Checking date: 01/05/2019


Course: 2019/2020

Data Visualization
(17468)
Study: Bachelor in Management of Information and Digital Contents (340)


Coordinating teacher: OLMEDA GOMEZ, CARLOS

Department assigned to the subject: Department of Library Science and Documentation

Type: Compulsory
ECTS Credits: 6.0 ECTS

Course:
Semester:




Students are expected to have completed
There are no specific course prerequisites for this course.
Competences and skills that will be acquired and learning results. Further information on this link
After completing the course satisfactorily, students should: - Know techniques and theoretical aspects of data visualization. - Know methods for design, visual coding and interaction with data. - Know and understand the state of the art of data visualization. - Clearly and efficiently understand how to communicate patterns found in the data. Acquire proficiency for: - Use tools to generate data visualizations. - Use tools that generate interactive visualizations in a web environment. - Explain the importance of choosing an appropriate color map. - Identify a visualization where an inappropriate design choice was made and explain why the choice was inadequate. and acquire skills: - to know the phases that comprise a complete data visualization project, independent of any specific software tool; - to propose alternative ways to visualize the same set of data; - to create better and more reflective data visualizations; - identify their own learning needs in relation to the use of data visualization in a specific context;
Description of contents: programme
1. Introduction to data visualization. 2. Workflows. 3. Data. 4. Working with data. 5. Tools. 6. Data representations. 7. Interaction techniques. 8. Color. 9. Data design for audiences.
Learning activities and methodology
TRAINING ACTIVITIES OF THE STUDY PLAN LA 1. Individual work for the study of readings and course materials developed and contributed by the teacher. LA 2. Individual work for problem solving and case studies. LA 3. Working in groups for solving data exercises. LA 4. Throughout the course it is expected to use videos to exemplify some of the aspects related to data visualization. LA 5. Active participation in practical classes. TEACHING METHODOLOGIES M 1. Explanations of the teacher with support of computer and audiovisual media, in which the main concepts of the subjects are developed. M 2. Critical reading of texts recommended by the professor of the subject. M 3. Resolution of practical cases and problems raised by the teacher in an individual way.
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40

The course syllabus and the academic weekly planning may change due academic events or other reasons.