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The State of Data Journalism Survey 2023

What are the biggest trends and challenges for data journalists worldwide? The answers can be found by checking out the latest results from our 2023 annual industry survey.

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Our original Long Reads, written by the best data experts

Covering issues

Climate change through a solutions and data lens

How solutions storytelling can engage local communities and bring local reporters together to solve the climate crisis.

Data visualisation

New climate metrics for new climate conversations

New metrics and visualisations are being developed by a multidisciplinary team of researchers, designers and journalists to reshape how we interpret the climate crisis and its impact on people's daily lives.

Data collection

Data gives voice to women on climate change

Scientific evidence clearly shows that women bear the brunt of climate change, yet until recently, scant attention has been paid to their plight. In many instances, the data are there, waiting to be discovered.

Case studies

Kill switch: reporting on and during internet shutdowns

What can data journalists do to report on Internet shutdowns, which are becoming increasingly common by governments? This article provides a guide with real-world examples you can use to raise your voice.

Data analysis

Putting data back into context

Data are never neutral ‘givens’, but always situated in a particular context, collected for a particular reason -- and it’s crucial that data journalists understand these.

Data visualisation

The unspoken rules of visualisation

Designers often follow a set of strict conventions when creating visualisations. Kaiser Fung examines the fundamental rules of data visualisation, why they are important, and when it is okay to break them.

Covering issues

Reporting beyond the case numbers: How to brainstorm COVID-19 data story ideas

While many journalists around the world report the daily infection rate and death toll of COVID-19, audiences are seeking other stories that show the impact of the virus on their lives. How can journalists tell those wider stories with data?

Data visualisation

The essential lies in news maps

In order to display three-dimensional world we live in, journalists are forced to distort reality. And every map does so in its own way. Maarten Lambrechts looks at commonly used maps and how to avoid being misled by them.

Data visualisation

The essential lies in news maps

In order to display three-dimensional world we live in, journalists are forced to distort reality. And every map does so in its own way. Maarten Lambrechts looks at commonly used maps and how to avoid being misled by them.

Data analysis

Putting data back into context

Data are never neutral ‘givens’, but always situated in a particular context, collected for a particular reason -- and it’s crucial that data journalists understand these.

Data analysis

Spreadsheets for journalism

Many journalists see themselves as “word people” and shy away from writing about numbers. Brant Houston shows how to embrace math with an overview of spreadsheets and functions for beginners.

Data visualisation

Ethics

Designing data visualisations with empathy

How do you get audience members, much less the journalists presenting a story, to walk a mile in the shoes of a dot? Or a bar chart? P. Kim Bui provides three approaches for achieving empathy in data visualisations.

For Disinformation And Media Manipulation

The latest edition of the Verification Handbook arrives at a critical moment. Today’s information environment is more chaotic and easier to manipulate than ever before. This book equips journalists with the knowledge to investigate social media accounts, bots, private messaging apps, information operations, deep fakes, as well as other forms of disinformation and media manipulation.

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The first resource of its kind, it builds on the first edition of the Verification Handbook and the Verification Handbook for Investigative Reporting.

The book is published by the European Journalism Centre and supported by Craig Newmark Philanthropies.

Towards a Critical Data Practice

What is data journalism? What is it for? What might it do? What opportunities and limitations does it present? Who and what is involved in making and making sense of it?

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The new edition of the Data Journalism Handbook explores new and innovative ways in which data is analysed, created and used in the context of journalism. And beyond that: it also reflects on the social, cultural, political and economic circumstances in which data journalism is embedded.

How journalists can use data to improve the news

When you combine the sheer scale and range of digital information now available with a journalist’s "nose for news" and her ability to tell a compelling story, a new world of possibility opens up. Explore the potential, limits, and applied uses of this new and fascinating field.

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This valuable handbook has attracted scores of contributors since the European Journalism Centre and the Open Knowledge Foundation launched the project at MozFest 2011. Through a collection of tips and techniques from leading journalists, professors, software developers, and data analysts, you’ll learn how data can be either the source of data journalism or a tool with which the story is told—or both.

A Guide To Online Search And Research Techniques For Using UGC And Open Source Information In Investigations

Based on the conclusions of the first book, this second edition of the Verification Handbook sheds light on the use of open data and open source information to produce critical journalistic investigations.

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As new challenges have emerged in the digital sphere, wider opportunities to carry out more comprehensive investigations have arisen as well. The authors of the book take the reader on a walk-through to hone their online investigation tactics, providing them with step-by-step guidance to apply research, fact-checking, and data journalism techniques.

A Definitive Guide To Verifying Digital Content For Emergency Coverage

The first edition of the Verification Handbook has become a definitive reference for professionals worldwide. This book laid the foundations for the process of digital content verification and opened a necessary debate about the steps to follow for ensuring the accuracy of reporting within emergency situations.

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Used by educators and journalists of any level, this pioneering book is an essential read for learning about the best-practices for verifying user-generated content and developing appropriate verification processes.

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Detailed courses and expert interviews for all workflow levels

Quality journalism
Countering hate speech

Julia Mozer

Video course
Fundamental search for journalists

Vincent Ryan

Coding
Python for journalists

Winny de Jong

Best practices
When to hire a data journalist

Winny de Jong

Coding
Python for journalists

Winny de Jong

Covering issues
Doing Journalism with Data: First Steps, Skills and Tools

Paul Bradshaw, Steve Doig, Simon Rogers, Nicolas Kayser-Bril, Alberto Cairo

Video course
Fundamental search for journalists

Vincent Ryan

Data collection
Cleaning Data in Excel

Maarten Lambrechts

Coding
Python for journalists

Winny de Jong

Covering issues
Doing Journalism with Data: First Steps, Skills and Tools

Paul Bradshaw, Steve Doig, Simon Rogers, Nicolas Kayser-Bril, Alberto Cairo

Data visualisation
Charting Tools for the Newsroom

Maarten Lambrechts

Data analysis
Going Viral Using Social Media Analytics

Stijn Debrouwere

Learn data journalism through the power of community

Join the other 9,000 members to participate in our community, to exchange ideas and stay up-to-date with the latest on data journalism.

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"Hi I am Francis from South Sudan"

"with open('reactorUnit.csv', 'w', newline='') as myFile: for row in table.find_all('tr'): cells =..."

"I think we should replace df = df.drop('Unnamed: 0', 1) --> I think it is no longer in use. with del..."

"When I wrote and run 'import pandas as pd' from jupyter it gives the following error: ModuleNotFoundError ..."

"Very interesting! Thank you!"

"When I wrote and run 'import pandas as pd' from jupyter it gives the following error: ModuleNotFoundError ..."

"with open('reactorUnit.csv', 'w', newline='') as myFile: for row in table.find_all('tr'): cells =..."

"Can I use Colaboratory instead of Conda? How would I apply it for that?"

17500+

Registered data journalism students, from all over the world

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Over 27 hours of quality free video courses to watch and follow

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70 hours of reading material, including 5 Handbooks and Long Reads

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Content from contributors and experts in their field