Getting Started with Data Journalism

0

Data storytelling is now an essential skill in the toolkit of any journalist and one which supports in-depth reporting and sustained engagement with readers. Tailored specifically for Irish journalists, this hands-on training course will equip journalists with the ability to find, analyse and visualise data using commonly available software tools. The course will particularly suit journalists and freelancers seeking to up-skill and those seeking to establish a data analysis team within a traditional news room.

Getting Started with Data Journalism

Divided over two-days, each expert-led two-hour session will include guided instruction, practice case studies, and personalised feedback. For reference during and after the course, participants will receive a resource pack with detailed ‘how to’ guides, practice examples, case studies and statistical and mathematic principles for journalists.

Exploring Data Journalism: This opening session will introduce participants to the range and variety of data journalism. Participants will learn about some of the earliest examples of data journalism and what the field looks like today. Going through notable examples of data journalism and exploring that data will start the discussion on how data is crucial to the future of this industry.

Learning Objectives:

  • Online resources
  • ‘Open data’ sources
  • Google’s potential through Google maps and Google trends
  • Social media data
  • Interactive examples from the top in the industry

Working with MS Excel: MS Excel is a powerful tool for organizing and analyzing data and for preparing data to import into other tools. Working with data sources relevant to Irish journalism, participants will learn how to import and work with data in spreadsheets.

Learning Objectives:

  • Import datasets to Excel
  • Use basic functions in Excel
  • Clean and prepare an Excel spreadsheet for analysis (sort, filter etc.)
  • Apply functions for descriptive analysis (average, max, min, correlation etc.)
  • Apply functions for inferential analysis (t-test)
  • Create pivot charts

Principles of Data Storytelling I: This hands-on session will utilize the learnings from the previous Excel session and put those skills into practice. Participants will move from story conception to completion and learn some useful tools and skills along the way.

Learning Objectives:

  • Investigate a story idea by collecting and analyzing data
  • Combine data sets when there is a similar variable
  • Accurately rank and compare data
  • Use Open Refine
  • Create and use fusion tables for story finding 

Finding Data: This session will show participants where to find data relevant to Irish journalism including common data sources, uncommon or underused data sources and the process of lodging Freedom of Information requests.

Learning Objectives:

  • Accessing Irish data
  • Underused Irish data sources for government departments, state-funded bodies, and commercial properties
  • Accessing European & international data
  • Checking data against other sources
  • Lodging Freedom of Information requests

Principles of Data Storytelling II: This session will introduce the participants to data visualization as a means to explore the data in hand, as well as to communicate the results and the story to the audience. Data visualization invites engagement and aids understanding but it’s important to follow sound principles of visualization. This session will introduce the audience to different types of data analysis and visualization, including ‘temporal’, ‘geospatial’, ‘topical’ and ‘network’.

Learning Objectives:

  • Different types of data analysis and visualization
  • The various types of graph
  • Principles of good data visualization

Using Visualization Tools: A wide range of free and commercial tools are available to help journalists visualize data stories via graphs and maps. Participants will be introduced to tools for data visualization and will learn how to use a subset of these tools.

Learning Objectives:

  • Visualize data using charts
  • Visualize geospatial data using maps
  • Visualize temporal data timelines

About The Instructors

Megan Lucero is the Data Journalism Editor at The Times and Sunday Times. She was one of the first data journalists hired by the two titles and led the data team’s development from a small supporting unit to a key component of Times’ investigations. Her work on The Times cycling campaign and its five-part series on understanding the Syrian conflict changed the way the paper told stories digitally and turned traditional print readers into an active online community that lobbied for change. Megan also spearheaded a data unit ahead of the UK’s 2015 General Election. Megan’s work has been commended by the Royal Statistical Society and the Global Editors Network and she has advised CNN, ITV, The Economist and The Bureau of Investigative Journalism on building investigative data teams.

Dr Bahareh Heravi leads the Insight News Lab at the Insight Centre for Data Analytics in NUIG where she also teaches data journalism. She was the project leader on a number of Insight projects with RTÉ and was the lead data scientist (2014-2015) at The Irish Times where she co-founded Irish Times Data. She is also the founder and main organizer of Hacks/Hackers Dublin.

Mark Coughlan is an investigative and current affairs reporter for RTÉ. As a researcher and reporter with Prime Time, he has focused on issues of corporate governance and the allocation of public money. Prior to RTÉ, Mark worked at Storyful and ran thestory.ie – a blog focused on data journalism, information transparency, and Irish current affairs.

Eoghan McConalogue is a lecturer in the DCU Business School where he teaches management and information systems. He has previously worked as an IT analyst and taught IT at DCU and Microsoft Ireland.

Share.