Ruprecht-Karls-Universität Heidelberg
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Module for [Scientific Computing]

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[Spatial Databases] - [2015 Sommer]

Module Code
IRDB
Name
Spatial Databases
Credit Points
8 LP CP
Workload
240 h
Duration
ein Semester
Cycle
0
Methods Lecture 4 h + Exercise course 2 h
Objectives
Content Principles and requirements of managing spatial data Application domains of managing and analyzing spatial data Support of managing spatial data using commercial and open-source DBMS Concepts and methods for representing spatial data in 2d and 3d; tessellation and vector model, groups of spatial objects abstract data types for spatial data Fundamentals of computational geometry (e.g., convex hull, sweep-line techniques, polygon partitioning, cut of polygons) Access structures for spatial data, in particular grid-files, kd-tree, quad-tress, and R-trees Algorithms and cost models for using spatial index structures Principles of spatial query processing and optimization, in particular spatial join techniques Temporal databases and index structures Moving objects: applications, querying, and index structures Introduction to mining spatial data (clustering, outlier detection)
Learning outcomes Knowing the principles and requirements underlying spatial data and the management of such data in different application domains (e.g., geography, biology, cosmology) Knowing the concepts and applications related to geographic information systems Be able to apply concepts and techniques for modeling spatial data Be familiar with the management and querying spatial data using a spatial database management system (e.g., PostGIS) Knowing fundamental methods of computational geometry Knowing important index structures for spatial data such as the grid-file, kd-tree, Quad-tree, and R-tree.
Prerequisitesnone
Suggested previous knowledge Algorithms and data structures (IAD); Introduction to databases (IDB1)
Assessments Assignments; at least 50% of the credit points for the assignments need to be obtained to be eligible to participate in the final written exam
Literature Spatial Databases – With Applications to GIS. Philippe Rigaux, Michel Scholl, Agnes Voisard. Morgan Kaufmann, 2001.
Computational Geometry: Algorithms and Applications Mark de Berg, Otfried Cheong, Marc van Kreveld, und Mark Overmars, Springer, Berlin, 2008.
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