nine years ago as a research project in Google Labs, later evolving into an experimental product. For a long time, it was one of the few free tools for easily visualizing large datasets, especially on a map. Since then, Google has developed several alternatives, providing deeper experiences in more specialized domains. In order to continue focusing our efforts in these areas, we will be retiring Fusion Tables.”

Quartz: The US plans to stop releasing its most detailed census data

Quartz: The US plans to stop releasing its most detailed census data. “As a data-focused journalist who writes about economic and demographic trends, I use census data a lot. Specifically, I rely on the individual-level microdata that is released by the bureau and turned into an easily usable format by the Minnesota Population Center. I am among tens of of thousands (pdf) of data analysts who rely on this data to study American poverty, health, and population patterns. The US Census announced this week that, because of privacy concerns, this microdata will no longer be made widely available.”

British Library: Introducing an experimental format for learning about content mining for digital scholarship

British Library: Introducing an experimental format for learning about content mining for digital scholarship. “This post by the British Library’s Digital Curator for Western Heritage Collections, Dr Mia Ridge, reports on an experimental format designed to provide more flexible and timely training on fast-moving topics like text and data mining.”

Washington Post: Step aside Edison, Tesla and Bell. New measurement shows when U.S. inventors were most influential.

Washington Post: Step aside Edison, Tesla and Bell. New measurement shows when U.S. inventors were most influential.. “The U.S. patent office has stockpiled the text to more than 10 million patents. But that’s often all they have: an enormous amount of text. Many early patents lack any form of citation or industry specification, which researchers could use to understand the history of American invention. Now a team of economists has created a clever algorithm that processes that text — often the only consistent data we have for many of the country’s most famous inventions — to create a measure of the influential inventors and industries of the past 180 years.”

Online Journalism Blog: How Periodista de Datos aggregated over 300 journalists in Spain and Latin America to help data journalism collaboration

Online Journalism Blog: How Periodista de Datos aggregated over 300 journalists in Spain and Latin America to help data journalism collaboration. “In July an aggregator of data journalists from Spain and Latin America was launched under the name Periodista de Datos. Four months later, Maria Crosas Batista interviewed Félix Arias, project lead with Miguel Carvajal, to find out more about how the project came about — and where they plan to take it next.”

Technical .ly: Cypher Philly, a project born from a meetup, wants to unlock the power of open data

Technical .ly: Cypher Philly, a project born from a meetup, wants to unlock the power of open data. “For Cypher Philly founder Jess Mason, the copious amounts of open data produced every year by OpenDataPhilly needed another layer that could maximize their potential impact. It’s why he set out — alongside cofounder Jason Cox and about 40 volunteers — to build an application that can connect the dots between data sets meant for transparency and higher government efficiency.”

Quartz: What’s the best way to learn the programming language R? (Preferably, for free)

Quartz: What’s the best way to learn the programming language R? (Preferably, for free). “As data becomes an ever larger part of work, for many people spreadsheets just are not enough. Programs like Microsoft Excel and Google Sheets are powerful tools, but they have limitations in terms of the amount of data you can work with, the kind of analyses you can do, and the types of charts you can make. When data users reach these limitations, the obvious next step is learning a programming language.”