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How to be a data journalist

How to be a data journalist
Data journalism is huge. I don't mean 'huge' as in fashionable - although it has become that in recent months - but 'huge' as in 'incomprehensibly enormous'. It represents the convergence of a number of fields which are significant in their own right - from investigative research and statistics to design and programming. The idea of combining those skills to tell important stories is powerful - but also intimidating. Who can do all that? The reality is that almost no one is doing all of that, but there are enough different parts of the puzzle for people to easily get involved in, and go from there. 1. 'Finding data' can involve anything from having expert knowledge and contacts to being able to use computer assisted reporting skills or, for some, specific technical skills such as MySQL or Python to gather the data for you. 2. 3. 4. Tools such as ManyEyes for visualisation, and Yahoo! How to begin? So where does a budding data journalist start? Play around. And you know what?

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Which chart or graph is right for you? Tableau Software helps people see and understand data. Tableau helps anyone quickly analyze, visualize and share information. More than 29,000 customer accounts get rapid results with Tableau in the office and on-the-go. And tens of thousands of people use Tableau Public to share data in their blogs and websites Data science We’ve all heard it: according to Hal Varian, statistics is the next sexy job. Five years ago, in What is Web 2.0, Tim O’Reilly said that “data is the next Intel Inside.” But what does that statement mean? Why do we suddenly care about statistics and about data? In this post, I examine the many sides of data science — the technologies, the companies and the unique skill sets.

Playing with heat-mapping UK data on OpenHeatMap Last night OpenHeatMap creator Pete Warden announced that the tool now allowed you to visualise UK data . I’ve been gleefully playing with the heat-mapping tool today and thought I’d share some pointers on visualising data on a map. This is not a tutorial for OpenHeatMap – Pete’s done a great job of that himself (video below) – but rather an outline of the steps to get some map-ready data in the first place.

Voices: News organizations must become hubs of trusted data in a market seeking (and valuing) trust Editor’s Note: American readers may know Geoff McGhee for his video project Journalism in the Age of Data, released to acclaim last fall. Here he teams up with two European colleagues — Mirko Lorenz, a German information architect and journalist, and Nicolas Kayser-Bril, head data journalist at OWNI in France — to argue that news organizations should restructure themselves as data generators, gatherers, and analyzers. They believe that selling trusted data should be the foundation of journalism’s new business model. Give their argument a look. Journalists and media companies in general have had to answer a fundamental question ever since their traditional business model collapsed: What are we?

How to analyze unfamiliar data: circle, dive, and riff When you come face to face with unfamiliar data, how do you proceed? How do you avoid sending yourself and your shiny “speed of thought” tool slamming into a dead end? Dan Murray’s got a routine — and he’s also got certain music and right-brained books to go along. Dan’s first rule: “Don’t pre-think.” It’s the hardest thing for people to learn, he says. “If you go into [data analysis] thinking you know where you’re going, you easily miss the granule of gold.” Syllabus: Critical thinking, ethics and knowledge-based practice in visual media Storytelling through videography and photography can form the basis for journalism that is both consequential and high impact. Powerful images can shape public opinion and indeed change the world, but with such power comes substantial ethical and intellectual responsibility. The training that prepares journalists to do this work, therefore, must meaningfully integrate deep analytical materials and demand rigorous critical thinking.

Narcolepsy - Introduction Description An in-depth report on the causes, diagnosis, and treatment of narcolepsy. Highlights Overview All people with narcolepsy experience excessive sleepiness during the day. Data journalism pt5: Mashing data (comments wanted) This is a draft from a book chapter on data journalism (part 1 looks at finding data; part 2 at interrogating data; part 3 at visualisation, and 4 at visualisation tools). I’d really appreciate any additions or comments you can make – particularly around tips and tools. UPDATE: It has now been published in The Online Journalism Handbook. The growing importance of data journalism One of the themes from News Foo that continues to resonate with me is the importance of data journalism. That skillset has received renewed attention this winter after Tim Berners-Lee called analyzing data the future of journalism. When you look at data journalism and the big picture, as USA Today’s Anthony DeBarros did at his blog in November, it’s clear the recent suite of technologies is part of a continuum of technologically enhanced storytelling that traces back to computer-assisted reporting (CAR). As DeBarros pointed out, the message of CAR “was about finding stories and using simple tools to do it: spreadsheets, databases, maps, stats,” like Microsoft Access, Excel, SPSS, and SQL Server. That’s just as true today, even if data journalists now have powerful new tools for scraping data from the web with tools like ScraperWiki and Needlebase, scripting with Perl, or Ruby, Python, MySQL and Django.

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