Data Modelling in Engineering
Objectives
1. Knowledge: a) Base modeling concepts and their applicability to engineering. b) Becoming familiar with various modeling formalisms.
2. Know-how: a) Capacity to model small systems. b) Abstract modeling skills.
3. Non-technical skills: a) Team work. b) Time management.
General characterization
Code
7226
Credits
6.0
Responsible teacher
Luís Manuel Camarinha de Matos
Hours
Weekly - 4
Total - 63
Teaching language
Português
Prerequisites
Programming skills.
Bibliography
1. Course notes - L.M. Camarinha Matos
2. The essence of databases - F. D. Rolland, Prentice Hall, 1998, ISBN 0-13-727827-6
3. AI through Prolog . Neil C. Rowe, Prentice Hall, ISBN 0-13-049362-7.
4. UML for Systems Engineering: Watching the Wheels, Jon Holt , 2001, ISBN:0852961057.
Teaching method
The course includes a theoretical-practical component and a laboratory component. The theoretical-practical component is provided through formal lectures on the concepts proposed in the program, complemented with exercises. The course has continuous assessment, by conducting evaluation tests carried out during the semester.
The practical component is provided through laboratory work, supported by teaching staff, where students work in groups to solve practical problems within this area. The evaluation is made on the results obtained in these works.
The rating is given by the average of the two evaluation components.
Evaluation method
3 Mini-tests - 60% (33.33%, 33.33%, 33.33%)
3 Lab Works - 40% (37.5%, 37.5%, 25%))
Minimum score: Tests >=9.5 Lab works >= 9.5
Subject matter
| 1. | INTRODUCTION | ||||
| 2. | MODELING BASED ON RELATIONAL MODEL
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| 3. | MODELING BASED ON LOGIC PROGRAMMING
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| 4. | MODELING BASED ON FRAMES
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| 5. | GRAPHICAL LANGUAGES - UML | ||||
| 6. | INTRODUCTION TO ONTOLOGIES |