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Main menu for Browse IS/STAG
Course info
KGM / PDB
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Course description
Department/Unit / Abbreviation
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KGM
/
PDB
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Spatial Databases
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Form of course completion
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Exam
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Form of course completion
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Exam
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Accredited / Credits
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Yes,
4
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
1
[Hours/Week]
Tutorial
2
[Hours/Week]
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Course credit prior to examination
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Yes
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Course credit prior to examination
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Yes
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Included in study average
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YES
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Language of instruction
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Czech
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Occ/max
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Summer semester
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0 / -
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0 / -
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0 / -
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Included in study average
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YES
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Winter semester
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1 / -
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7 / -
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2 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Winter semester
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Semester taught
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Winter semester
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Minimum (B + C) students
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1
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
1|2|3|4 |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
Yes
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Fundamental course |
Yes
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Fundamental theoretical course |
Yes
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Evaluation scale |
1|2|3|4 |
Evaluation scale for credit before examination |
S|N |
Substituted course
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KMA/PDB
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Preclusive courses
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KGM/PDB-E
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Prerequisite courses
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N/A
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Informally recommended courses
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N/A
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Courses depending on this Course
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KIV/ISSZ
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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The main aim of this subject is to introduce the main principles of spatial databases. In particular the followings themes: Data structures for spatial data indexing. Algorithms of spatial databases. Spatial join in spatial queries. Spatial objects and SQL - Abstract Data Types. Data modelling in spatial databases (conceptual, logical and physical data model). Strategies and techniques for data conversion. Commercial and open source solutions.
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Requirements on student
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Students have to do semestral work to obtain credit. Next they have to present this work. The exam has two parts ? written and oral. Students have to obtain minimally 60% of all points in written test. Than the oral part of exam will follow.
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Content
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1. Introduction to spatial databases. Definition of the main terms.
2. Spatial data representation formats.
3. Query language for spatial data.
4. Modelling of spatial data with constraints.
5. Algorithms of spatial databases.
6. Data structures for spatial data indexing.
7. Spatial queries and spatial join.
8. Commercial and open source solutions for spatial data handling.
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Activities
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Fields of study
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Studentům jsou k dispozici studijní opory v elektronické formě.
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Guarantors and lecturers
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-
Guarantors:
Doc. Ing. Karel Janečka, Ph.D. (100%),
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Lecturer:
Doc. Ing. Karel Janečka, Ph.D. (100%),
Ing. Karel Jedlička, Ph.D. (100%),
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Tutorial lecturer:
Doc. Ing. Karel Janečka, Ph.D. (100%),
Ing. Karel Jedlička, Ph.D. (100%),
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Literature
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Basic:
Claramunt, C., Schneider, M., Wong, R.C.-W., Xiong, L., Loh, W.-K., Shahabi, C., Li, K.-J. Advances in Spatial and Temporal Databases. Hong Kong, China, 2015. ISBN 3319223623.
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Basic:
Arctur, David; Zeiler, Michael. Designing geodatabases : case studies in GIS data modeling. Redlands : ESRI Press, 2004. ISBN 1-58948-021-X.
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Basic:
Shekhar, Shashi; Chawla, Sanjay. Spatial databases : a tour. Upper Saddle River : Prentice Hall, 2003. ISBN 0-13-017480-7.
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Basic:
Rigaux, Philippe; Scholl, Michel; Voisard, Agn?s. Spatial databases : with applications to GIS. San Francisco : Morgan Kaufmann Publishers, 2002. ISBN 1-55860-588-6.
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Basic:
Janecka, K., Karki, S., van Oosterom, P., Zlatanova, S, Kalantari, M., Ghawana, T. 3D Spatial DBMS for 3D Cadastres. Copenhagen, Denmark, 2018. ISBN 978-87-92853-64-6.
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Recommended:
Beinat, Euro; Godfrind, Albert; Kothuri V, Ravikanth. Pro Oracle Spatial. Apress, 2004. ISBN 1-59059-383-9.
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On-line library catalogues
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Contact hours
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39
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Presentation preparation (report) (1-10)
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1
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Preparation for an examination (30-60)
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30
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Individual project (40)
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40
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Total
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110
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
to describe the possibilities of representations of geographical data in the digital form |
to describe the basic database objects of relational databases |
to describe the differences between a conceptual, a logical and a physical data model |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
to write a simple SQL DML query |
to propose a conceptual, a logical and a physical data model of the relational database |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
to describe the basic differences between a relational- and a spatial- database |
to characterise the basic properties of a data model for spatial data according to the ISO 19125 |
to explain the principles of selected data structures for spatial data indexing |
to propose a usage of an appropriate algorithm for selected task from the field of spatial databases |
to explain the principles of a spatial join |
Skills - skills resulting from the course: |
to propose a conceptual and a logical data model for storage of spatial data |
to describe the proposed data model by the means of UML |
to propose the suitable spatial data types for a physical data model |
to implement the physical data model in selected database managament system with a spatial option (Oracle Spatial, PostGIS, ESRI Geodatabase) |
Competences - competences resulting from the course: |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Seminar work |
Individual presentation at a seminar |
Written exam |
Practical exam |
Oral exam |
Skills - skills achieved by taking this course are verified by the following means: |
Seminar work |
Individual presentation at a seminar |
Oral exam |
Written exam |
Practical exam |
Competences - competence achieved by taking this course are verified by the following means: |
Seminar work |
Individual presentation at a seminar |
Written exam |
Practical exam |
Oral exam |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture supplemented with a discussion |
Task-based study method |
Skills demonstration |
Collaborative instruction |
Individual study |
Students' portfolio |
One-to-One tutorial |
Interactive lecture |
Discussion |
Skills - the following training methods are used to achieve the required skills: |
Lecture |
Lecture with visual aids |
Practicum |
Task-based study method |
Textual studies |
Skills demonstration |
Students' portfolio |
Collaborative instruction |
One-to-One tutorial |
Discussion |
Individual study |
Competences - the following training methods are used to achieve the required competences: |
Textual studies |
Task-based study method |
Individual study |
Students' portfolio |
Discussion |
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