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My work explores the role of digital data, digital methods and digital infrastructures in the composition of collective life.

I am Senior Lecturer (Associate Professor) in Critical Infrastructure Studies at the Department of Digital Humanities, King's College London. I am also co-founder of the Public Data Lab as well as Research Associate at the Digital Methods Initiative at the University of Amsterdam and the médialab at Sciences Po, Paris.

You can find out more about my work here.

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"Datajournalistik","University of Gothenburg, The Department of Journalism, Media and Communication","SE, Sweden","Bachelor","a 9-hp (high school points) module of a 30 hp-course, second year of the Bachelor programme, taught in Swedish"

Name - Datajournalistik
Institution – University of Gothenburg, The Department of Journalism, Media and Communication
Country – SE, Sweden
Level – Bachelor
Type – a 9-hp (high school points) module of a 30 hp-course, second year of the Bachelor programme, taught in Swedish

Data Journalism Syllabus

Data Journalism Syllabus: https://docs.google.com/document/d/1yIeUNOGHH7xOY-sNuXG7vKAokJUsQRDUspWHFmI9nk4/edit

DATA JOURNALISM
Undergraduate-Graduate Modul Program
Pınar Dağ - https://khas.academia.edu/pinardag

The aim of the course
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.

Course Content
How Data is Used for Public Interest Stories
How to Find a Story in Data
Sector-Specific Data Stories
Common Data Formats
Finding Data Online
Finding Open Data
Alternative Data Sources (FOI)
Planning a Data Story
Enriching Stories With Data
Analyzing Fact Sheets
Organizing Data
Verifying Data
Summarizing and Simplifying Data Insights
Essential Statistics
Evaluating Data Interpretation
Data Privacy
Purpose of Data Visualization
Matching Data and Graph Types
Design and Color Basics
Map Theory
Ethics of Data Visualization
Visual Storytelling
Reaching your Audience
Data Driven Interviews
Anatomy of a Data Story
Data-Driven Leads
Data-Driven Writing
Scraping
Excel 1,2,3,4,5,6
Cleaning
Visualization 1,2
Visualization 3 Tableau
Mapping CARTO 2
Tableau Dashboards 1

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.

Course Sources / Sites / Books:

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
Gazeteciliğin Geleceği:Veri Gazeteciliği-Pınar Dağ https://docs.google.com/document/d/1ueHNSvev8C5FRf9c-wwfoTrdbTLfrRPYakpphCOj2Ig/edit
Finding Stories in Spreadsheets
https://leanpub.com/spreadsheetstories
Tüm Boyutlarıyla İnternet Haberciliği
http://www.verigazeteciligi.com/verigazeteciligi-bolumunun-de-yer-aldigi-tum-boyutlariyla-internet-haberciligi-kitabi-cikti/
AVVG http://www.avvg.org.tr/yazilar/94-acik-veri-ve-veri-okuryazarligi-egitimleri%C2%A0herkesin-erisimine-acildi.html
Data Journalism: Inside the global future
http://www.slideshare.net/mrdamian/data-journalism-inside-the-global-future
https://www.amazon.co.uk/d/Books/Data-Journalism-Inside-global-future-Tom-Felle/1845496639
Data Journalism: Mapping the Future
http://www.abramis.co.uk/books/bookdetails.php?id=184549616
Scraping for Journalists
https://leanpub.com/scrapingforjournalists
NUMBERS IN THE NEWSROOM: USING MATH AND STATISTICS IN NEWS, SECOND EDITION, E-VERSION
http://store.ire.org/products/numbers-in-the-newsroom-using-math-and-statistics-in-news-second-edition-e-version
https://docs.google.com/presentation/d/1O73PPejZOwN6WRehN-pH2IWAdoYfx4iCgOLQBJdj3Gg/edit#slide=id.g1b7278b63f_0_96

Tools used
Excel
Import.io / Web Scraper
Tabula
Google Fusion tables
Google Spreadsheet Charts
Infogr.am
R
OpenRefine
Tableau Public
Google Drive
Openoffice
Adobe Reader
http://blog.cartodb.com/

Grading
Attendance / Participation 20%
Practice/Exercise 10%
Project (Assignment) 20%
Homework Assignments 15%
Extra-Class Activities (Reading, Individual Work, etc.) 15%
Final Exam 20%
Grade is determined by participation, completion of all solo homework assignments & completion of the two major team assignments. Assignments will be evaluated in terms of use of data, online web tools, story,context,design.
Grades for each major assignment are further broken down as follows:
Pitch (25%)
Storyboard (12.5%)
Draft (25%)
Final (25%)
Revision (12.5%)

Course Schedule

Week | Theme | Info
Modul 1 | Basic Data Concepts
Lesson 1: What is data, what are types
Lesson 2: International Data
Lesson 3: National Data
Lesson 4: Civil Data: Social Media
Lesson 5: Case Studies: Turkey
Lesson 6: Example: Tips & Tools |
Introductions
Read this piece: http://www.holovaty.com/writing/fundamental-change/Github.Spreadsheets, part 1: Structuring your data. Why it matters

Modul2 | Data Research Techniques
Lesson 1: Effective Data Research Methods
Lesson 2: Data Collection and Validation Methods
Lesson 3: Working with the "Data Biography" Template
Lesson 4: Importance of data filtering skill from the databases
(Exercise) |Making research practice according to data formats before lesson

Modul 3 | Data Cleaning
Lesson 1: Data Cleaning and Ethics
Lesson 2: Definition of Messy Data
Lesson 3: Messy Data Cleaning with Open Refine
Lesson 4: Using GithubLesson
5: Uploading data into Github
(Exercise) |
Open refine, read http://kwantu.net/blog/2016/12/28/how-to-clean-up-messy-data-using-open-refine

Modul 4 | Data Literacy, MetaData, Open Data
Lesson 1: What is Open Data
Lesson 2: What is Open Gov. Data
Lesson 3: Open Data Index
Lesson 4: Open Data Practice: Turkey
Lesson 5: Data Literacy , who is data literate?
Lesson 6: How metadata should be?
Exercise | Open Your Data
opendatahandbook.org/guide/en/
http://opendefinition.org/www.avvg.org.tr

Modul 5 | Effective Utilization Methods from FOIA
Lesson1:What is FOIA? How it is working in Turkey? And globe?
Lesson2: Shared data types and formats from FOIA ( CSV focued)
Lesson3:FOI tools and sample reviewsLesson4:Making FOI request
(Exercise)
https://www.whatdotheyknow.com/https://www.bimer.gov.tr/

Modul6 | Thinking Like a Data Journalist
Lesson 1: What is Data Journalism
Lesson 2: Who Should Be a Data Journalist?
Lesson 3: Data Journalism Sites and Data Journalists
Lesson 4: Examples | Award-winning Data Journalism Projects
(Exercise)
https://www.datajournalismawards.org/

Modul7 | What is Good / Bad Data
Lesson 1: Reviewing and Creating Data Sets
Lesson 2: Building Good Data
Lesson 3: Bad Data Set Review and importance of structured data
Assignment |Please structure your data
(Exercise)
https://github.com/Quartz/bad-data-guide

Modul8 | Data Analysis and Interpretation
Lesson 1:Data Analysis by using Excel and PivotTable
Lesson 2: Data Scraping from PDF and Web
Assignment|Analyze Your data
(Exercise) | http://tabula.technology/
https://data-miner.io/
http://www.firstpythonnotebook.org/prerequisites/cli.html

Modul9 | Statistics for Journalists
Lesson 1:Basic Statistics for Everyone
Lesson 2: Measuring Central Tendency
Lesson 3: Distribution / Measuring Differentiation
Lesson 4: Basic Statistics and Practices in Excel
(Exercise)
http://journalistsresource.org/tip-sheets/research/statistics-for-journalists
www.avvg.org.tr

Modul10 | Data Visualization Principles
Lesson 1: How to Visualize DataLesson
Lesson 2: Data Visualization RulesLesson
Lesson 3: Data Visualization Elements
Lesson 4: Data Visualization Color
Lesson 5: Matching Data and Graph Types
Lesson 6: Design and Color Basics
Lesson 7: Map Theory
Lesson:8 Ethics of Data Visualization
(Exercise) |
https://www.fusioncharts.com/whitepapers/downloads/Principles-of-Data-Visualization.pdfhttp://paldhous.github.io/ucb/2016/dataviz/week2.htmlhttps://datavizcatalogue.com/www.avvg.org.tr

Modul11 | Data Visualization
Lesson 1: Purpose of Data Visualization
Lesson 2: Using spreadsheet for making graphics (Line, Bar, Pie-Population Pyramid)
Lesson 3: GIS, Mapping with Fusion TableLesson 3: Techniques for Creating Effective Infographics
Assignment | Visualize your data
(Exercise)
http://www.creativebloq.com/design-tools/data-visualization-712402

Modul12 | R for Data Journalism
Lesson 1- Introduction to R
Lesson 2-RStudio program setup
Lesson 3: Data visualization examples with R
(Exercise) | https://rddj.info/

Modul13 | Story Telling with Data
Lesson 1: Using Data for breaking news
Lesson 2: Story Telling with Data
Lesson 3: Visual Storytelling
Lesson 4: Reaching your Audience
Lesson 5: Data Driven Interviews
Lesson 6: Anatomy of a Data Story, Data-Driven Leads, Data-Driven Writing
(Exercise)
https://www.journalism.co.uk/news/-nicar2016-3-tips-for-using-data-for-breaking-news/s2/a618607/

Modul14 | WORKING ON FINAL PROJECT &CLASS PRESENTS FINAL PROJECT
http://www.verigazeteciligi.com/?s=solo+project

Modul15 | FINAL EXAM |

Add programs in Kyrgyzstan, Albania and Sudan

“Data Journalism”,”American University of Central Asia”,”KG”,”Undegraduate”,”Programme”,”https://auca.kg/en/auca_news/2962/”
“Data Journalism”,”American University of Central Asia”,”KG”,”Postgraduate”,”Programme”,”https://dss.auca.kg/master-in-journalism-and-mass-communications/”
“Data Literacy”,”University of Khartoum”,”SD”,”Undergraduate”,”Module”,”https://www.sudandata.org/learning/2”
“Data Literacy”,”Ahfad University”,”SD”,”Undergraduate”,”Module”,” https://www.sudandata.org/learning/2”
“Data Journalism”,”University of Tirana”,”AL”,”Undegraduate”,”Module”,”http://www.odecanet.org/data-journalism-manual/”

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