Data Journalism
Programme
7-8 May 2012
European Broadcasting Union, Geneva, Switzerland
M aster Class
Trainer
Kevin Anderson is a journalist, journalism trainer and digital strategist. After starting his journalism career in newspapers, Kevin shifted to digital journalism in 1996. In 1998, he became the first online journalist for the BBC outside of the US, based in the BBC's flagship Washington bureau. He joined The Guardian in 2006 as their first blogs editor. Two years later, he became digital research editor at the newspaper, helping identify and implement new technologies to support the newspaper's world-class journalism. Since March 2010, he has been an independent journalist and strategist. He works with journalists and news organisations around the world, including Al Jazeera and Reed Business Information, to help prepare them for the digital future.
Objectives
− Review the fundamental skills you need both to plan and execute your stories based on data journalism.
− Get acquainted, through tutorials and practical exercises, with the tools needed to quickly " mine" , analyse and visualize data.
− Get inspired by and learn from successful data journalism stories
Monday 7 May
During the first day of the course, w e’ll be w orking w ith pre-selected data sets. In day 2, w e’ll be w orking w ith data sets that you have brought or have found.
13:00 - 13:30 Module 1: W hat is data journalism? − The history of data in journalism
− Computer-assisted reporting
− What is data journalism?
o Tools and techniques that help you manage and make sense of small and large sets of data
o Tools that help you uncover patterns
o Tools and techniques that help you tell award-winning stories − What’s driving the data journalism revolution?
o The rise of the data mash-up
o Better, easier tools (both for analysis and visualisation) o The public data revolution
o Crowdsourcing
Discussion: What data projects are you currently working on? What projects would you like to do?
13:30 --- 13:45 W elcome − Tour de table
M aster Class
13:45 - 14:15 Module 2: Statistics: Common pitfalls and how to avoid them − Data journalism requires an understanding of statistics.
o Not your average average o Percentage abuse
o Sample size
o Dig deeper than national statistics
14:15 - 15:15 Module 3: Spreadsheets: The data journalist’s key tool − Excel, Open Office, Zoho and Google Docs
o Excel versus online spreadsheets
o How to create an online spreadsheet and enter your data o Formatting data - dates, currencies and regional formats o Basic calculations
o Web-only features of online spreadsheets o More complex calculations
o Choosing the right chart
o How to create simple charts and graphs Exercise: Create a chart or charts using our sample data
15:15 --- 15:30 Coffee break
15:30 - 16:30 Module 4: Other data tools: Google Fusion charts & Pivot Tables − Google Fusion charts, a great tool for raw data
o Exporting data from Google Spreadsheets and Fusion Tables.
o The difference between Google Fusion Tables and Google Spreadsheets. o Uploading data into Google Spreadsheets and Google Fusion tables. o Raw data versus processed data.
o Filters and aggregation in Google Fusion Tables. o How to identify ‘dirty data’
Exercise: Look for other patterns in this data. What other aspects would you look at? What other patterns do you find? What questions did your analysis raise?
− Pivot tables: A powerful tool for analysing data
Filters and aggregation in Fusion Tables are a simplified version of pivot table reports in spreadsheets.
While aggregation in Fusion Tables allows you to easily analyse one dimension of a data set, pivot table reports allow you to
o How to analyse data in multiple dimensions using pivot tables in Google Spreadsheets.
o Pivot tables in Excel (and OpenOffice)
Exercise: Using this set of raw data, use pivot tables to analyse the data. Think of different aspects of the data that you want to analyse.
M aster Class
16:30 - 17:00 Module 5: How to use data in your newsroom
A look at how data desks are organised in newsrooms with examples of the Australian Broadcasting Corporation and The Guardian.
Discussion: Does your news organisation currently have a data team? If you do projects using data, how are they currently done?
17:00 - 17:30 Module 6: How to find your own data
A look at
− Different data formats.
− National and European data sources.
− Generating data sets using Eurostat.
− Data search tips using Google.
Exercise:Find two data sets which you will use for the rest of the course. At least one of the data sets much include location.
19:00 Netw orking dinner at the Café du Soleil, Petit-Saconnex, Geneva
21:30 End of Day 1
Tuesday 8 May
In Day 2, w e’ll move on to advanced concepts and put some of the ideas from yesterday in action
09:00 --- 09:15 Review of Day 1 and objectives of Day2 09:15 - 10:30 Module 7: Analysing data sets
− Is your data clean?
− Will you need to focus on a certain area of your data?
− Will you need pivot tables or can you simply use some basic analysis using a spreadsheet?
− What are the patterns in your data?
− What chart does your analysis lend it to?
− What reporting do you still need to do? What questions is your data asking?
10:30 - 11:30 Module 8: Creating maps
− Batch Geo. An easy tool to map data.
− Zeemaps: Mapping multiple points with your data
− Google Fusion Tables powerful mapping tools.
M aster Class
11:30 --- 11:45 Coffee break
11:45 - 12:30 Module 9: Tableau Public: A power visualisation tool − Tableau Public is a special tool for visualising data.
o Opening data in Tableau Public. o Example 1: mapping earthquake data o Example 2: US closure data
− Creating a data dashboard.
12:30 - 13:00 Closing discussion: What projects are you now inspired to do?
13:00 --- 13:15 W rap-up
− Key learning points
− Evaluation
13:15 End of the M aster Class
Contact
Hélène Rauby-M atta
Business Development Manager EBU TRAINING
L’Ancienne Route 17A 1218 Grand Saconnex GE Switzerland T +41 22 717 24 21 F +41 22 747 44 21 w w w .ebu.ch/training @ebutraining
