Programme overview
Introduction:
Data journalism and visual storytelling, from finding and analysing to charting data stories, is a 1-week course for reporters, desk editors and government or corporate media units that ends with a Data Story Package and Newsroom Data Desk Plan for a case organisation. Many media units publish figures copied from press releases, miss the stories hidden in public datasets and release charts with broken axes or wrong percentages. Nominees already handle numbers in their copy and work hands on in spreadsheet and charting labs with real public datasets. CoreConcept Training Center delivers this data journalism and visual storytelling course.
Course Objectives:
- Locate open datasets, statistical releases and unpublished records and request missing data through freedom of information routes
- Clean, restructure and standardise raw spreadsheets and extracted PDF tables so that figures can be compared reliably
- Analyse datasets with pivot tables, rates, medians and percentage change to surface outliers, trends and story angles
- Select chart types and maps that match the story and design graphics that read correctly on mobile screens
- Check every published number for calculation, axis and correlation errors and document the method behind each data story
- Plan a newsroom data desk with roles, toolkit, request workflow and a pipeline of recurring data stories
Target Audience:
- Reporting staff responsible for turning statistics, budgets and public records into news stories
- Desk editing staff responsible for checking figures, charts and headlines that carry numbers before release
- Government media unit staff responsible for publishing official statistics, performance figures and open datasets for the public
- Corporate communication staff responsible for annual figures, survey results and data-led content on owned channels
- Graphics and digital production staff responsible for charts, maps and interactive tables
Course Outline:
Day 1: Data Journalism Landscape, Story Types and Newsroom Baseline
- Computer-Assisted Reporting and Precision Journalism Roots of Data Reporting
- Simon Rogers Data Project Types From Facts to Investigations
- Martha Kang Seven Data Story Types Applied to Headlines
- Data Literacy Three-Step Routine for Reading Unfamiliar Tables
- Newsroom Data Readiness Audit of Recent Published Figures
Day 2: Data Journalism Workflow Models and Data Sourcing Routes
- Bradshaw Inverted Pyramid Stages From Compiling to Combining Datasets
- Lorenz Data Journalism Process From Scraping to Story Building
- Open Data Portal and Statistical API Search Strategies
- Freedom of Information Request Drafting and Response Tracking Log
- PDF Table Extraction and Web Scraping for Unpublished Records
Day 3: Cleaning, Analysing and Interviewing the Data
- OpenRefine Clustering and Faceting to Standardise Messy Records
- Spreadsheet Pivot Tables, Filters and Formulas for Story Leads
- Percentage Change, Rates per Capita and Median Calculations
- Interviewing the Data Question Log for Outliers and Trends
- Start With the Data Finish With a Story Angle Worksheet
Day 4: Visual Storytelling, Data Ethics and Number Error Risks
- Chart Type Selection Matrix for Comparison, Trend and Distribution
- Choropleth and Proportional Symbol Maps for Local Data Stories
- Interactive Graphic and Searchable Table Design for Mobile Readers
- Misleading Axis, Correlation and Sample Size Error Checklist
- Data Ethics Review for Anonymisation, Privacy and Methodology Notes
Day 5: Lab Build of the Data Story Package and Data Desk Plan
- Lab Exercise Cleaning and Pivoting a Public Spending Dataset
- Lab Exercise Building Charts and a Map for One Story
- Data Story Package Drafting With Methodology Box and Source Files
- Newsroom Data Desk Roles, Toolkit and Request Workflow Design
- Data Story Package and Data Desk Plan Completion and Review
Skills You Will Gain:
- Open Data Sourcing
- Information Request Management
- Spreadsheet Data Cleaning
- Statistical Story Analysis
- Chart and Map Selection
- Interactive Graphic Design
- Numerical Error Checking
- Data Desk Planning
Why Attend This Course:
- Deliver a Data Story Package and Newsroom Data Desk Plan for a case organisation to the head of news or media unit director
- Decide which datasets merit a story, which chart or map suits it and when a figure is too weak to publish
- Avoid public corrections caused by wrong percentages, truncated axes, mismatched units and causal claims drawn from correlation
- Share cleaning recipes, pivot templates, chart selection guides and information request logs with reporting and graphics colleagues
Conclusion:
Back at work, the participant presents the Data Story Package and Newsroom Data Desk Plan to the head of news, the media unit director or the communication manager. They use it to decide which recurring datasets the unit tracks, who cleans, analyses and charts them, and which checks every figure passes before release. After the first data stories published under the plan, the unit should review reader engagement, corrections, turnaround time and request response rates, then adjust desk roles, tools and the story pipeline.
Frequently Asked Questions (FAQ):
What should participants know before a data journalism and visual storytelling course?
Participants should already use numbers in their copy or publications and be comfortable with basic spreadsheet entry. No coding or statistics qualification is needed. Bringing an anonymised dataset or a published chart from their own unit helps them apply the labs to real material.
How does data journalism and visual storytelling differ from a news writing or fact-checking course?
It concentrates on finding, cleaning, analysing and charting datasets to produce stories. News writing courses teach leads, structure and sub-editing, and fact-checking courses teach verifying claims, images and video, while this course builds the spreadsheet, chart and map skills behind data-led reporting.
Why does data journalism and visual storytelling start with cleaning the data?
Raw datasets carry duplicates, inconsistent names, missing values and mixed units that distort every later calculation. Cleaning and documenting each change first means pivot tables, rates and charts rest on sound figures, and the method can be explained to editors and readers.
What do participants take back from the data journalism and visual storytelling course?
Participants take back a Data Story Package and Newsroom Data Desk Plan for a case organisation, with a cleaned dataset, analysis log, chart and map set, methodology box, information request tracker and data desk roles they can adapt to their own unit.