Information Visualization

• Teachers
• Weekly hours
• Competences
• Objectives
• Contents
• Activities
• Teaching methodology
• Evaluation methodology
• Bibliography
• Previous capacities

Teachers

Person in charge

• Pere Pau Vázquez Alcocer ( )

Others

• Imanol Muñoz Pandiella ( )
• Oscar Argudo Medrano ( )

Weekly hours

Competences

Technical Competences

Technical competencies

• CE1 - Skillfully use mathematical concepts and methods that underlie the problems of science and data engineering.
• CE4 - Use current computer systems, including high performance systems, for the process of large volumes of data from the knowledge of its structure, operation and particularities.
• CE5 - Design and apply techniques of signal processing, choosing between different technological tools, including those of Artificial vision, speech recognition and multimedia data processing.
• CE7 - Demonstrate knowledge and ability to apply the necessary tools for the storage, processing and access to data.
• CE10 - Visualization of information to facilitate the exploration and analysis of data, including the choice of adequate representation of these and the use of dimensionality reduction techniques.

Transversal Competences

Transversals

• CT3 [Avaluable] - Efficient oral and written communication. Communicate in an oral and written way with other people about the results of learning, thinking and decision making; Participate in debates on topics of the specialty itself.
• CT4 - Teamwork. Be able to work as a member of an interdisciplinary team, either as a member or conducting management tasks, with the aim of contributing to develop projects with pragmatism and a sense of responsibility, taking commitments taking into account available resources.
• CT5 [Avaluable] - Solvent use of information resources. Manage the acquisition, structuring, analysis and visualization of data and information in the field of specialty and critically evaluate the results of such management.
• CT7 - Third language. Know a third language, preferably English, with an adequate oral and written level and in line with the needs of graduates.

Basic

• CB3 - That students have the ability to gather and interpret relevant data (usually within their area of ??study) to make judgments that include a reflection on relevant social, scientific or ethical issues.
• CB4 - That the students can transmit information, ideas, problems and solutions to a specialized and non-specialized public.

Generic Technical Competences

Generic

• CG2 - Choose and apply the most appropriate methods and techniques to a problem defined by data that represents a challenge for its volume, speed, variety or heterogeneity, including computer, mathematical, statistical and signal processing methods.

Objectives

1. Introduction to Information Visualization
   Related competences: CE4, CE10, CT3, CG2, CB3, CB4,
   Subcompetences:
   • The Visualization Mantra
   • Basics
   • Historia
   • The information visualization process
2. Introducción a la percepción visual
   Related competences: CE10, CT3, CG2,
   Subcompetences:
   • Fundamentals of human perception
   • Marks and channels
   • Color and perception
3. Exploratory data analysis
   Related competences: CE5, CE10, CT3, CG2, CB4,
   Subcompetences:
   • Data wrangling
   • Data presentation
   • Hypothesis testing
4. Design of information visualization systems
   Related competences: CE7, CE10, CT3, CT5, CG2, CB3, CB4,
   Subcompetences:
   • Basic principles of visualization
   • Elements of an information visualization system
   • Visualization design
5. Focus and context
   Related competences: CE1, CE10, CT3, CT4, CG2, CB3, CB4,
   Subcompetences:
   • Eliding information
   • Information overlapping
   • Distortion
6. Interaction and animation
   Related competences: CE5, CE7, CE10, CT3, CT4, CT7, CG2, CB4,
   Subcompetences:
   • Navigation
   • Selection and pointing
   • Filtering
7. Visualization of multi-dimensional data
   Related competences: CE1, CE4, CE5, CE7, CE10, CT3, CT4, CT7, CG2, CB3, CB4,
   Subcompetences:
   • Multiple marks and channels
   • Complex diagrams: Trellis, SPLOM, PCP
   • Views
8. Multiple views and coordinated views
   Related competences: CT3, CB3, CB4,
   Subcompetences:
   • Effective use of space
   • Overlapping and juxtaposition
9. Item and attributes reduction
   Related competences: CE1, CE5, CE10, CG2, CB4,
10. Validation of visualization systems
    Related competences: CE1, CE10, CT3, CB4,
    Subcompetences:
    • Domain validation
    • Validation of abstraction
    • Validation of the representation
    • Validation of the algorithm
11. Implementation of visualization applications
    Related competences: CE1, CE4, CE5, CE7, CE10, CT3, CT4, CT5, CT7, CG2, CB3, CB4,
    Subcompetences:
    • Visualization coding
    • Data processing
    • Design of coordinated views
12. Advanced visualization tècniques
    Related competences: CE4, CE7, CT3, CG2, CB3,

Contents

1. Introduction to visualization
   In this topic we will discuss the need for visualization of data and the objectives of the visualization tools.
2. Perception and color
   Visual perception is a very important factor when creating visualizations, since the visual system is the one that receives the greatest amount of information that we perceive. In this topic we will talk about the visual system, and some theories of the perception of color and forms.
3. Visual representations of the data
   There are a large number of methods of data representation: tables, graphs, trees, etc. In this topic we will visit them and we will end up giving some guides to select the most appropriate representation for each problem.
4. Visualization of multiple data
   In many cases, the information that we want to represent will be highly complex and we will often find ourselves in the situation of having to represent multiple variables. Here we will discuss different possibilities that will be detailed in later issues.
5. Animation and interaction
   To explore the data, you must be able to work on visual representations. This topic will see data changes in different dimensions: time, point of view ...
6. View manipulation
   To explore the data, you must be able to work on visual representations. In this section you will see changes of data in different dimensions: time, point of view ...
7. Advanced data representation systems
   Advanced data representation systems
   
   - Maps
   
   - Time display
   
   - Visualization of 3D data
   
   - Other scientific data
8. Implementation of information visualization applications
   There are many tools and technologies developed recently that make creating views easier, such as Tableau, Vega, Lyra or using programming languages and libraries such as D3 for JavaScript or Bokeh for Python. The objective of this subject is that students are able to perform visualization applications using some of the most modern tools.

Activities

Activity Evaluation act

Teaching methodology

Evaluation methodology

Bibliography

Basic:

• Visualization analysis and design - Munzner, T, CRC Press, Taylor & Francis Group, 2015. ISBN: 9781466508910
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991004067699706711&context=L&vid=34CSUC_UPC:VU1&lang=ca
• Show me the numbers: designing tables and graphs to enlighten - Few, S, Analytics Press, 2012. ISBN: 9780970601971
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991004067739706711&context=L&vid=34CSUC_UPC:VU1&lang=ca

Previous capacities