GIJN’s Data Journalism Top 10: European Election, Data via Audio, Tax Fraud & Parserator

What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from May 27 to June 2 finds immense buzz around the recent European Parliament elections, with @SZ explaining the EU political landscape, @morgenpost looking at the results in Berlin, and @journocode collecting data journalism pieces related to the election. There’s also @datajournalism’s tips on presenting data through audio and @BIRNSrbija’s data investigation into major corporate tax fraud in Serbia.

GIJN’s Data Journalism Top 10: Game of Thrones Deaths, Visualizing Rich Hungarians, European Parliament

What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from May 20 to 26 finds @PostGraphics’ meticulous cataloguing of all on-screen deaths in Game of Thrones, @datajournalism’s tips on covering the crime beat, @DIEZEIT’s analysis of a politically diverse European parliament, and a quick beginner’s guide to learning data visualization by @AlliTorban.

GIJN’s Data Journalism Top 10: Moscow Garbage, Mexican Homicide, EU Ideologies

What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from May 13 to 19 finds a preview snippet on sensible charts from @albertocairo’s upcoming book “How Charts Lie,” @ladatamx’s report on homicides in Mexico, @RepublikMagazin’s analysis on the changing ideologies of political parties in the European Union, and a recap of the Data Journalism UK conference by @paulbradshaw.

Struck by Lightning: A Quick Lesson on Cleaning up Your Data

Being struck by lightning is often used as an example of heavenly retribution because it is so unlikely. Fatalities due to lightning are statistical outliers, since most people struck by lightning survive. So what is the best way to avoid becoming one of these outliers? The following is a step-by-step set of instructions for unpacking a dataset – and being careful about the conclusions we draw.

GIJN’s Data Journalism Top 10: Weak Passwords, Wolf Drama, Chart Chooser, London vs. England

What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from May 6 to 12 finds @SteveFranconeri’s chart chooser based on data formats instead of visualization functions, @daswasfehlt’s examination of Austrian politicians’ weak email passwords in the wake of a major data leak, @NZZ’s look at whether wolves are really a nuisance in Switzerland and @wihbey’s research into the data competence and partisanship of journalists.

GIJN’s Data Journalism Top 10: Populism Popularity, DataViz Pedagogy, National vs. Local Media, German Migration

What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from April 29 to May 5 finds @zeitonline mapping German migration post-reunification, @FILWD pointing out the gaps in current data visualization teaching syllabi, @AlJazeera launching its data journalism introductory guide, and @WSJ highlighting the stark divide between national and local media in the United States.