GIJN’s Data Journalism Top 10: Plastic Mountains, #SharpieGate, Stopwatch Analysis, Collaborative Software

What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from September 9 to 15 finds ProPublica open-sourcing its collaborative reporting software; CityLab interviewing Mark Monmonier, author of “How to Lie With Maps,” on Donald Trump’s deceptive hurricane map; Al Jazeera surveying South Sudan’s citizens on displacement; and Reuters visualizing just how bad the Earth’s problem is in terms of single-use plastics.

Data Journalism on Indigenous Communities

The absence or poor quality of data on Indigenous communities presents both challenges and opportunities for data journalism. Because it is widely recognized that official data on Indigenous communities is faulty or sparse, reporters may need to look for alternative sources, or even create it themselves. Although data journalism commonly refers to the use of existing data, it also can mean filling a data void. Creating data is more work, but the results can be impressive, unique, and highly impactful. This GIJN/NAJA guide will:

Look at some of the issues concerning the available data on Indigenous people
Discuss alternative sources of data
Provide information on learning about data journalism
Review data journalism tools
Suggest some of the official places to look for data

Problems with National Data
Complaints about the data on Indigenous peoples are similar around the world.

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 in 2018: Visual Vocabulary, Eclectic Visualization, Google Dataset Search, Laughing in Parliament

It’s been a great year for data journalism and visualizations. GIJN’s Top 10 #ddj series captured snapshots of what’s popular on Twitter among the global data journalism community for 46 weeks in 2018. For this edition, we asked NodeXL to map 2018’s most popular #ddj tweets from January 1 to December 11 and the results are in. This year’s most popular tweets include @FinancialTimes’ ever-popular Visual Vocabulary chart, @Google’s Dataset Search, @hnrklndbrg’s eclectic visualizations, and @SZ’s analysis of Germany’s parliamentarians using laughter as a debate weapon.

GIJN’s Data Journalism Top 10: German Heat, Austrian Arms, Quebec School Fees and Salvadoran Kidney Disease

What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from Sept 3 to 9 finds @FiveThirtyEight attacked by the green-eyed monster with their equivalent of Bloomberg’s “Jealousy List,” @daswasfehlt breaks down Austria’s export of arms, @GoogleAI announces the beta launch of Google Datasets Search, and @SZ documents how climate change is wreaking havoc on temperatures in Germany but boosting ice-cream sales.

GIJN’s Data Journalism Top 10: Dam Disaster in Laos, Global Star Gazing, Why We Love Pie Charts

What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from July 23 to 29 finds @NadiehBremer visualizing beautiful constellations imagined by different cultures, @mslima diving deep into why we love pie charts, @leigh_tami18 explaining the various methods of joining datasets and the Reuters Graphic’s team visualization of the dam disaster in Laos.

GIJN’s Data Journalism Top 10: Democratic Data, Berlin’s Bicycles and Cricket Crazy

What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from April 16 to 22 finds @camellia_will debating the future of data portals, @DLeonhardt using hard data to show whether Democratic or Republican presidents have been more fiscally responsible and @morgenpost mapping bicycle thefts hotspots in Berlin.

GIJN’s Data Journalism Top 10: Ethics, Awards and Open Source for IJ

What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from April 9 to 15 finds an ultra useful data visualization tool that is perfect for non-programmers by @Adobe and @GeorgiaTech, a list of 99 amazing data journalism works by @GENinnovate’s Data Journalism Awards nominees and @CARTO shares 50 experts on location intelligence to follow.

This Week’s Top 10 in Data Journalism

What’s the global data journalism community tweeting about this week? Our NodeXL #ddj mapping from December 4 to 10 has @Reuters documenting the deplorable living conditions at refugee camps in Bangladesh, Financial Times’ @theboysmithy transforming bad charts into useful ones and the impressive work of the 2017 @infobeautyaward winners.