Module: Data Journalism

Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title	Data Journalism
Module Code	CM2003A
School	School of Communications
Module Co-ordinator	Semester 1: Jane Suiter Semester 2: Jane Suiter Autumn: Jane Suiter
Module Teachers	Jane Suiter
NFQ level	8	Credit Rating	5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

None
Any failed assignment must be re-submitted as a resit over the summer.

Description

This module focuses on how data and IT tools can assist and support journalists in digital storytelling. The module aims to give students a solid basic understanding of the tools available and possibilities of data journalism. Besides learning about the basics of this increasingly vital discipline, students will learn how data is used in the media industry today, where to locate data, how to clean and analyze it critically, and how to optimise the presentation of information for maximum readability and interactivity. The module also gives students a thorough grounding in the use of common tools including spreadsheets and presentation. The module focuses particularly on using visualisation to effectively communicate data sets. Students will apply these principles and tools in telling journalistic stories. The module will be delivered as a series of lectures and seminars which will cover file management, spreadsheets, document and presentation preparation and visualisation tools Introduction and Context Ubiquity of computers, information and systems. Data vs Information Where to Find Data and the Stories Open data, FoI, Publically funded datasets. Social networks. How to interview the data Sorting, Cleaning, Analytics, Pivot Tables, Basic Statistics. How to Bring the Data to Life Principles. Design. Animation. Interaction

Learning Outcomes

1. Explain how data is used in journalism
2. Understand where to source data for journalistic stories
3. Learn how to clean and utilise appropriate data, including FoI, open government and public datasets
4. Report and write complex, multi-source data driven journalism
5. Solve analytical problem and learn how to view data critically (incl. spreadsheets)
6. Apply the basic principles in effectively communicating data visually.
7. Utilize online tools to both collect and visualize data sets.

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Lecture	22	A formal lecture which typically presents the essential ideas and core concepts pointing students towards resources where they can get further information. Students are expected to prepare for each lecture by, for example, reading materials suggested by the lecturer
Assignment Completion	22	Weekly Preparation
Independent Study	22	Researching Data Journalism Exemplars
Laboratory	24	Software and Analytics Practice
Independent Study	35	Writing / Designing Project
Total Workload: 125

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Introduction and Context

Ubiquity of computers, information and systems

Data vs Information

Where to Find Data and the Stories

Open data

FoI

Publically funded datasets

Social networks

Data Sorting, Cleaning, Analytics, Pivot Tables, Basic Statistics

How to Bring the Data to Life Principles

Design, Animation, Interaction

Assessment Breakdown
Continuous Assessment	100%	Examination Weight	0%

Type	Description	% of total	Assessment Date
Course Work Breakdown
Short Answer Questions	Kubicle Online Assessment	30%	Week 29
Assignment	In class presentation	20%	Week 30
Assignment	Assignments to find, combine, and present data from multiple data sources	50%	Week 11

Reassessment Requirement Type
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
This module is category 1

Indicative Reading List

Liliana Bounegru Liliana Bounegru: 2012, The Data Journalism Handbook, European Journalism Center,
edited by Jonathan Gray, Liliana Bounegru and Lucy Chambers: 2014, The Data Journalism Handbook. How Journalists can use data to improve the news, O'Reilly, New York,
Brant Houston,: 2005, The Investigative Reporter's Handbook, 5th, St. Martin's, Boston, 978-0312589974
Stephen J. Berry,: 2009, Watchdog Journalism, 1st, Oxford UP, Oxford, 978-0195374025
Paul Bocij, Andrew Greasley, Simon Hickie: 0, Business Information Systems: Technology, Development and Management for the e-Business, 5th, 1,2 3,4 5,6, 7, 13, Prentice Hall London,

Other Resources

None

Programme or List of Programmes

JR	BA in Journalism

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