LogoLogo
The Fundamentals of Data-driven Storytelling
The Fundamentals of Data-driven Storytelling
  • About this course
    • Course Introduction
  • Module 1 - Find
    • 1.1 How to Find Data for Storytelling and journalism
      • Starting with a question
      • Open data portals and platforms
      • Other sources of data
    • 1.2 How to get better data from a Goolge Search
      • Searching for filetypes and formats
      • More on Advanced Search operators
      • Other common Google Search operators
    • 1.3 Sourcing your own data
      • Creating a Google Form for Research
      • Creating a questionnaire with TypeForm
      • Using quizzes and comments as a sources of data
  • Module 2 - Get
    • 2.1 Turning websites and PDFs into machine readable data
      • Scraping data with Tabula
    • 2.2 An introduction to spreadsheet software
      • Google Sheets, Microsoft Excel and Libre Office Calc.
      • Finding your way around a spreadsheet
      • Simple web scraping with Google Sheets
  • Module 3 - Verify
    • 3.1 Can I use this data in my work?
      • Initial steps for verification
      • What do these column headings mean?
  • Module 4 - Clean
    • 4.1 What to do with disorganised data?
      • Why is clean data important?
      • Keep your data organised
      • Cleaning data cheatsheet
  • Module 5 - Analyse
    • 5.1 What is the story within the data?
      • Spreadsheet rows, columns, cells and tabs
        • Spreadsheet formats, forumlas and essential shortcuts
          • Using the VLOOKUP Function
            • Combine Data From Multiple Spreadsheets
    • 5.2 How to turn numbers into stories
  • Module 6 - Visualise
    • 6.1 Ways we visualise data
    • 6.2 Why we visualize Data
    • 6.3 How to visualise data
  • Course Testing & Feedback
    • ⏱️Quick course exam
    • 🎓Extended course exam
    • 📝Survey and feedback
Powered by GitBook
On this page
  • The fundamentals of data-driven storytelling
  • The stages of the data-driven storytelling pipeline
  1. About this course

Course Introduction

Next1.1 How to Find Data for Storytelling and journalism

Last updated 2 years ago

Data journalism, or data-driven storytelling, means using data in order to generate ideas or angles for a story, or adding context for readers through the use of data. Often, but not always, a data story will help raeders to understand the data by presenting it visually, in charts, graphs or diagrams.

Even if you do not work as a data journalist or in a visual medium, data literacy is essential for all journalists and storytellers today. You can find our Fundamentals of Data Literacy course here.

The fundamentals of data-driven storytelling

Working with data for storytelling can be intimidating at first. Where do you start, and what happens if you can't find the data you need in the format you need?

To help newcomers organise their work and avoid becoming overwhelmed, many professionals (including OpenUp) recommend a framework called "the data storytelling pipeline". The image of a pipeline is useful, because it allows us to divide up the process of working with data into discrete and understandable stages.

The stages of the data-driven storytelling pipeline

The pipeline is presented as a sequential of things to do: you start with the investigative question and finish with a packaged data narrative. It's important to remember that this is just a metaphor, however. In reality, it's unlikely that many endeavours will follow it in a linear manner, and you will likely need to go back a few steps in order to progress at times.

In fact, you can also visualise the data-driven storytelling pipeline as a flow chart with points highlighted that indicate where decisions about data must be made.

This course uses the pipeline metaphor as module headings. Read on to find out more about how to find data.