Based on the user needs assessment we have designed and implemented a computing infrastructure to serve high-priority activities, such as exploratory research, prototyping, and self-learning. It is tailored for big data analysis, but feel free to use it for other geospatial computing needs!
Each working environment is containerized and isolated from each other and also from the host unit to ensure privacy.Powered by Docker
Built on a cluster of computing units, the platform scales automatically and balances workload among the units.Powered by Docker Swarm
Your assets are protected against hardware failures through replicated storage with minimum two physical copies.Powered by ZFS
Each computing unit has 8-core ARM v8.2a 64-bit CPU, 512-core Volta GPU with Tensor Cores, and 32GB 256-bit LPDDR4 RAM.Powered by Jetson AGX Xavier
Software packages are ready to use out-ot-the-box, without any further setup required.
Software packages are kept current to allow the use of latest, state of the art features.
Software packages are fine-tuned for best performance utilizing high-performance, multi-threaded libraries.
Computing units operate at 10–30W ensuring low energy footprint, albeit high performance.
The platform utilizes innovative hardware and state-of-the-art software components to provide a highly-available and performant computing environment.
NVIDIA Jetson AGX Xavier units with 1 TB local and 200 TB network storage connected through Gigabit Ethernet empower the platform.
Interactive Jupyter notebooks provide easy to use and user friendly data analysis and visualization environment.Powered by JupyterLab
All units in the platform and their GPUs are available for distributed out-of-core geospatial data analysis purposes.Powered by Dask and Apache Spark
Multiple programming languages can be used to access platform resources and perform geospatial computations.
Quite often you may also need additional services, such as a database to store your data, a map server to publish your maps, a data repository to share your research data. To facilitate and support your work we provide some out-of-the-box services!
Open source server for sharing geospatial dataAccess
Open source platform for publishing spatial dataAccess
Open source relational databaseAccess
Open source relational databaseAccess
Open source research data repository softwareIn cooperation with ITC Research Data Team
Open source lightweight code hosting solutionAccess
Open source platform to collect data quickly, accurately, offline, and at scaleAccess
How can I access to the platform?
You can access to the platform at https://crib.utwente.nl/geospatialhub by using your personal University of Twente account (i.e., e-mail address and password).
Unless stated otherwise, all additional services (e.g. GeoServer, Gitea) can also be accessed in the same way. Each service may require you to sign in separately.
Is it secure?
Your working environment is created on demand and isolated from the others which are active on the platform. Therefore, your assets (e.g. files, documents, images, etc.) are only accessible to you.
The platform uses University of Twente LDAP service to authenticate your credentials also through a secure connection and does not store your password.
How can I use the platform?
The default interface of the platform is JupyterLab, which enables you to work with interactive notebooks and documents through text and code editors, terminals, and other custom components (e.g. map widgets).
If you are new to JupyterLab (or Jupyter notebooks in general), a good starting point is its official documentation, which includes a detailed user guide. There is also a nice and short (~ 6 min.) introduction video available.
For specific components integrated to the platform (e.g. Code Server), please refer to their own documentation.
Which languages are supported by the platform?
The platform has kernels for Python (3.8.5), R (4.1.0), Go (1.16.3), Julia (1.5.4), Java (11.0.11), Scala (2.12.12), PHP (7.4.3), Ruby (2.7.0), Octave (6.2.0), dot (2.43.0), gnuplot (5.2) which you can use in interactive notebooks. All these languages are also accessible through the terminal interface. By using the terminal you can also use C (GNU 9.3), C++ (GNU 9.3), Fortran (GNU 9.3), Perl (5.30), and CUDA (10.2).
Which libraries and packages are supported by the platform?
Complete list of system packages (including low-level libraries, e.g. OpenBLAS, ATLAS, PROJ, GDAL, etc.) and language-specific packages (e.g. Python and R packages) are listed under
public/platform folder on the platform.
Why the latest version of xxx is not available?
We do our best to make the latest versions of software packages and libraries available. However, occasionally certain versions of the packages are not compatible to each other or not fully supported by the platform architecture (Linux / ARM v8.2a) - so we have to choose. If you are not happy with the selection please let us know.
Why xxx is not available?
We are trying to make widely-used software packages and libraries available with a special focus on geo-information and Earth observation. In fact, we did a survey to understand your needs and determined the list accordingly. We will periodically review this list and add more packages.
If the software package you need is not available on the platform (yet), the reasons could be:
Can I install software packages?
Sure. System-wide packages are protected, but you can install additional software packages to your workspace (i.e. home folder). For Python, you can use pip. For R, you can use
install.package() command. Please contact us for other languages and low-level libraries.
Do you have question on the platform and related services?
Do you need additional software packages and services?
Are you interested in collaborating with the Center of Expertise in Big Geodata Science?
Contact us to share your questions and discuss the possibilities!