Introduction

Knowledge Graphs are large graphs used to capture information about the real world in such a way that is useful for applications. In these data structures, there are all sorts of entities (for example, people, events, places, organizations, etc.). These graph also contains all sorts of information about these entities (e.g., age, opening hours, …) and relations between them (e.g., this shop is located in Aachen).

Knowledge Graphs are used by many organizations to represent the information they need for their operations. The most well-known is Google, where a knowledge graph is used to enrich the search results. Also personal assistants, like Amazon’s Alexa, Apple’s Siri and Google Now, as well as question answer systems like IBM Watson, make use of knowledge graphs to provide information to their users. Besides these, also other information graphs, are in use by large organizations to improve or personalize their services. Examples include the Facebook graph, the Amazon product graph, and the Thompson Reuters Knowledge Graph.

In this course we will give a basic practical introduction to working with these graphs. As this is the first time this practical course is thought, some parts are still under construction. Currently, we plan to cover the following in the course:

• Graph representation of data
• Use of vocabularies and ontologies
• Searching information in knowledge graphs
• Information extraction
• Data mining techniques for knowledge graphs
• Knowledge graph completion (predicting links, finding anomalies)

Preparing for the course

One options to prepare yourself for the course is watching trough these videos by Harald Sack: https://open.hpi.de/courses/semweb2015

Preliminary schedule

The meetings will take place on Tuesdays from 14 till 16 in 5053.1 (colloquially know as the small b-it room).

We will have our first session on April 10. Take your laptop with you!

Currently our schedule looks as follows (minor changes might occur)

• April 10
  • Introduction session (canceled)
• April 17
  • Short introduction slides
  • Presentation knowledge graphs in the industry (OSTHUS - slides)
• April 24
  • Extra session to compensate for canceled intro session
  • Slides in L2P
• May 8 (also industry presentation), May 29, June 12, June 26, July 3, July 10
  • Presentations of solutions to tasks
  • May 8
    • Presentations by Andra Waagmeester
      • Wikidata and Pathways
      • ShEx
  • May 29 slides
    • Feedback on task 2
    • Intro to graph embeddings
    • Description for task 3
      • The dataset for can be downloaded here
      • The evaluation dataset can be found here
    • Presentation of final project tasks
• July 16, July 17
  • Presentations for the final tasks in longer sessions 10-16!!!

Required Prior knowledge

We expect that you are able to program and use data structures and algorithms. Having experience with graphs is not required, but is definitely useful. We will also have some data mining related task, so past experience in that domain is also an asset.

Note that the language of this course is English.

The course is organized with the appreciated support from OSTHUS