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Kooplex is a collaborative data analytics platform which is built around the transparent shareable framework of the Jupyter ecosystem. It includes many components which are related to the topics of authentication and user database, project management, pipeline creation, data exploration, notebook versioning, shareable data analysis and collaborative forum.
In this application, the container always refers to Docker container. Docker computer program implements OS-level, lightweight virtualization (a.k.a. containerization). Therefore several containers can be run within a single server simultaneously (due to sharing of operating system kernel) and can cooperate with each other. Each container can only use the allocated resources and the mounted volumes which were (largely) fixed already at the container creation time and volume mounting at runtime is not possible. The most relevant containers are project-related ones from a user point of view. These are created over a specified image (a.k.a. template) and always run a notebook server.
In this application, the image always refers to Docker image:
Docker images are the basis of containers. An Image is an ordered collection of root filesystem changes and the corresponding execution parameters for use within a container runtime. An image typically contains a union of layered filesystems stacked on top of each other. An image does not have state and it never changes.
From a user point of view, these images behave like starting templates for a project, which can be either an empty template or you can clone an already available project. When selecting an empty template choose by the image name. The basic image provides your project with all the necessary packages. In case you clone a project the following project groups are defined:
- mine: those projects you created so far.
- shared: those projects other users created but you are a collaborator of.
- public: those projects that anyone can see.
The Jupyter notebook could refer to either a web-based application or a notebook document:
A web application: a browser-based tool for interactive authoring of documents which combine explanatory text, mathematics, computations and their rich media output.
Notebook documents: a representation of all content visible in the web application, including inputs and outputs of the computations, explanatory text, mathematics, images, and rich media representations of objects.
(For more information, please visit the web-site)
Here we have made a distinction between them: the web app is alluded by notebook server and the document is called simply by notebook. The system starts containers for each user and project.
The project is a central item of Kooplex Hub. It links all of the igredients which are related to project work such as a repository of documents, notebooks, (smaller) data files, discussions etc. Project owner can choose and change the scope of it (private, internal, public, it is agreement with GitLab project visibility) and can add members (from the set of existing users). There is a possibility to put certain project files under version control because their revision history can be stored in a web-based Git repository using GitLab (see more information). GitLab also provides discussion forum where project-related issues (questions, suggested developments etc.) can be discussed by project members.
Notebooks can be published in any of the following ways:
- Interactive document (Dashboard): there is an ability to run a notebook as standalone application and the author of notebook can arrange outputs (text, plots, widgets etc.) in grid- or report-like layouts (see more information). In this way, other people can enter the inputs of computations which can have an impact on the outputs (e.g. plots) but source code cannot be changed.
- Static document (HTML): this option is a simpler way to export a notebook.
Here the volume always refers to Docker volume:
A volume is a specially-designated directory within one or more containers that bypasses the Union File System. Volumes are designed to persist data, independent of the container's life cycle. Docker therefore never automatically delete volumes when you remove a container, nor will it "garbage collect" volumes that are no longer referenced by a container.
There are two types of volumes in this application:
- Module volume: it contains installed conda environments, python and other packages. When you run a notebook only one conda environment can enabled at once. However, other packages will be available.
- Storage volume: it contains data from host filesystem.
Navigation bar contains the following menus:
Only Reports and Help menus are available for unauthenticated users. The other menus check if a user is logged in or not. In the latter case, it redirects to login page. See details below.
This page is where credentials can be provided to log in which involve username and password. Furthermore, guest user can register and a (forgotten) password can be reset.
This page is where a user can access digested scientific output. See details »
This page is where a user can manage jupyter notebook projects. See details »
This page is where a user can browse project or file issues. See details »
This page is where a user can access cloud storage. See details »
This involves tutorial videos, this user documentation and contact information.