Teaching Data Journalism by Andreas Veglis - Milan 2015

Teaching Data Journalism in
the School of Journalism &
MC-Greece
Andreas Veglis – Professor
Media Informatics Lab School of
Journalism & Mass Communication
Aristotle University of Thessaloniki
Greece

Media Informatics Lab – School of Journalism & MC
• Very rapid advanced of Information and Communication technologies
• Digitalization of data
• Digital data processing, storing, distribution
• Continuous production of new data
• Ability to find data on the internet
Abundance of digital data

Suitable conditions for the introduction
of Data Journalism
• Kind of Journalism that is
conducted with the help of
data.
• Can allow a journalist to
communicate a complicated
story with the help of
visualizations.

Defining Data Journalism……
• Data Journalism, Computer-Assisted Reporting,
Computational Journalism, Data-driven Journalism .
• Journalism done with data.
• «Data can be the source of data journalism, or it can be the
tool with which the story is told — or it can be both. Paul
Bradshaw, Birmingham City University
• Only finding interesting data does not constitute data
journalism – for example the case of Wikileaks.

Data Journalism Definition
• Data Journalism is the process of extracting useful information from
data, writing articles based on the information and embedding
visualizations (interacting in some cases) in the articles that help
readers understand the significant of the story or allow them to
pinpoint data that relate to them.

Data Journalism - example
• http://schoolofdata.okfn.g
r/2014/05/07/european-
student-mobility-2001-
2012/

Why Journalists have to work with data?
• News stories from multiple
sources.
• The combination of various
news allow  the whole
picture of an event.
• Data: small pieces of
information, unrelated at first
glance.
• Journalists should approach
data as a chance to find new
stories.

Data Journalism in Guardian, 1821

Mortality in the British army (1856)

Stages of data Journalism
Data
Compilation
Data
Cleaning
Data
Understanding
Data
Validation
Data
Visualization
Article
Writing
?

Data compilation
• may be supplied directly by an organization,
• may be found with the help of advanced searching
techniques,
• may be compiled by scraping web pages,
• may be collected by converting documents to other
formats that can be analyzed, and
• may be collected by means of observation, surveys,
online forms or crowdsourcing.

Data Cleaning (Scrubbing)
• The process of detecting and correcting (or removing)
corrupted or inaccurate records from a dataset
• Forms of Cleaning:
– removing human errors and
– converting the data into a format that is consistent with other
data the journalist is using.
• Cleaning methods:
– using find and replace commands or filters on spreadsheets
– Using specialized tools, like Google’s OpenRefine.

Data Understanding
• Data not easy to be understood.
• Further data is needed in order for existing data to
become meaningful.
• Journalists ought to be data-literate. They must have the
ability to:
– consume knowledge, produce coherently and think critically
about data.
– understand statistics and how to work with large datasets, how
they were produced, how to connect various datasets and how
to interpret them.

Data Validation
• Cross-checking data, obtaining additional data.
• Data cannot always be trusted.

Data Visualization
• It is the graphical display of abstract information for data analysis
and communication purposes
• The visualization can be static or it can be interactive.
• There is a user input and the changes made by the user must be
incorporated into the visualization in a timely manner.
• Infographics  graphic visual representations of data or
knowledge, which are able to present complex information quickly
and clearly .

Article Writing
• May include special characteristics:
– external links to other articles or related material,
– multimedia content,
– mashups,
– static or interactive visualizations.

Types of Data Journalism
• By just the facts
• Data-based news stories
• Local data telling stories
• Analysis and background
• Deep-dive investigations

Open data sets to be used in Data Journalism
projects
• Easy to find
• Standard format
• Easy to use or re-use
• Specific usage licenses
Linked data
• Easy to acquire relevant data
• Way to verify the data
Open & Linked Data

Chicago Tribune

Datablog της Guardian

Ukraine’s election results 2012

Language communities of Twitter

Necessary skills for Data Journalism

Necessary skills for Data Journalism
• Finding, compiling data.
• Cleaning data.
• Understanding and combining data.
• Validating data
• Visualizing data

Data Journalism Courses in the School
of Journalism and MC
• BA Program – elective course – Spring Semester .
• ΜΑ in Digital Media, Communication and Journalism -
European Journalism elective course – Spring Semester.
• Life-long learning for professional journalists Spring 2016

Data Journalism Course structure
• Introduction to Data Journalism – Defining Data Journalism – Historical
evolution.
• Data Journalism teams – Case studies – Transforming data to stories
• Searching for data sets – Searching techniques
• Law for data and data sources.
• Data scraping –using Google Spreadsheet.
• Basic statistics for Journalists – Data classification and data filtering
• Pivot Tables
• Working with messy data – cleaning and filtering
• Data Visualization – choosing the suitable visualization type – examples
• Data Visualization tools (Google Spreadsheet, Google Fusion Tables,
Tableau, Data wrapper, many eyes, Infogram)

Course Evaluation
• Lab exercises during the lessons (50%)
• Final Data project (50%)

Data Journalism web site
• http://datajournalism.jour.auth.gr

Greek version of the Data journalism
handbook
• http://data-journalism.okfn.gr/handbook/
• http://iwrite.gr/bookstore/the-data-
journalism-handbook/

Information Validation
• Data from various sources
• Are they valid?
• Validation process

Verification Handbook
http://verificationhandbook.com/

Thank you for your attention
Andreas Veglis – professor
E-mail: veglis@jour.auth.gr
Webpage: http://blogs.auth.gr/veglis
Twitter: @veglis

Teaching Data Journalism by Andreas Veglis - Milan 2015

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