Data journalism

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Using data analysis and visualization to find and report on news stories, and the tools and techniques for collecting and interpreting data.

Data analysis: Learning how to work with data, clean, process and analyze it using programs like SQL, Python or R.
Visualization: Techniques to represent data in a visual format that helps understand data and reveal patterns and trends in data.
Statistics: Understanding the basic principles of probability and statistical analysis, as well as interpreting numerical data and dealing with uncertainty of results.
Ethics: The importance of ethical considerations in data journalism, including privacy, transparency, copyright laws, and accuracy.
Digital Literacy: Understanding the modern communication landscape, and the use of social media, blogs, and other digital platforms to collect and present data.
Research: Learning techniques to investigate data and find sources, as well as sourcing data from government and other public sources.
Storytelling: Conveying the story of data through write-ups, visualizations, multimedia presentations, and other communication tools.
Narrative Journalism: The practice of telling stories through data, including narrative structure, character, and plot threads.
Data Journalism Tools: Learning how to use tools like Tableau, Excel, Google Sheets or data visualization software like Flourish, Chartbeat, or Datawrapper.
Investigative Journalism: Techniques and processes of investigating data, fact-checking, cross-referencing and the criteria for reliable sources.
Audience Engagement: Techniques to engage and interact with the audience, build trust, and crowdsourced journalism.
Different Sources of Data: Access and analysis of different sources of data, including data from government, industry, public opinion polls, and other social surveys.
Investigative Journalism: Investigative Journalism is all about digging deep and analyzing data sets to expose the hidden truths and hold the powerful accountable.
Visual Journalism: Visual journalism is a popular form of data journalism that utilizes charts, graphs, and other visual representations of data.
Sports Journalism: Sports journalism uses data to analyze and showcase the performance of athletes, teams, and leagues.
Political Journalism: Political journalism focuses on analyzing and visualizing government and political data.
Social Media Journalism: Social media journalism tracks online conversations on different social media platforms, identifies trends and narratives, and analyzes their impact.
Environmental Journalism: Environmental journalism deals with data relating to climate change, pollution, and other environmental issues.
Health Journalism: Health journalism uses data to highlight important issues and help readers make more informed decisions about their health.
Educational Journalism: Educational journalism focuses on analyzing and visualizing education data, including K-12 and higher education data.
Financial Journalism: Financial journalism analyzes and visualizes data about financial markets, stocks, commodities, and more.
Crime Journalism: Crime journalism utilizes data to highlight crime trends and patterns in different geographies, and places that fit the narrative of crime.
Business Journalism: Business journalism analyzes and visualizes data sets relating to different industries, such as retail, real estate, and manufacturing, and how they interact and grow.
Data Visualization Journalism: Data visualization journalism is a growing field that focuses on visualizing data in creative and innovative ways to tell compelling stories.
Photojournalism: Photojournalism uses data visuals to tell stories with the help of photographs.
Car Journalism: Car journalism utilizes data to analyze and test the performance of different car models, and identify the best choices for consumers.
Travel Journalism: Travel Journalism utilizes data to showcase and highlight the performance of tourist zones, hotels, travel seasons, and their impact on the economy.
- Quote: "Data journalism or data-driven journalism (DDJ) is journalism based on the filtering and analysis of large data sets for the purpose of creating or elevating a news story."
- Quote: "Data journalism reflects the increased role of numerical data in the production and distribution of information in the digital era."
- Quote: "It involves a blending of journalism with other fields such as data visualization, computer science, and statistics, 'an overlapping set of competencies drawn from disparate fields'."
- Quote: "Many data-driven stories begin with newly available resources such as open source software, open access publishing and open data, while others are products of public records requests or leaked materials."
- Quote: "This approach to journalism builds on older practices, most notably computer-assisted reporting (CAR) a label used mainly in the US for decades."
- Quote: "Data-driven journalism strives to reach new levels of service for the public, helping the general public or specific groups or individuals to understand patterns and make decisions based on the findings."
- Quote: "The findings from data can be transformed into any form of journalistic writing."
- Quote: "Visualizations can be used to create a clear understanding of a complex situation."
- Quote: "Furthermore, elements of storytelling can be used to illustrate what the findings actually mean, from the perspective of someone who is affected by a development."
- Quote: "This connection between data and story can be viewed as a 'new arc' trying to span the gap between developments that are relevant, but poorly understood, to a story that is verifiable, trustworthy, relevant, and easy to remember."
- Quote: "The process builds on the growing availability of open data that is freely available online and analyzed with open source tools."
- Quote: "Data-driven journalism strives to reach new levels of service for the public, helping the general public or specific groups or individuals to understand patterns and make decisions based on the findings."
- Quote: "Other labels for partially similar approaches are 'precision journalism', based on a book by Philipp Meyer, published in 1972, where he advocated the use of techniques from social sciences in researching stories."
- Quote: "Telling stories based on the data is the primary goal."
- Quote: "This approach to journalism builds on older practices, most notably computer-assisted reporting (CAR) a label used mainly in the US for decades."
- Quote: "Many data-driven stories begin with newly available resources such as open source software."
- Quote: "Data-driven journalism might help to put journalists into a role relevant for society in a new way."
- Quote: "Furthermore, elements of storytelling can be used to illustrate what the findings actually mean, from the perspective of someone who is affected by a development."
- Quote: "Visualizations can be used to create a clear understanding of a complex situation."
- Quote: "Many data-driven stories begin with newly available resources such as open access publishing."