Winter School 2021

The first winter school of the KnowGraphs takes place on February 23rd – 25th, 2021. The goals of this school are:

  1. Disciplinary Training
    • Topic: Scientific foundations
    • Approach: Beginner talks on techniques related to KGs
  2. Complementary Training
    • Topic: Research methodology
    • Approach: Data challenge
  3. Professional Development
    • Topic: Possible professional paths in science and industry, IPR
    • Approach: Industry talks + talk on data and law

Programme

Details of the single talks will be added soon.

What are knowledge graphs?

Presenter: Prof. Dr. Sören Auer

Abstract: The availability of large-scale datasets has unleashed an enormous potential of making computers smarter and gave rise to cognitive computing. In order to realize the potential of AI a common understanding of the structure and meaning of data (e.g. to be used as training or evaluation data) must be established. We can leverage vocabularies, Linked Data, knowledge graphs or Semantic Data Lakes for that purpose. In this talk we give an overview on knowledge graphs, which all help to realize the emerging concept of hybrid AI, where large-scale, rich semantic data and knowledge tightly interacts with machine learning and analytics. We discuss some enterprise applications and present with the Open Research Knowledge Graph a use case and approach for semantically describing and organizing scientific contributions to empower researchers to master the flood of staticscientific publications.

Application talk 1

Presenter: Dr. Martin Voigt

Introduction to description logics

Presenter: PD. Dr.-Ing. habil. Anni-Yasmin Turhan

Constructing Knowledge Graphs

Presenter: Prof. Dr. Roberto Navigli

Application talk 2

Presenter: Martin Kaltenböck and Artem Revenko

Abstract: The amount of structured, semi-structured and unstructured data in organisations is growing heavily and data and information is often stored in silos inside of department solutions, but organisations are interested in unified 360 degree views on their data and information to be able to make precise and sustainable decisions. Enterprise Knowledge Graphs can solve this problem by integrating data and information from heterogeneous sources in different formats by mapping it to one or more central knowledge models and linking it to each other in the form of a Knowledge Graph. This talk will provide a short introduction into the problem statement and why and how Knowledge Graphs can help, furthermore it gives a short introduction into PoolParty Semantic Suite, a Semantic Middleware for powerful Knowledge Graph applications and finally it will provide an overview of the most important use cases that Enterprise Knowledge Graphs can solve.

Further reading:

Machine Learning on KGs

Presenter: Prof. Dr. Steffen Staab

Constraints

Presenter: Asst. Prof. Dr. Sabrina Kirrane

Application talk 3

Presenter: Dr. Peter Haase

Legal Aspects of KGs

Presenter: Prof. Dr. Jeanne Pia Mifsud Bonnici

Practical Information

The winter school will take place online using the BigBlueButton platform. Registered participants will receive a link to the room via mail before the winter school starts.

People external to the KnowGraphs project can participate in the winter school. Please contact Michael Röder before February 20th via mail for registration.

Schedule

Day 1

9:00 – 9:30
Intro
9:30 – 11:30
What are knowledge graphs?
Prof. Dr. Sören Auer
11:30 – 11:45
Coffee break ☕
11:45 – 12:30
Application talk 1
Dr. Martin Voigt
12:30 – 13:30
Lunch 🍔
13:30 – 15:30
Introduction to description logics
PD. Dr.-Ing. habil. Anni-Yasmin Turhan
15:30 – 15:45
Coffee break ☕
15:45 – 18:00
Data Challenge 💻
  • Group formation (3 groups)
  • Setup for benchmarking
  • Questions to helpers

Day 2

9:00 – 9:30
Intro
9:30 – 11:30
Constructing Knowledge Graphs
Prof. Dr. Roberto Navigli
11:30 – 11:45
Coffee break ☕
11:45 – 12:30
Application talk 2
Martin Kaltenböck and Artem Revenko
12:30 – 13:30
Lunch 🍝
13:30 – 15:30
Machine Learning on KGs
Prof. Dr. Steffen Staab
15:30 – 15:45
Coffee break ☕
15:45 – 18:00
Data Challenge 💻

Day 3

9:00 – 9:30
Intro
9:30 – 11:30
11:30 – 11:45
Coffee break ☕
11:45 – 12:30
Application talk 3
Dr. Peter Haase
12:30 – 13:30
Lunch 🍜
13:30 – 15:30
15:30 – 16:00
Coffee break ☕
16:00 – 17:30
Data Challenge Presentations
17:30 – 18:00
Wrap up