Spatial Data Storage

Total Hours in Course120

Number of hours for lectures24

Number of hours for seminars and practical classes0

Number of hours for laboratory classes32

Independent study hours79

Date of course confirmation13.12.2023

Responsible UnitInstitute of Computer Systems and Data Science

Course developer

prof.

Gatis Vītols

Dr. sc. ing.

Replaced course

InfT3043 [GINT3043] Spatial Data Storage

Course abstract

Studies of basic functionality of database technology are performed. Basics of database design and data models are discussed, including concepts of spatial data. Students learn to develop, bond and normalize data tables. Table relationships and basics of data retrieval are learned. Data retrieval from tables with structured query language are discussed and practically applied. Spatial query basics are introduced. Students gain practical knowledge about work with database management system PostgreSQL and develop semester assignment about storage of spatial data.

Learning outcomes and their assessment

Students know about general concepts of database technology, spatial data and Structured Query Language SQL. Evaluated in Test No. 2.
Gain skills about the development of databases for storage of various data types, examination of data table design, elimination of design inconsistencies and retrieval of data with Structured Query Language are acquired. Evaluated in Test No.1 and Test No. 3.
Develop competences of group or individual data analysis, choosing and taking part in discussions about the technological solution for data storage and retrieval. Evaluated using semester assignment.

Course Content(Calendar)

Full-time studies:
1. Data, information, knowledge (1h).
2. Understanding data model (1h).
3. Relational data model (1h).
4. Table normalization (1h).
5. Database management systems (1h).
6. Relational database model development for particular task (2h).
7. Architecture of PostgreSQL database management system (2h).
8. Relational database table development (2h).
9. Data definition language statements and application (2h).
10. Table joins (1h).
11. Recursive join (1h).
12. Structured Query Language (2h).
13. Spatial data storage (3h).
14. Single-table data retrieval (1h).
15. Multiple table data retrieval (1h).
16. Spatial data retrieval and extensions (2h).

Part-time studies:
All topics specified for full-time studies are implemented, but the number of contact hours is 1/2 of the specified number of hours

Requirements for awarding credit points

Exam
To take the exam, all laboratory work must be completed and defended, and all tests must be successfully passed.
Tests:
Test 1: Creating a relational database model for a specific problem domain.
Test 2: Management of relational and spatial data and data retrieval.
The exam consists of two parts:
In the first part, the student receives one of the exam task variations and answers theoretical questions orally.
In the second part, the student is given a practical task, which must be implemented in the specified database management system.

Description of the organization and tasks of students’ independent work

In semester assignment students must develop database project using skills acquired during the course. It is necessary to use knowledge and skills acquired during laboratory assignments and create database project, documentation for the project as well as students need to be able to explain and answer questions about the project. Section about spatial data management is mandatory

Criteria for Evaluating Learning Outcomes

Practical work is graded as "Pass" or "Fail." Tests are graded on a 10-point scale. Each task has a specified maximum score that can be earned for its completion.

Students have the option to retake one of the tests before the start date of individual study assessments.

Exam Structure and Scoring:
The exam consists of two parts:

Part 1 – A maximum of 3 points can be earned.
Part 2 – A maximum of 7 points can be earned.

Compulsory reading

1. Date C.J. An Introduction to Database Systems, An 8th Ed. Boston: Addison Wesley, 2004. 1024 p.
2. Kumar V.N.A. PostgreSQL 13 Cookbook: Over 120 recipes to build high-performance and fault-tolerant PostgreSQL database solutions, 2021. 344 p.
3. Coronel C. Database principles: fundamentals of desing, implementation and management. Andover: Cengage Larning, 2013. 866 p. 3. Oppel A.SQL: a beginners guide New York: McGraw-Hill, 2016. 533 p.
4. PostgreSQL. PostGIS documentation. https://postgis.net/documentation/

Notes

Professional higher education bachelor study program “Geoinformatics and Remote Sensing” in full-time studies and part-time studies

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