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Data Journalism
Engineering & Social Sciences Program
Madrid, Spain
Dates: 1/18/24 - 6/5/24
Data Journalism
OVERVIEW
CEA CAPA Partner Institution: Universidad Carlos III de Madrid
Location: Madrid, Spain
Primary Subject Area: Journalism
Instruction in: English
Course Code: 13461
Transcript Source: Partner Institution
Course Details: Level 400
Recommended Semester Credits: 3
Contact Hours: 42
Prerequisites: The subjects related to this subject are closely linked to the basic notions of the Excel sheets and search and use of information sources. Use and application to the editorial design.
DESCRIPTION
1.INTRODUCTION TO DATA JOURNALISM, versus Precision Journalism. The case: the television network CBS to predict the results of the presidential elections.
2. OPEN DATA and OPEN JOURNALISM. How to obtain reliable data through the network. A study model: The Guardian.
3. DATA AND THE LAWS OF ACCESS TO PUBLIC INFORMATION. How to obtain data information through from documentary sources and public bodies. The TRANSPARENCY LAW.
4. The "NEWSROOM" in Data Journalism and building the "New Journalism".
5. How to understand the data and organize them. "GETTING DATA". The concept of "Web Scrapping".
6. DATA REPRESENTATION AND INFORMATION DISPLAY (I).
7. TOOLS (I), (II), (III) most common used in Data Journalism.
7.1.More common tools (Excel) and more complex (Gapminder).
8. The CONCEPT OF VISUALIZATION OF INFORMATION AND BASIC PRINCIPLES. A case study: "INFORMATION IS BEAUTIFUL".
9. COMPLEX VISUAL NARRATIVE STRUCTURES: "Mapping Data", TreeMap, etc.
10. SPACE-TEMPORARY STRUCTURES: Timelines and Flows, used to improve the VISUALIZATION OF INFORMATION.
11. FUTURE PERSPECTIVES IN DATA JOURNALISM.
2. OPEN DATA and OPEN JOURNALISM. How to obtain reliable data through the network. A study model: The Guardian.
3. DATA AND THE LAWS OF ACCESS TO PUBLIC INFORMATION. How to obtain data information through from documentary sources and public bodies. The TRANSPARENCY LAW.
4. The "NEWSROOM" in Data Journalism and building the "New Journalism".
5. How to understand the data and organize them. "GETTING DATA". The concept of "Web Scrapping".
6. DATA REPRESENTATION AND INFORMATION DISPLAY (I).
7. TOOLS (I), (II), (III) most common used in Data Journalism.
7.1.More common tools (Excel) and more complex (Gapminder).
8. The CONCEPT OF VISUALIZATION OF INFORMATION AND BASIC PRINCIPLES. A case study: "INFORMATION IS BEAUTIFUL".
9. COMPLEX VISUAL NARRATIVE STRUCTURES: "Mapping Data", TreeMap, etc.
10. SPACE-TEMPORARY STRUCTURES: Timelines and Flows, used to improve the VISUALIZATION OF INFORMATION.
11. FUTURE PERSPECTIVES IN DATA JOURNALISM.