ASOCEU - Lesson 2 - Data Journalism Part Two (slides)
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This document provides examples and guidance for conducting data journalism investigations and projects. It discusses investigating major public investments by looking at factors like why and how they were funded, timeline of development, and impact. It then presents a checklist for data journalism, including hunting for relevant data, cleaning and formatting data, analyzing data through sorting, filtering, and visualization, enriching data with additional context, and developing the story. Finally, it provides a quick guide of necessary steps for a data journalism project, from selecting a topic to collecting and analyzing data to visualizing findings and developing the narrative.
ASOCEU - Lesson 2 - Data Journalism Part Two (slides)
- 1. WHAT IS DATA JOURNALISM (part two)
- 2. WHAT IS DATA JOURNALISM (part two)
- 3. SOME EXAMPLES: DATA JOURNALISM INVESTIGATIONS Major public investments ● Often made in capital cities and also small centres ● They concern infrastructure designed and financed by one or more institutions, with long fulfilment times ● Very often have a complex and articulated path of development, from planning to completion
- 4. SOME EXAMPLES: DATA JOURNALISM INVESTIGATIONS Looking further into projects ● Why were they financed? ● Which indicators led to them happening? ● Which funds were set aside and by whom? ● How they developed compared to schedule? ● What problems arose? ● What was their impact on the territory? Can it be measured?
- 5. THE DATA JOURNALISM CHECKLIST
- 6. THE DATA JOURNALISM CHECKLIST Hunting for data ● What data can be most helpful for your research? ● Are there public institutions that make the data available to all online (OpenData)? ● Are there official archives on the issue?
- 7. THE DATA JOURNALISM CHECKLIST The data format ● Are the data you have found structured? Can you open them in a spreadsheet? ● Should you then construct the table starting from the data that you found in other formats (PDF, HTML)?
- 8. THE DATA JOURNALISM CHECKLIST Cleaning data ● Are the data you have found well formatted? ● Check the data: are they homogeneous or written differently? ● Are the data subdivided coherently in columns or are they disordered? ● Are there blank or empty cells? Why?
- 9. THE DATA JOURNALISM CHECKLIST Analyse the data ● Sort the data from the highest value to the smallest (equivalent of a classification) ● Filter the data in order to focus only on data of interest (Territory? Type?) ● Group the data using a pivot table to measure them quantitatively
- 10. THE DATA JOURNALISM CHECKLIST Enrich the data ● Do you have addresses? Find the geographic coordinates to build a map ● Want to compare multiple territories? Build a statistical indicator to classify them and find out a phenomena’s impact ● Is there a list of municipalities in your data? Enrich the data by adding a Province column
- 11. THE DATA JOURNALISM CHECKLIST Visualise ● Want to build a classification? The bar chart is the most suitable ● Can the data be added together? Then a pie chart is ideal ● Want to show the trend of a phenomenon over time? The best choice is a line graph ● Got geographical data? Create a map
- 12. THE DATA JOURNALISM CHECKLIST Analyse ● What is the context of the data? Are there particular events that allow us to understand them better or what they compare with? ● Are there other data or other information that you can find to enrich your research? ● Can there be correlations between different data?
- 13. THE DATA JOURNALISM CHECKLIST Storytelling ● It is important to be precise, cite sources and explain the research method ● Add some creative spice to the narrative to make it captivating ● Know who you are telling the story to and which is the most appropriate language, also based on the media used
- 14. QUICK GUIDE: THE NECESSARY STEPS FOR DEVELOPING THE PROJECT
- 15. QUICK GUIDE: THE NECESSARY STEPS FOR DEVELOPING THE PROJECT Which phenomenon is being analysed? Which project? 1 Collect data: which will be useful? Where can we find them? Are the data collected structured? Should they be re- cleaned? What do they tell us? 3 We visualise the data to understand them better, it can help for the analysis 4 Check new data and information: does it help to aggregate them with other data? What answers are in the data? Our story starts here: let’s tell it! 5 6 2
- 16. WHAT IS DATA JOURNALISM (part two)