Code               202100291
Title                Ontology-Driven Conceptual Modelling
Type                Master course (M-IST, M-BIT, M-CS)
Year                 2023-2024
Period             2B
Credits            5 ECTS
Language        English

Learning outcomes

After completing this course successfully, the students are capable of:

1. Explaining the nature and purposes of Conceptual Modelling. Historical Review of existing classical conceptual modeling languages (e.g., UML, ER, BPMN, Archimate); the role of Foundational Ontologies in Ontology- Driven Conceptual Modeling (ODCM).
2. Explaining the modelling constructs and patterns of the OntoUML ODCM language.
3. Applying OntoUML to analyse and represent domains that have average complexity.
4. 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.
5. Critically assessing and positioning OntoUML w.r.t. to classical conceptual modelling languages (e.g., EER, UML, ORM, OWL).

Lecturers                     G. Guizzardi, L. Ferreira Pires
Mode of delivery        Face-to-face learning with work sessions
Prerequisites               Experience with a structural conceptual modeling language (e.g., ER, OWL, but preferably UML), basic knowledge of predicate calculus and/or first-order logic.

Course contents
The main objective of this course is 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. 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, among many others. In particular, a Domain Ontology denotes a special type of Reference Conceptual Model that formally defines concepts and their relationships of a specific domain. In recent years, there has been a growing interest in the development and use of Reference Conceptual Model in areas such as, for example, Finances, 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 for reference conceptual modelling 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 a language and methodology based on a Foundational Ontology, i.e., a domain-independent common-sense theory 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 conceptual modelling language designed to meet the desiderata for a general conceptual modelling. Moreover, we present a number of advanced conceptual modelling techniques, such as design patterns and methodological guidelines, 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

Course material
The material of this course consists of:

• Book: Giancarlo Guizzardi. Ontological foundations for structural conceptual models, PhD thesis, University of Twente. 2005.
• Slides to be found on this Canvas site.
• Other documents (papers, standards, etc.) to be found on this Canvas site.

Planned teaching and learning activities

The following learning activities are planned in this course:

• Lectures that address methods, techniques and typical problems related to Ontology-Driven Conceptual Modelling, in general, and OntoUML, in particular. These lectures are given in the form of a discussion forum, which means that you must prepare yourself by reading the material before the lecture. During some lectures you will be asked to do some simple exercises with pen and paper but also with the OntoUML tool, so you are expected to bring your laptop to the lectures. Slides will be made available in the Canvas Site after each lecture.
• Practical sessions that have been designed to motivate the students to practise with the techniques discussed during the lectures.
• Project to be performed by groups of two students. For the project, students will be asked to choose a modelling domain of their interest to work on. In the project, students have to submit two deliverables.
• Final exam that consists of questions on the subjects discussed during the lectures and the practical sessions.

The project tasks are the following:

• Task 0: Project proposal not graded, students get feedback on the feasibility of the project.
• Task 1: Model Building Developing an OntoUML model for a domain of interest chosen by each of the groups.
• Task 2: Model Evaluation Performing automatic verification of the OntoUML produced and eliminating all possible errors detected; identifying potential unintended interpretations(possibly with the support of Anti-Pattern detection); propose a list of constraints that rectify the model by eliminating the unintended interpretations identified.

For each of these tasks a report should be delivered by the project groups and feedback is given by the lecturers.

Assessment methods and criteria

In this course students, are assessed and graded based on the results of the practical sessions, the project and the final exam.

• Practical sessions (Lab) During the course, students have to participate in six practical sessions. The practical sessions are mandatory, i.e., students have to actively participate in all the practical sessions in order to pass the course. Students who fail to participate in the practical sessions get no access to the final exam and are excluded from grading. No mark is assigned to the practical sessions.
• Project In the project, students work in groups of three students. Each project group submits two deliverables. The project result is determined by the results of the project milestones, and it counts for the final mark only if all project deliverables are properly submitted and the presentation is delivered, otherwise no project grade is issued.

Warning: In this course you get a lot of freedom for doing the project. You are requested to develop original solutions to the exercise series, which means that copying solutions from books or other groups is considered as fraud. Once the instructors detect any form of fraud, the Examination Board will be informed, which can bring severe consequences for the students involved. Similar punitive measures will also be taken against groups that make their results available to other groups.

Final mark calculation

The final mark of this course is determined by the results of the project result and the final exam. A mark higher than 5.0 for the exam and the project is necessary for a final mark higher than 5.0 in this course. The final mark is determined by the following formula:

P = T1 * 0.6 + T2 * 0.4 If E >= 5.0 and P >= 5.0 then F = (( E + P )/2)
else F = min (5.0, (( E + P )/2)

where: 

• F denotes the final mark.
• P denote the final mark of the project considering the two deliverables according to the formula above. •
• E denotes the final exam.
• Tn denotes the mark of task n.

Remark: The marks for tasks T1 and T2 is the same for all members of the group, while the mark for E is individual.