198847 VU Data Analysis II: Semantic and Spatial Information Integration
summer semester 2022 | Last update: 03.03.2022 | Place course on memo listUnder the successful completion of this course students understand the basics of creating, managing and analysing spatial data used in Geoinformation systems and semantic data as used in Linked Open Data. A creation and integration pipeline for both data types will be applied by the students for information integration. They acquire the ability to use selected methods of relational databases (SQL), geoinformation systems and semantic technologies and are capable of creating semantic data related to geodata. They understand the potential of automating specific tasks with Python.
- Introduction to a data processing pipeline using semantic and geoinformation methodologies for information integration.
- Technological and theoretical backgrounds of geodata and geoinformation systems.
- Technological and theoretical backgrounds of ontologies and semantic technologies.
- Examples of semantic and geodata creation in different fields, like (historic) texts or structured data.
- Basic skills in semantic technologies (RDF-creation) and geoinformation processing.
- Use of Python with files/databases/geoinformation systems to automate specific tasks of the pipeline.
- Practical skills to create, manage, manipulate data in Postgres and Triple stores and visualize/analyse them in Geoinformation systems through a mini project.
Presentation of lecture slides by lecturer to provide a summary of learning material; using of flipped classroom and exercises in the class for hands-on exercises working with databases and geodata as well as using Python to automate tasks. Creation and query of RDF data; working on mini projects and presentation of results by participants.
Participants are graded through marks of oral exams for the lecture part and in-class presentation of classroom exercises and mini projects. Details will be announced in the first session.
- N. Bartelme (2005): Geoinformatik, Springer.
- J, Campbell, M. Shin (2011) Essentials of Geographic Information Systems, ISBN 13: 9781453321966.
- D. Bodenhamer, J. Corrigan, T. Harris (2010) The Spatial Humanities.
- D. Allemang, J. Hendler (2011) Semantic Web for the Working Ontologist, 2nd edn. Morgan Kaufmann.
Participants are required to use their (laptop) computers (Windows, Linux, Mac) to the class for hands-on exercises. Basic knowledge of relational databases and SQL as well as Python coding is necessary.
The following tools will be used:
- GIS: QGIS (https://www.qgis.org/de/site/)
- Database: Postgres/Postgis (https://www.postgresql.org/)
- Semantic Data: Karma (https://usc-isi-i2.github.io/karma/); GraphDB (https://www.ontotext.com/products/graphdb/)
- Programming: Python (https://www.python.org/)
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- Faculty of Mathematics, Computer Science and Physics
- Interdisciplinary and additional courses
- Minors (Complementary Subject Area)