[ISTDB] - [2018 Sommer] - [de] - [Spatial and Spatio-temporal Databases]


Spatial and Spatio-temporal Databases [2018 Sommer]
Code
ISTDB
Name
Spatial and Spatio-temporal Databases
Leistungspunkte
8 LP
Dauer
one semester
Turnus
every 2nd to 3rd winter semester
Lehrform
Lecture 4 SWS + Exercise course 2 SWS
Arbeitsaufwand
240 h; thereof
90 h lecture
20 h preparation for exam
130 h self-study and working on assignments/projects (optionally in groups)
Verwendbarkeit
B.Sc. Angewandte Informatik,
M.Sc. Angewandte Informatik,
M.Sc. Scientific Computing
Lernziel Students
- have a solid understanding of concepts, models, and techniques underlying the modeling, management, processing, and querying of diverse types of spatial and spatio-temporal data
- know important spatial and spatio-temporal indexing structures
- can employ core algorithmic frameworks for processing spatial and spatio-temporal queries
- can apply key algorithms adopted from computational geometry
- can apply suitable data management techniques using systems such as PostgreSQL or PostGIS
Inhalt - 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 models, 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
- Spatio-temporal databases and index structures
- Moving objects: applications, querying, and index structures
- Introduction to mining spatio-temporal data
Voraussetzungen recommended are: Algorithmen und Datenstrukturen (IAD), Datenbanken (IDB)
Prüfungs
modalitäten
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; students can also work on a project (non-graded); final written exam
Literatur - Philippe Rigaux, Michel Scholl, Agnes Voisard: Spatial Databases – With Applications to GIS. Morgan Kaufmann, 2001.
- Mark de Berg, Otfried Cheong, Marc van Kreveld, and Mark Overmars: Computational Geometry: Algorithms and Applications Springer, Berlin, 2008.
- Xiaofeng Meng,? Zhiming Ding,? Jiajie Xu: Moving Objects Management: Models, Techniques and Applications. Springer, 2016.