Data Journalism Links

Curated by Winny de Jong, more at the #ddj blog.

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A quick repo with basic command line commands, plus a very brief CSVKit run through.

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"With the proliferation of available data, it’s become more common for newsrooms to have access to datasets that contain more story leads than they can meaningfully pursue themselves. Collaborative data journalism allows multiple newsrooms to find and tell those stories, make the most out of large datasets and, ultimately, increase the chances that their work will have impact."

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For news outlets to successfully innovate, interdisciplinary teams are essential. Here’s how to make them work: define your mission; grow your team organically; fit a model to your newsroom; hone a digital strategy and mindset; work on a common language; manage your skill sets; live in beta mode; develop your own tools; engage in job development for news nerds; and experiment a lot.

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Paul Bradshaw reflects on the lessons learned from a decade of teaching dedicated data journalism courses.

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"Effective information design is achieving that Goldilocks balance between what to show, the amount and type of information, and how to show it, visual representation." Sheila Pontis about the concept of the Goldilocks understanding.

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Weighing up whether or not you want to use web scraping for your next job? Have a look at the pro's and con's.

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«The Stories Behind a Line» is a visual narrative of six asylum seekers' routes. They travelled from their hometown to Italy. This project wants to tell their stories through the data that shaped their personal travelling line.

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“One of the keys to the success of a data journalism team is the diversity of its members.” – La Nación

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As news traveled around the world that one of the largest icebergs ever observed had finally broken off from Antarctica, reporters were faced with a question of scale. Few among us can visualize just how large a 2,200 square-mile (5,698 square-kilometer) hunk of ice really is, so they had to come up with a reference their readers might recognize.

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No matter where you might reside on the collect/compute/represent continuum, it will do you service to stand on high ground, to stretch your vision as far as you can towards the opposite edge. By taking a systems approach to data I believe we can make better things. And we might also find deeper and more meaningful questions– questions that are as much about how these things work (or don’t work) as why they exist in the first place.

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A Google Spreadsheet with essential datasets, their topics, sources and data types. Collected by Quartz.

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Show the full distribution wherever possible, as this demonstrates the full range of circumstances experienced by different people, which in turn: ensures that the people represented by that data feel truly represented; often highlights the real story that was obscured by the summary statistics; and confronts the importance of relative standing. Don't stop at the simple answer: dig deeper than summary statistics. Sometimes it's only at this stage that the answer reveals itself

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Ted Han and Quinn Norton give advice how to protect your sources when you share your documents: scrub metadata, redact information properly, search for microdots, and more. Think carefully about how the document will be perceived and used in public, and maximize the effectiveness of the evidence that supports your story while minimizing the harm to sources and bystanders.

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This book covers the foundation skills necessary to using d3.js to visualize data on the web. It requires no technical background, and teaches students how to begin programmatically building interactive graphics in modern and reproducable ways.

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The Open Up report is intended to be part of a growing body of work using open data to fight corruption. It includes use cases and methodologies, 30 priority datasets and key attributes needed to address corruption, and recommended data standards.

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Data Gif Maker, a tool to help journalists make these visuals, which show share of search interest for two competing topics.

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“Government agencies, businesses and other organizations alike all communicate in the language of data and statistics,” the AP said. “To cover them, journalists must become conversant in that language as well.” Here are a few of the AP’s data journalism recommendations: get the data in searchable form, if you can; scraping data should be a “last resort”; make sure someone else can reproduce your findings; let your readers see the source data, too.