Summer School 2022 / KISTE project workshop:
“Open Source solutions for Earth system data
(R, OSGeo, Python)”
- Live presentations and demos by leading R and OSGeo developers,
- 5 days of Earth System Analysis training sessions and R / OSGeo tutorials
- Including 1 day of R-Spatial workshops,
- Including 1 focus day “extreme events”
- Discussion panels and break-out rooms.
Topics of interest
Topics of interested are focused around but not limited to (unsorted):
- AI for Earth System Sciences
- Modelling Extreme Events (with ML/AI and statistics) (~1 day)
- Classifying remote sensing time series data,
- Design-based methods for assessing map accuracy,
- Point pattern analysis in R,
- Analysing spatiotemporal disease/health data,
- Reproducible research,
- Machine Learning and deep learning methods for spatial data,
- Analyzing massive amounts of EO data in the cloud with R, gdalcubes, and STAC,
- Running a Research Data infrastructure with OS Tools
- Geocomputation and spatial segmentation in R,
- Static and interactive visualization of spatial data
Social events & hackathon
Recipe: Pre-order the group by their broader interest into subgroups. Split each subgroup equally where one half will be stationary and the other half be moving “clockwise” through the room. Pairs of people sit down for a given amount of time (~7 mins) and present their research topic to each other.
Recipe: Interested participants sign up for a 3-min-madness where they pitch their research in 3 min “on stage” in front of all participants. Elect a jury (among the lecturers) that will ask quick questions and will finally vote for the “best pitch”. This could also be flavored towards a “science slam”.
Participants can nominate their latest research for a reproducibility check. Share your paper and the associated resources with the group and let’s explore how far we can reproduce your study and whether everyone achieves the same result.
Registrations & Fees
Participating in person
Max capacity: 80
Full price: 625 EUR. Reduced price: 475 EUR for full-time students / ODA-recipient country. Join the physical event in Siegburg and enjoy the full experience! You will interact directly with the experts, network with peers and join the social events (dinners, Research Speed Dating; 3-min-madness; Reproducibility Hackathon). The fees cover costs of using facilities, lunch and coffee breaks, gala dinner and costs of travel and accommodation for lecturers and are determined per cost-recovery basis.
- Conference center
- Coffee and drinks
- Lunch (per-person-per-day)
- Lecturers reimbursment
- Hackathon, Research Speed Dating, 3-min-madness
- Gala dinner & Social events
Max capacity: 500
International participants will be able to follow the blocks of interest via the Zoom Webinar livestream service with the possibility to ask questions to the lecturers. This option does not require any fees, however virtual participants will not be able to follow hackathons and workshops aiming at smaller groups, or interact with the other participants during the social events.
- Live broadcast of main lectures
- Live discussion panels
- Questions to lecturers
- Social events, hackathons & other side events
- Live support
- Extra crash courses
Why should you attend this event?
- Find out what are the trends in spatial analysis and modeling from the leading open source developers.
- Follow online demo’s / tutorials, ask questions, share your experiences and help us resolve important issues.
- Connect to similar participants and network. Find co-authors and co-creators that match your style of work and ambitions.
- Contribute to the Open Source community and global good.
We have made a reservation at the Friendly City Hotel Siegburg close to Bonn for the period 28.08.2022 – 03.09.2022. They offer large and well equipped conference rooms and the venue would also allow for us to host parallel sessions as in previous years.
The offer includes:
- Air-conditioned conference room (max capacity 80 people) with balcony & including standard equipment (beamer, screen, 3 flipcharts, 3 moderator boards, paper & pencils);
- Free internet access throughout Hotel (600Mbit);
- Coffee & tea all day long from the specialty (in front of the conference room); soft drinks will be charged to according consumption;
- Candy bar with sweet and sour delicacies (in front of the conference room);
- Active break in the morning: coffee from the machine specialty & various tea, fruit juices & sandwiches;
- Vital lunch at noon the finger food in front of the room or buffet in the restaurant included octopus water on the table;
- Active break in the afternoon: coffee from the specialty machine & various tea, fresh-cut fruit and pastries;
Accommodation costs (fixed price):
- 105 EUR bed & breakfast (single);
- 140 EUR bed & breakfast (double occupancy);
The pricing is at the upper boundary of what appears reasonable. Rooms and facilities appear to be modern and of good quality. The hotel is rated 3-star and has a 8.1 on booking.com.
** Under construction **
Materials in terms of R-markdown tutorials, screen-recordings and similar will be provided to all participants before the start of the Summer School.
Technology in use
Virtual machines / software installation
For consistency we recommend that all participants use a prepared virtual machine (docker containers), best via:
This would make sure that everyone follows exactly the same settings / same package versions etc.
Use of virtual containers / virtual OS comes at the cost of RAM, so we need to provide to all participants instructions on how to prepare and emphasize that their laptops should have a minimum configuration of 16GB RAM and similar.
All lectures will be video-recorded using Zoom webinar functionality in HD quality. Subject to approval of the presenters, the videos will be uploaded to https://av.tib.eu/publisher/OpenGeoHub_Foundation and a DOI will be assigned to each talk. Lecturers will be asked to accept the general recording conditions and sign a document allowing for videos to be shared. Copyright of the video’s will be assigned to authors / presenters as in standard Open Access materials.