Selected Topics in Visual Analytics (Wintersemester 2019/2020)

Lecturer: Prof. Dr. Jürgen Döllner (Computergrafische Systeme) , Dr. Jan Klimke (Computergrafische Systeme)

General Information

• Weekly Hours: 4
• Credits: 6
• Graded: yes
• Enrolment Deadline: 01.10.-30.10.2019
• Teaching Form: Seminar / Project
• Enrolment Type: Compulsory Elective Module
• Course Language: German

Programs, Module Groups & Modules

Description

Visual Analytics "[is] the science of analytical reasoning facilitated by interactive visual interfaces" (Thomas, Cook: Illuminating the Path, 2004) it covers concepts, techniques, and processes from different scientific areas: information visualization, computer graphics, data processing, management, and statistical analysis. Here one key element of Visual Analytics is to provide users massive datasets (e.g., sensor data, financial transactions, or data about software systems structure and behavior) visually and in an interactive manner. By exploiting the strengths of the human visual system (e.g., preattentive processing and pattern recognition) structures, correlations, and patterns in massive datasets can be recognized and assessed.

Students are expected to cope with a specific aspect or technique in the area of Visual Analytics, including a prototypical implementation for massive spatio-temporal datasets originating from different application areas, e.g., industrial IoT, building automatation, or health surveys.

Examples for thematic areas include:

• Integration, processing, and visualization of massive sensor datasets
• Outlier and pattern recognition in spatio-temporal data
• Mapping techniques for Visual Analytics
• Visualization Techniques for spatio-temporal data
• Layout techniques and hierarchy building for spatio-temporal data
• Assisting User Interfaces for Visual Analytics
• ML techniques for visual analytics 
• Interaction techniques for Visual Analytics
• Virtual/Augmented Reality for Visual Analytics
• Event processing, visualization, and notification
• Uncertainty and validity visualization
• Multi-View Dashboards
• Evaluation of Visualizations and connceted User Interfaces
• …

The topics provided contain a strong relation to current research activities at the computer graphics systems group. Partially, an existing Visual Analytics framework can be used as a basis for implementation. Course material including topic presentations are available on CGS Moodle.

After successful completion of the course, many of the topics provide the possibility to extend the work into an academic publication, a master thesis, or to continue working on the topic as a working student.

Requirements

Master students enrolled in the IT-Systems Engineering or Computer Science program of the university of Potsdam are targeted by this course. Depending on the selected topic, skills in object oreinted programming, web-based programming (Typescript, JavaScript, Node.js, Ruby), foundations of computer graphics and visualizations  (OpenGL, GLSL und WebGL, visualization concepts such as the visualization pipeline or mapping data to visual variables). There will be topics for different focuses and skills, from data processing, visualization methaphors to 2D/3D rendering techniques.

Literature

Besides the online accessable information concerning a specific topics we will provide a set of up-to-date articles and other literature. An in depth research of further related work in the field is expected to be conducted by participants.

Learning

In general participants are expected to read up on the assigned topic and its related work. In course of the semester participants are indiviually mentored by members of the Computer Graphics Systems group. Regular meetings are scheduled individually for progress presentation and 

Examination

To sucessfully complete the cours it ist expected to 

• give a conceptual presentation that introduces the topic area, propblem statement, and presents related work
• successfully plan and implement a software development project related to the topic (50%),
• assemble foundations and results of the seminar work in a scientifically written document  (4 pages) (25%),
• give a final presentation about the topic highlightig results and specfic aspects of interest  (25%) halten.

Dates

Seminar topics are presented during the first scheduled slot of the instructional period on Wednesdy October 16th 11:00 am at H-2.58.

There is no fixed schedule during the seminar period. Meetings with mentors during the semester are scheduled individually. Appointments for presentations are announced and coordinated separately for all participants. The participants are expected to attend these presentations.

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