Knowledge Graphs - Foundations and Applications

Despite the fact that it affects our lives on a daily basis, most of us are unfamiliar with the concept of a knowledge graph. When we ask Alexa about tomorrow's weather or use Google to look up the latest news on climate change, knowledge graphs serve as the foundation of today's cutting-edge information systems. In addition, knowledge graphs have the potential to elucidate, assess, and substantiate information produced by Deep Learning models, such as Chat-GPT and other large language models. Knowledge graphs have a wide range of applications, including improving search results, answering questions, providing recommendations, and developing explainable AI systems. In essence, the purpose of this course is to provide a comprehensive overview of knowledge graphs, their underlying technologies, and their significance in today's digital world.

自十一月 21, 2023起开始自学
语言: English
Big Data and AI, Expert


A knowledge graph is a structured representation of knowledge that is used to provide a comprehensive and interconnected view of a specific domain. In this course we will discuss the key features and characteristics of knowledge graphs. You will learn all what is necessary to design, implement, and apply knowledge graphs. The focus of this course will be on basic semantic technologies including the underlying principles of knowledge representation and symbolic AI. This includes information encoding via RDF triples, knowledge representation via ontologies with OWL, efficiently querying knowledge graphs via SPARQL, latent representation of knowledge in vector spaces, as well as knowledge graph applications in innovative information systems, as e.g., semantic and exploratory search. Furthermore the role of knowledge graphs in artificial intelligence and machine learning will be discussed, as well as their potential to improve explainability and trustworthiness of "black box" deep learning models such as Chat-GPT.


  • Basic understanding of knowledge graphs
  • Basic understanding of ontologies
  • Basic understanding of Semantic Web Technologies
  • Basic understanding of ontology design and knowledge graph construction
  • Basic understanding of knowledge graph embeddings


  • students
  • practitioners of computer science, digital humanities, and information sciences
  • enthusiats with an AI related background and an interest in symbolic knowledge representation


  • Week 1

  • Week 2

  • Week 3

  • Week 4

  • Week 5

  • Week 6

  • 7 Final Exam

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该课程是免费的。 只需在openHPI上注册一个帐户并参加课程!

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Course End
11月 21 2023
Course Start
10月 11 2023




  • 课程证书 授予者需要至少取得课程总分的百分之 50%
  • 参与证明 授予者需要至少学习了所有课程资料的百分之 50%



Prof. Dr. Harald Sack

哈拉尔德-萨克是卡尔斯鲁厄FIZ-莱布尼茨信息基础设施研究所和卡尔斯鲁厄技术研究所的信息服务工程教授。1990年在联邦部队慕尼黑校区大学计算机科学专业毕业后,1990-1997年他在德国联邦部队的信号情报团担任系统/网络工程师和项目经理。1997年,他成为特里尔大学 "数学优化 "研究生项目的联系成员,并于2002年获得计算机科学博士学位。2002-2009年在耶拿的弗里德里希-席勒大学担任博士后。2009-2016年,他在波茨坦大学哈索-普拉特纳信息技术-系统工程研究所(HPI)担任高级研究员和 "语义技术 "研究组组长。



Harald Sack在国际期刊和会议上发表了200多篇论文,包括三本网络技术的标准教科书。他是yovisto GmbH(的共同创始人。