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Spatial Data Storage

Course developer

Replaced course

InfTB003 [GINTB003] Spatial Data Storage

Course abstract

The aim of the study course is learn basics of relational and spatial data storage and retrieval technologies.Studies of basic functionality of database technology are performed. Basics of database design and data models are discussed. 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. 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

As a result of mastering the course students:
• know about general concepts of database technology and Structured Query Language SQL. (Evaluated in Test No. 2.)
• have practical 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)
• are able working in group or individual to perform data analysis, choose and take 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 (2h).
2. Understanding data model (1h).
3. Relational data model (1h).
4. Table normalization (2h).
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 (2h).
14. Single-table data retrieval (1h).
15. Multiple table data retrieval (1h).
16. Possibilities for data grouping in queries (1h).

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

Test with mark. To acquire final mark, students must complete and defend all lab assignments and successfully pass all tests.
Test No. 1. Creation of relational database model for particular area of interest
Test No. 2. Creation of data tables and definition of joins. Data input and indexing.
Test No. 3. Spatial data management and retrieval

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

Learning outcomes are evaluated using marks acquired in each assignment. Final mark is calculated as average mark from tests and semester assignment, Student can re-take one of the assignments until beginning of individual examination session.

Compulsory reading

1. Date C.J. An Introduction to Database Systems., 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.
4. Oppel A. SQL: a beginners guide. New York: McGraw-Hill, 2016. 533 p.
5. PostgreSQL. PostGIS documentation. Pieejams: https://postgis.net/documentation/

Further reading

1. Žurnāls "Data Base Journal", QuinStreet. Pieejams: http://www.databasejournal.com

Notes

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