Data Journalism Course Modules-BAKU
  • Training Module for Data Journalism Course
  • DATA JOURNALISM IN THE NEWSROOM
  • 1. Module introduction
  • 2.The History of Data Journalism
  • 3. Definition of Data Journalism
  • 4.Case studies from Turkey and from other countries
  • Practice
  • 5.Assembling a team for a data journalism project
  • 6.Skills necessary for working with data
  • TELLING STORIES WITH VISUALIZATION
  • 1.Module introduction
  • 2.History of Data Visualization
  • 3.Definition of Data Visualization
  • 4. Basic Principles of Data Visualization
  • 5.Creating good data visualization
  • 6.Matching Data and Graph Types: Interpreting Data Visualizations
  • DATA VISUALIZATION TOOLS
  • 1.Module introduction
  • 2.Using Excel to do data journalism
  • 3.Data journalism basics with Google spreadsheets
  • 4.Simple visualization tools: Infogram, Piktochart, Workbenchdata, Flourish and datawrapper
  • 5.Data visualization: advanced visualizations using Tableau.
  • Resource
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3.Definition of Data Visualization

Previous2.History of Data VisualizationNext4. Basic Principles of Data Visualization

Last updated 5 years ago

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Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that might go undetected in text-based data can be exposed and recognized easier with data visualization software. So it is the process of converting raw data into easily understandable images / photos for fast and effective decision-making.

Graph: (950-Europe BC) The first known quantitative indicator - a multiple time series graph showing the changing position of planets and moons.

Map: (6500 BC), the oldest known map-Çatalhöyük / Konya Museum-Turkey At the beginning of the 20th century, Gestalt Psychologists observed that the perceptual output of elements was more effective than expected when transformed into a shape or symbol. In this context, visualizing data is not new, it is not wrong to state that it has developed with technology over time. Computer-based visualization has also accelerated since 1984.

Roots of Data Visualization Cartography / Cartography Statistics Data Visual Thinking Technology

Types of Data Visualization Linear Visualization Planar Visualization Volumetric Visualization Multi-Dimensional Visualization Hierarchical Visualization Temporal Visualization Conductive Visualization

Data Visualization Process It includes the process of finding, collecting, verifying, cleaning, analyzing and visualizing raw data according to the characteristics of the data set.

Limits of Data Visualization Data Quality: The quality of the data used for visualization is a priority of a good visualization. If the raw data is not of good quality, it may not be possible to visualize it. Clearing and making the data usable is an important process in visualizing the data in this context.

Cause-Result Relationship: Data visualization is often used to show relationships. As it is stated in the introduction, there is no cause-and-effect relationship, but it should be avoided to show that something has happened. Sometimes what is visualized can cause serious mistakes.

Verifiable - Verifiable: Does data visualization involve the process of making sense, collecting, verifying, analyzing, presenting raw data? If it doesn't, it should be questioned. In which respect does it include details such as measuring, analyzing and making decisions? Or is it just beautiful visuals? Knowing them is important.

Visual Ethics Visuals, photographs: affect our thinking, our emotions, our behavior in good and bad ways. Visual ethics is not just digital ethics or visual journalism, advertising, public relations or TV journalism, nor is it to do something uniform by exposing people to visuals. Visual ethics is the nervous system of communication, the "soul" of communication. That is, "The eyes are the mirror of the heart" and this is not ironic.

Why Visual Ethics is Important Seeing is believing What is visualized is more powerful than words & offers more alternatives

Graph: Watch the axes!