Lecture Big Geospatial Data - Summer Term 2020

Aim of this Lecture

By completing this module, students will be enabled to work with big datasets of spatial nature both in scientific environments using cluster computing architectures based on MPI as well as in scalable computing models such as cloud computing more tailored to business adoption.

Contents

By completing this module, students will be enabled to work with big datasets of spatial nature both in scientific environments using cluster computing architectures based on MPI as well as in scalable computing models such as cloud computing more tailored to business adoption.

Time Table

This conference runs in an inverted classroom manner due to Corona. That is, every week, a detailed list of resources including

  • lecture videos
  • papers
  • screencasts

and other media is published here and in Moodle.

Then, students can attend an interactive walkthrough session as a video conference depending on the quality of video conferencing during semester.

In addition, a chat will be used for asynchronous exchange.

Every week, an open line hour will be held in this chat with options of breakout to video conferencing services.

The timing is not fixed as it will be coordinated with activities of others and availability of students.

Lets make the best we can in these difficult times!

tba

Lecture Slides

tba

Feedback and Support

We appreciate your feedback and support. You can drop me a line at any time. If you have interesting examples, you want to share with your fellow students, you can either send it to me via email or create a pull request on GitHub. I would be happy to include your examples, solutions and portations in the lecture.


Contact

Martin Werner
Professur für
Big Geospatial Data Management

Willy-Messerschmitt-Str. 1
82024 Taufkirchen/Ottobrunn
martin.werner(at)tum.de

© 2020 M. Werner