1. Subject name |
Planning of Transport Databases (PhD) |
2. Subject name in Hungarian |
Közlekedési adatbázisok tervezése (PhD) |
3. Code |
BMEKOKUD004 |
4. Evaluation type |
exam grade |
5. Credits |
2 |
6. Weekly contact hours |
0 (0) Lecture |
2 (0) Practice |
0 (0) Lab |
7. Curriculum |
PhD Programme |
8. Role |
Specific course |
9. Working hours for fulfilling the requirements of the subject |
60 |
Contact hours |
28 |
Preparation for seminars |
0 |
Homework |
20 |
Reading written materials |
8 |
Midterm preparation |
0 |
Exam preparation |
4 |
10. Department |
Department of Transport Technology and Economics |
11. Responsible lecturer |
Dr. Juhász János |
12. Lecturers |
Dr. Juhász János |
13. Prerequisites |
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14. Description of lectures |
The aim of the course is to learn how to capture, store, collect and analyse traffic-related data, to get to know, choose and apply the most common methods:
- Methods of collecting and storing traffic data. Sources of error.
- Questionnaire data collection forms, ways of storing and processing data, transport applications.
- Description of data model types, presentation of their usage possibilities.
- Structure, characteristics and comparison of OLAP, MOLAP, ROLAP, OLTP systems.
- Big Data's theoretical background, overview of transport examples.
- Characteristics and methods of analysis of GIS databases. Traffic location identification systems.
- The system of registration, construction, information content of road accidents involved injured persons.
|
15. Description of practices |
Exercising theoretical knowledge with examples and case studies. |
16. Description of labortory practices |
|
17. Learning outcomes |
A. Knowledge
- Knows the methods of collecting traffic data.
- Knows the different data model types.
- Knows the structure, characteristics and peculiarities of OLAP, MOLAP, ROLAP, and OLTP systems.
- Knows the Big Data's theoretical background.
- Knows the structure and main characteristics of GIS systems.
- Knows the structure of the road accident database.
B. Skills
- Able to design and execute data collection.
- Able to design and build a data storage structure.
- Able to select the most suitable data model type for the purpose.
- Able to design and prepare a geospatial database, to map data, to create spatial queries.
- Able to retrieve information from a personal road accident database.
C. Attitudes
- The student attends the lectures, prepare independent study on time.
- During the lectures, he is actively involved in processing the current topic.
- During the independent study the student strives to develop new technical solutions.
- Interested in international and domestic developments in the field.
- Open to learn new knowledge and learn.
D. Autonomy and Responsibility
- Apply responsibility the knowledge acquired in the course of the course.
- Can independently develop new technical solutions.
- Accepts the framework of collaboration, can perform its work independently or as part of a team, depending on the task.
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18. Requirements, way to determine a grade (obtain a signature) |
Exam. Evaluation of individual study. |
19. Opportunity for repeat/retake and delayed completion |
Retake exam. Study repair |
20. Learning materials |
Supported by downloadable documents from the Department website |
Effective date |
27 November 2019 |
This Subject Datasheet is valid for |
Inactive courses |