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Department of Informatics Interactive Visual Data Analysis Group

Fundamentals of People Oriented Computing

Fundamentals of People-Oriented Computing is a new teaching format that replaced the "Master Basismodule".

It is part of the People-Oriented Computing (POC) study direction, comprising the topics offered by IFI that focus on the relationship between humans and technology. POC deals with the human-centered design of information technology. User-friendliness, security, and cultural and ethical aspects are of core importance. You create interactive systems and visualize information.

Title Fundamentals of People-Oriented Computing
Specialization People-Oriented Computing
Term Fall 2023
IVDA Topic Human-Centered Interactive Visual Data Analysis

Several professors will offer topics to choose from. The topics we are offering run under the umbrella "Human-Centered Interactive Visual Data Analysis".

About the Course

The Fundamentals of POC is designed to:

  • Provide a deep dive into a POC topic that excites you
  • Give you experience in reading and analyzing scientific literature
  • Give you the chance to gain familiarity with a professor or research group in POC
  • Complement other lectures and teaching formats with a self-directed module

Basic format of topic is reading scientific literature and individual oral examination

  • Reading is typically 250-300 pages, depending on format
  • Course grade is mainly determined by the grade of the assessment

Our Topic: Human-Centered Interactive Visual Data Analysis


This topic investigates the human-centered component in data-centric research and practice. We will study concepts, methodologies, and techniques focusing on the Human-Centered AI, Human-Centered Machine Learning, and Human-Centered Data Analysis in particular.

Focus Topics (within IVDA)

This year, we have ten focus topics at your disposal. Focus topics are specializations of the human-centered IVDA topic, towards an aspect that is most interesting to you:

  • XAI for Recommender Systems: interactive visual explanations for recommender systems
  • IVDA and Data Humanism: how principles of data humanism align with interactive visual data analysis
  • Human-AI Teaming: discover how interactive visual data analysis can facilitate human and machine teaming
  • Human-Centered Healthcare: how interactive visual data analysis in personal and digital health
  • Item Ranking: ranking items by more than one attribute at the same time
  • Item Labeling: human-centered ways to create  training data for supervised machine learning
  • Digital Libraries and Humanities: how interactive visual data analysis techniques can help
  • Sustainability: applying interactive visual data analysis techniques to make the world more sustainable
  • Item Similarity, Search and Exploration: human-centered forms of similarity definition, search, and exploration
  • Human-Centered Relation Discovery: interactive visual techniques to find new (co-)relations in multivariate datasets