Section outline

  • In this module, you will learn how Knowledge Graphs are used in the Social Sciences and Humanities to structure and link information. You will explore the standards and formats that make data interoperable and reusable, with a focus on W3C recommendations. You will also gain a clear understanding of what an ontology is, how it supports knowledge representation, and how it is applied in real-world contexts such as medicine, smart cities, and digital humanities. Finally, you will be introduced to key ontology representation languages like RDF and OWL.

    • 2a. KG for SSH
      This course begins by introducing the concept of a graph — a structure made of nodes and links used to represent relationships between entities. Building on this foundation, it explores how graphs evolve into Knowledge Graphs (KGs) when the nodes and links carry semantic meaning. Led by Dr. Maria Papadopoulou, Assistant Professor in Digital Humanities & Classics, the course guides learners through how KGs represent real-world knowledge in a machine-readable form. By using subject-predicate-object triples, KGs encode facts and reveal complex relationships between people, places, events, and ideas. The course showcases how these models are built, how Uniform Resource Identifiers (URIs) give unique meaning to concepts, and how KGs support reasoning, search, and data integration. Real examples—from the Peloponnesian War to museum datasets—demonstrate their power in the SSH context. Through this approach, the course equips learners to model, query, and link information in ways traditional databases cannot.

    • 2a. KG for SSH (Intoduction)

    • Knowledge Graph for SSH - Introduction (mp4-en) File
    • KG4SSH Introduction (ppt in pdf format) File
    • 2a. KG for SSH (Part I)

    • KG4SSH Part I (mp4-en) File
    • KG4SSH Part I (ppt in pdf format) File
    • 2a. KG for SSH (Part II)

    • KG4SSH Part II (mp4-en) File
    • KG4SSH Part II (ppt in pdf format) File

    • 2b. What is Ontology?

      This MOOC provides a structured introduction to ontology as understood in Knowledge Engineering. It is organized into six main sections. The first part explores the origins of ontology, tracing its roots from philosophy to its contemporary use in computer science. The second section provides definitions of ontology, particularly in the context of information systems and knowledge sharing, emphasizing the formal specification of conceptualizations that can be interpreted by machines.
      Next, three concrete examples—drawn from medicine, smart city systems, and digital humanities—illustrate how ontologies are used in practice to organize knowledge, enhance interoperability, and manage complex data structures. The fourth section examines theories of concept, which underpin various approaches to conceptual modeling. It distinguishes between essential and descriptive characteristics, and explains the difference between concepts and classes as units of knowledge organization.
      The fifth section surveys different ontology representation languages, including graphical, AI-based, logical, and W3C languages such as RDF and OWL. These languages vary in formality, expressiveness, and suitability depending on the application domain. The final section presents two ontology-building environments—Protégé and Tedi—highlighting their respective modeling paradigms and practical uses in constructing ontologies based on either class-based or concept-based approaches.

    • What is Ontology? (mp4-en) File
    • What is Ontology? (mp4-fr) File
    • What is Ontology? (ppt in pdf format) File
    • What is Ontology? (ppt with script in pdf format) File
    • 2c. Quiz on Module 2
    • Quiz on Knowledge Graph Module