Since the development of computers, CAR has been used by journalists to uncover patterns and trends by examining data. Now, CAR has become a subset of the wider area of expertise known as data journalism – which includes coding, automation, and data visualisation for interactive storytelling.

In our article ‘What is data journalism?‘ we refer to CAR in the context of its role in data journalism. But what is CAR? And how does it differ from data journalism.

• Computer-Assisted Reporting (CAR):
  • Emerged in the late 20th century as journalists began using computers for reporting.
  • Focuses on using databases, spreadsheets, and basic statistical tools to analyse public records, election results, crime reports, etc.
  • Example: A journalist using Excel to analyse government spending records for a piece of investigative journalism.
• Data Journalism:
  • A broader, more modern evolution of CAR that includes data collection, analysis, and data visualisation.
  • Incorporates coding, automation, and interactive storytelling techniques.
  • Often involves using programming languages (Python, R), web scraping, machine learning, and data visualisation tools (Tableau, D3.js).
    • See our ‘Data journalism glossary‘
  • Example: The New York Times’ interactive COVID-19 tracking dashboards or The Guardian’s data-driven investigative reports.
    

Differences between CAR and data journalism:

In short, CAR is an early form of data journalism. While CAR was about using computers for analysis, data journalism has expanded to include sophisticated digital tools, coding, and visual storytelling techniques.

Related articles

What is data journalism?

Good journalism has always been about data

Data journalism – resources and tools

Data journalism glossary

The post Computer-assisted reporting (CAR) first appeared on Media Helping Media.

We have compiled a list of some of the leading resources and tools that are available for those starting out in data journalism.

This list will be updated over time. You might want to consult our Data journalism glossary to look up some of the terms that appear below.

Tools;

Below is a list of tools used by data journalists. They cover data gathering, cleaning, analysis, and visualisation. These tools are great for both beginners and experienced data journalists:

Data collection & scraping tools

• Tabula: (Extract tables from PDFs) https://tabula.technology/
• Web scraper Chrome extension: (Browser-based web scraping tool) https://www.webscraper.io/
• Google Sheets: ImportXML, ImportHTML, and ImportData functions are powerful for scraping web data. https://www.google.com/sheets/about/
• Wayback Machine: For finding historical web data or removed pages https://archive.org/web/

Data cleaning & preparation

• OpenRefine: Powerful tool for cleaning messy datasets and transforming formats. https://openrefine.org/
• Trifacta Wrangler (Cloud free version): Data cleaning and shaping tool (registration required) https://www.trifacta.com/products/wrangler/
• Open Data Institute Labs: Validate CSV files for errors and formatting issues. https://csvlint.io/

Data visualisation tools

• Datawrapper: Create charts, maps, and tables easily. https://www.datawrapper.de/
• Flourish: Interactive graphics and storytelling visuals. https://flourish.studio/
• Chartbuilder: (Quartz’s open-source chart tool) https://github.com/Quartz/Chartbuilder
• RawGraphs: Great for creating complex data visualisations (exports as SVG). https://app.rawgraphs.io/
• Tableau Public: A powerful data visualisation tool that allows you to create interactive dashboards and visualisations. The public version is free for public data. https://www.tableau.com/solutions/web-data-sources

Mapping tools

• Google My Maps: Simple mapping tool for plotting points or routes. https://www.google.com/maps/d/
• Kepler.gl: Advanced geospatial analysis and visualisations. https://kepler.gl/
• QGIS (Free, open-source GIS software): Desktop software for serious mapping projects. https://qgis.org/en/site/

Data analysis & statistics tools

• Google Sheets: Built-in analysis, pivot tables, and scripting. https://www.google.com/sheets/about/
• Python (with pandas, matplotlib, seaborn): Free programming tools for serious data analysis. https://www.python.org/
• R Project (Statistical computing and graphics): https://www.r-project.org/

Fact-checking & verification tools

• TinEye: Reverse image search for verifying photos. https://tineye.com/
• Google Fact Check Explorer: Search verified fact-checks globally. https://toolbox.google.com/factcheck/explorer

Other handy tools

• TimelineJS: Create interactive timelines. https://timeline.knightlab.com/
• StoryMapJS: Tell stories with maps and multimedia. https://storymap.knightlab.com/
• Otter.ai (Free tier for transcription): https://otter.ai/
• Excalidraw: Sketch quick diagrams or workflows. https://excalidraw.com/
• Jupyter Notebooks: An open-source web application that allows you to create and share documents that contain live code, equations,  visualisations, and narrative text. https://jupyter.org/

Tools for specialist reporters and correspondents

• Climate, environment & energy
  • Global Forest Watch: Deforestation and land-use data, interactive maps https://www.globalforestwatch.org/
  • NASA Earthdata: Access satellite imagery, climate, and environmental datasets. https://earthdata.nasa.gov/
  • Carbon Brief: Data-driven analysis on climate science and energy policy. https://www.carbonbrief.org/
  • Climate Data Online (NOAA): U.S. climate data including historical weather records. https://www.ncdc.noaa.gov/cdo-web/
• Health, medicine & pandemics: 
  • World Health Organization (WHO) Data: Global health statistics and disease surveillance. https://www.who.int/data
  • Our World in Data (OWID): COVID-19, vaccines, and global health datasets. https://ourworldindata.org/
  • CDC Data & Stats: U.S. public health datasets including mortality, diseases, and surveillance. https://data.cdc.gov/
  • IHME Global Health Data: Health metrics and disease burden visualisations. https://www.healthdata.org/
• Finance, business & economy
  • U.S. Securities and Exchange Commission (SEC) EDGAR Database: Corporate filings, financial reports, executive compensation. https://www.sec.gov/edgar.shtml
  • World Bank Open Data: Economic and development datasets globally. https://data.worldbank.org/
  • IMF Data Portal: Macroeconomic and financial data from the International Monetary Fund. https://data.imf.org/
  • OpenCorporates: Global corporate registries and company data. https://opencorporates.com/
• Crime, justice & human rights
  • Bureau of Justice Statistics (U.S.): Criminal justice datasets, prison data, and law enforcement stats. https://bjs.ojp.gov/
  • UN Office on Drugs and Crime (UNODC): Global crime, drug, and human trafficking data. https://dataunodc.un.org/
  • The Marshall Project – Data Resources: Journalism and data on criminal justice in the U.S. https://www.themarshallproject.org/
• Politics, elections & government transparency
  • Google Public Data Explorer: Visualisation of world development, economy, and politics datasets. https://www.google.com/publicdata/directory
  • U.S. Census Bureau: Demographic, housing, and political district data. https://data.census.gov/
  • OpenSecrets: U.S. campaign finance, lobbying, and political donation tracking. https://www.opensecrets.org/
  • VoteSmart: Track political candidates, voting records, and campaign donors. https://justfacts.votesmart.org/
• General data search & repositories
  • Google Dataset Search: Search datasets across thousands of open data portals. https://datasetsearch.research.google.com/
  • Kaggle Datasets: Public datasets for machine learning, data journalism, and analysis. https://www.kaggle.com/datasets
  • U.S. Data.gov: Access to open datasets from U.S. government agencies. https://www.data.gov/
  • Humanitarian Data Exchange (HDX): Global crisis and humanitarian data. https://data.humdata.org/

Considerations for using free tools:

• Data privacy: Be mindful of data privacy when using free tools, especially when working with sensitive information.
• Learning curves: Some powerful free tools might have a steeper learning curve than paid alternatives.
• Community support: Look for tools with active communities, as this can provide valuable support and resources.

By combining these free resources, you can build a strong foundation in data journalism without breaking the bank.

Websites:

• The Data Journalism Handbook / European Journalism Centre (EJC)
  • Website: https://datajournalism.com/
• International Consortium of Investigative Journalists (ICIJ)
  • Website: https://www.icij.org/
• The Center for Investigative Reporting / Reveal
  • Website: https://revealnews.org/
• The Investigative Reporters and Editors (IRE)
  • Website: https://www.ire.org/
• Global Investigative Journalism Network (GIJN)
  • Website: https://gijn.org/
• Reuters Institute for the Study of Journalism (RISJ):
  • Website: https://reutersinstitute.politics.ox.ac.uk/
• Pew Research Center:
  • Website: https://www.pewresearch.org/
• Columbia Journalism School – Tow Center for Digital Journalism:
  • Website: https://journalism.columbia.edu/
• Bellingcat:
  • Website: https://www.bellingcat.com/
• Datawrapper Academy
  • Website: https://blog.datawrapper.de/
• Knight Center for Journalism in the Americas
  • Website: https://journalismcourses.org/
• R Journalism (Subreddit for Data Journalism)
  • Website: https://www.reddit.com/r/DataJournalism/
• OpenNews
  • Website: https://opennews.org/

Related articles

Good journalism has always been about data

Data journalism glossary

What is data journalism?

The post Data journalism – resources and tools first appeared on Media Helping Media.