After completing this course successfully, the students are capable of:
- Explaining the term Ontology in its multiple interpretations, and their relations to Semantics and Semantic Interoperability.
- Explaining the nature and purposes of Conceptual Modelling. Historical Review of existing classical conceptual modeling languages (e.g., EER, UML, ORM, OWL); the role of logics in providing semantics for conceptual modeling languages; the role of domain-independent (foundational) Ontologies in Ontology- Driven Conceptual Modeling (ODCM).
- Explaining the modelling constructs, patterns, as well as computational and methodological tools of the OntoUML ODCM language ecosystem.
- Applying OntoUML to analyse and represent domains that have average complexity. Use complexity management techniques for dealing with the complexity of these models.
- Evaluating and Rectifying OntoUML models by (i) applying automated verification, (ii) detecting anti-patterns, (iii) identifying unintended interpretations of OntoUML models, (iv) removing anti-patterns and unintended interpretations by specifying constraints.
- Critically assessing and positioning OntoUML w.r.t. to classical conceptual modelling languages (e.g., EER, UML, ORM, OWL).
The main objective of this course is to equip students with the theoretical, methodological, and computational tools needed for addressing the requirements of Semantic Interoperability of modern model-based systems. In particular, the course focus on the development of a particular type of model termed a conceptual model. Conceptual Modelling is a discipline of great importance to several areas in Computer Science such as Software and Knowledge Engineering, Enterprise Modelling, Information Systems Design, Database Design, Knowledge Management, Artificial Intelligent, among many others. In particular, a Domain Ontology denotes a special type of Conceptual Model that captures the shared semantics of concepts, relations and constraints in that domain. |
The more specific objective of this course is then to introduce students to the theory and practice of advanced conceptual modelling in general, and domain ontology engineering, in particular, through the application of a new emerging discipline named Ontology-Driven Conceptual Modelling.
In recent years, there has been a growing interest in the development and use of Domain Ontologies in areas such as, for example, Finance, Robotics, Cybersecurity, Industry 4.0, IoT, Digital Twins, as well as in the FAIR data initiative. However, as we demonstrate in this course, an approach to ontology engineering uniquely based on logical languages (e.g., OWL, RDFS) is insufficient to address a number of semantic interoperability problems that arise in open and dynamic scenarios. We then show that these languages should be complemented by languages, methodologies and tools based on foundational theories, i.e., domain-independent ontological theories constructed by aggregating suitable contributions from areas such as philosophical ontology and logics, cognitive science and linguistics.
In this course, we give an introduction to a theoretically well-founded advanced conceptual modelling language designed to meet the requirements for semantic interoperability. Moreover, we present a number of modelling techniques as well as methodological (e.g., design patterns and anti-patterns) and computational tools, based on the foundations of this language, and show how they can be used to solve some classical and recurrent conceptual modelling problems that (re)appear in concrete application scenarios.
Assumed previous knowledge
|- Experience with any structural conceptual modeling language (e.g., ER, OWL, but preferably UML).|
- Basic knowledge of predicate calculus would be advantageous, but it is not formally a prerequisite.
|Master Business Information Technology||Required materials|
Recommended materials-Instructional modes
|Giancarlo Guizzardi. Ontological foundations for structural conceptual models, PhD thesis, University of Twente. 2005. https://research.utwente.nl/en/publications/ontological-foundations-for-structural-conceptual-models|
|Self study without assistance|