DH-404 / 5 credits

Teacher: Kenderdine Sarah Irene Brutton

Language: English


Summary

This course will engage novel approaches for visualizing and interacting with cultural heritage archives in immersive virtual environments.

Content

Keywords

Cultural Heritage Data

Visualization

HCI

Immersive and Interactive Virtual Systems

Computational Museology

Learning Prerequisites

Required courses

No mandatory prerequisites

Recommended courses

Applied Data Analysis

Machine Learning for Digital Humanities

Design Research for Digital Innovation

Introduction to Digital Humanities

Important concepts to start the course

Interaction Design

3D game engines (Unity / Unreal Engine)

3D Modelling

Learning Outcomes

By the end of the course, the student must be able to:

  • Assess / Evaluate : Evaluate key methodological concepts for displaying and interacting with cultural archives in museum settings.
  • Decide : Decide the potential of different digital archives for immersive and interactive visualization
  • Explain : Analyze and gain a deep understanding of a cultural archive
  • Create : Conceptualize and design immersive and interactive real time applications for cultural archives
  • Apply : Implement an aspect of their real time application

Transversal skills

  • Plan and carry out activities in a way which makes optimal use of available time and other resources.
  • Demonstrate a capacity for creativity.
  • Manage priorities.
  • Communicate effectively with professionals from other disciplines.
  • Evaluate one's own performance in the team, receive and respond appropriately to feedback.
  • Make an oral presentation.
  • Write a literature review which assesses the state of the art.
  • Write a scientific or technical report.

Teaching methods

Theoretical lectures

Exhibitions and installation experiences and critiques

Applied project design, hands on sessions

Expected student activities

  • One short essay
  • Applied learning activities in data modelling / data science
  • Group work
  • Design critiques
  • Evaluation
  • Participation to the hands-on sessions
  • Main project (in groups of 3-4)
  • Written and oral presentation of the main project

 

Assessment methods

Short essay (10%)

Main project (90%) comprised of:

  • Analysis of the dataset (20%)
  • Implementation of an aspect of the project (20%)
  • Design and conceptual work (50%)

 

 

Supervision

Office hours Yes
Assistants Yes
Forum Yes

Resources

Virtual desktop infrastructure (VDI)

No

Bibliography

Extensive readings given during class in visualzation and new museology.

Websites

In the programs

  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Cultural data sculpting
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Project: 3 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Cultural data sculpting
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Project: 3 Hour(s) per week x 14 weeks
  • Exam form: During the semester (summer session)
  • Subject examined: Cultural data sculpting
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Project: 3 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Cultural data sculpting
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Project: 3 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9     
9-10    
10-11     
11-12    
12-13    
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     

Thursday, 8h - 10h: Lecture

Thursday, 10h - 13h: Project, other

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