Principles of spatial data quality (terminology in the
field of spatial data quality, the importance of data
quality and standardization, standardized data
quality models, elements of data quality; data
quality control in GIS);
Official spatial data sets, voluntary geographic data
and information collection;
Integration of spatial data sets, process models for
transformations between different data formats;interoperability, INSPIRE directive, spatial data
infrastructure, semantic integration of spatial data;
open GIS;
Spatial data for decision-making, methods of multi-
criteria decision-making in GIS;
Internet and web-GIS, their relation to GIS
technology, web communication and spatial data
transfer, web GIS;
Mobile GIS and spatial data handling in the field;
field computers, wireless data transfer and
communication;
Cost and benefit analysis and its application in the
domain of geoinformation, value chain of spatial
(geographic) data;
Vector and raster data models for graphical
presentation of spatial data, 3D- and 4D spatial data
models, advantages and weakness; importance and
definition of topological rules, visualization;
Archiving of spatial data and spatial data backups;
optimization of GIS procedures, modelling of data
schemes, data migrations protocols, automation of
GIS analyses . Intended learning outcomes: Understanding of the spatial data domain and
advanced theoretical approaches and technological
processes in the field of geoinformation;
Understanding of the characteristics, strengths and
weaknesses of existing data models and data
processing methods for a given application domain;
Understanding of advanced geoinformatics solutions
and capacity of their suitable use for the selected
purposes
