2015-2016 Autumn Semestre KadirHas University Faculty of Communication Data Journalism: The Basics
Autumn 2015: Sep 18th
Friday 09:00-12:00 am
Room:D-107 /NM 421 Data Journalism
The data journalism course will present fundamentals of open /data collecting, gathering, cleaning, analysis, visualisation process and understanding FOIA. Data skills are getting more important to affect data driven works for media industry. In the developing Internet world; to understand and figure out how database journalism turns to data journalism; and as the future of journalism, to teach with open data disciplines how data became a strong role in transferring more efficient growing online resources, tools, and techniques. This course will also address common pitfalls in misinterpreting data..
Class Blog: http://www.verigazeteciligi.com/
Class Notes: http://piratepad.net/KxVfSJhX4F
Class Hastag: #Khasddj15
Hastags: #ddj #ddjedu #datajournalism #opendata
#vg #vgegt #verigazeteciligi #açıkveri
Facebook Data Journalism Group:
Pınar Dağ, @pinardag / Instructor , D-107
Hours: Friday 09:00-12:00 am
Phone:90/532- 134- 53- 92
What is Data Journalism — And Where Does it Come From
Definition of Messy Data, Accuracy of Data – How To Learn
The Recognition and Understanding of Data Formats
Finding Stories in Data – How Do You Do It
Cleaning and analysing Data – How to Make the Data Make Sense
Scraping Data – Using the Web as a Data Source
Introduction to Data Visualisation Tools (Open Source)
Visualising the data: what works and what doesn’t
Which tools are available with which (Graphics, Charts, Map etc)
Basic Statistics and Excel Working Practices
Freedom of Information Requests
Open Data – Definition
Open Data and Ethics
Sources and Techniques – How to Find Data
Social Media Data Analysis / Learn-Digital Content Verification Techniques
Learning Outcomes of the Course Unit
Understand the history, current practice and likely impact of data journalism.
Demonstrate the skills involved in accessing, analysing and curating data from publicly available sources, data collection.
Work efficiently in teams and newsroom environments to produce data journalism packages
Demonstrate editing and production skills, online web tools, understanding technologies available to create online, interactive data-driven stories
Design basics, effective visual communication, and data visualisation
Understanding the development process for creating data stories and dealing with messy data
Freedom of Information Request and Understanding the Open Data
Learning techniques for Verification of Digital Content
Making Open Data Creation Practice
Understanding how to use Social Media Data and Analysis & Technical Development
Learning Extended Search Techniques during the solo and group projects.
Planned Learning Activities and Teaching Methods
Weekly course reading materials, use and try the tools before lecture and homework linked group, and solo projects practice and quizzes.
Books,sources,working with data:
Open Data Institute / http://theodi.org/
School of Data / http://schoolofdata.org/
Getting Started with Data Journalism /Writing data stories in any size newsroom /by Claire Miller/https://leanpub.com/datajournalism
Data Journalism HandBook /Edited by Jonathan Gray,Lilliona Bounegry and Lucy Chambers /http://datajournalismhandbook.org/
Data Journalism Heist /by Paul Bradshawhttps://leanpub.com/DataJournalismHeist
Data Journalism: Mapping the Future
Gazeteciliğin Geleceği:Veri Gazeteciliği-Pınar Dağ https://docs.google.com/document/d/1ueHNSvev8C5FRf9c-wwfoTrdbTLfrRPYakpphCOj2Ig/edit
Online Visualising data tools/Desktop software
Import.io / Web Scraper
Google Fusion tables
IBM Many Eyes
Google Spreadsheet Charts
OpenRefine (formally Google Refine https://code.google.com/p/google-refine/)
Tableau Public / Tableau data visualization software
Veri Gazeteciligi Blog
Participants/Students stories will be showcased in the class blog(Verigazeteciligi). Participants/students will be required to present the stories in class for discuss/critique. Project posts to the class blog are public by default, but can choose to keep them private. Participants/Students are encouraged to submit superior and/or timely work for publication elsewhere, including school outlets such as the Kadir Has University Faculty of Communication.
Attendance / Participation 20%
Project (Assignment) 20%
Homework Assignments 15%
Extra-Class Activities (Reading, Individual Work, etc.) 15%
Final Exam 20%
Grades for each major assignment are further broken down as follows:
What does it mean pitch?
*Why we care? *Who cares? *What pre-reporting you have done, incluiding a questions, an angle/a hook. why this story is matter/important?, a link of data (Means you found a data), one source.
What is Storyboard?
A sketch of how to organize a story and a list of its contents. A storyboard helps you: Define the parameters of a story within available resources and time. Organize and focus a story. Figure out what medium to use for each part of the story. Check out Mark Luckie’s thoughts on sketching/storyboarding, with examples, from 10,000 Words.
What is rough draft?
A late stage in the writing process.It is not a final report but it should be close that. Stundents should have created the visualizations that plan to use. Stundents complete rough draft must includes: clean data in spreadsheets, visualizations of the data,captions, credits, a headline, at least three links to other reporting that puts your story in a broader context, introductory text that includes information gleaned from at least one human source,a source list.
What is final report?
Story must be posted to the class blog. Need to post a headline, excerpt, image and linked text to the class blog.
Any form of plagiarism is unacceptable and will result in serious penalties. All submitted works be fully supported by your own reaerch.
In addition to being a serious academic issue, copyright is a serious legal issue. Please check for better understand, the Citizen Media Law Project it http://www.dmlp.org/legal-guide/search
Assigment due no later than HOUR pm on DAY/ MONTH 2015-2016
Absences and Tardiness
A minumum of 85% attendance is required across all elements of the course- specially group-based working etc. Please be in time for class and back to class from breaks. Repeated tardiness will result in a reduction of grade in participation.
Read Datablog http://www.theguardian.com/news/datablog
Data Driven Journalism: http://datadrivenjournalism.net/
Read school of data stories: http://schoolofdata.org/category/data-stories/
Read Anna Cordrea-Rado’s “Between the Spreadsheets” column at Columbia Journalism http://www.cjr.org/between_the_spreadsheets/
Read Kevin Quealy’s blog, “Charts and Things”: http://chartsnthings.tumblr.com
Due Seb 18:
Geoff McGhee’s Knight Fellowship Report on Data Journalism at http://datajournalism.stanford.edu/
Week 1| Seb 18:
–Course introduction (expectations, syllabus review)
Introduction to Data Journalism and Open Data.
What is data journalism and its history &why data journalism
The components of data journalism
The mindset and framework to understanding Data journalism and its application in various contexts
Understand the history, current practice and likely impact of data journalism.
What is Data Journalism
Why is it important?
Example of Data Journalism
Data Journalism Workflow
–Datasets to Practise
( https://r-dir.com/reference/datasets.html )
Turkish, European and International data banks/portals
FOI ( Pratic)
Data scraping: ScraperWiki and import.io
3| Oct 9:
Start working with Excel
Basic Newsroom Math
Excel basic Math functions
Discuss homework /preparation
Spreadsheet review:data types, rows and columns, sorting, copy and paste, selections, formulas & introduction to Pivot tables
Where to Find the Data and the Stories
How to find the stories in the data
Best practices and examples of stories and visualizations using data in various contexts
Class Exercise:Using spreadsheets and Pivot tablets
Introduction to Data Visualisation
Data visualisation using charts
Dataviz game & http://datavizcatalogue.com/
Introduction to Messy Data