Workspace

This page provides a screenshot-driven preview of the website serving the workspace software platform. A quick screen recording is available as well.

The user workspace in DTaaS is a personal Linux environment provided to each registered user. The https://intocps.org is used in this page as an illustration for base URL of the installation. Do replace it with the correct URL of the installation.

Visit the Workspace Installation

URL: https://intocps.org (specified in config/client.js file)

Navigation begins by visiting the website of the DTaaS instance for which the user is registered.

Redirected to Authorization Provider

URL: https://intocps.org/auth/realms/dtaas/xxxx (specified in config/.env file)

The browser redirects to the Keycloak Authorization page for the DTaaS Workspace.

The email/username and password should be entered.

The browser redirects to the Application page.

After successful authentication, redirection to the login page of the DTaaS website occurs.

URL: https://intocps.org

The DTaaS website employs an additional layer of security - the third-party authorization protocol known as OIDC. This protocol provides secure access to a DTaaS installation for users with active accounts at the selected OIDC service provider. This implementation also uses Keycloak as the OIDC provider.

After successful authorization, redirection to the Library page of the DTaaS website occurs.

URL: https://intocps.org/library/xxxx

Three icons are located on the top-right of the webpage. The hyperlink on the icon redirects to the help page, while the hyperlink on the github icon redirects to the GitHub code repository. The Account using the top-right purple 🅰️ icon provides options to change settings and logout.

Menu Items

The menu is hidden by default. Only the icons of menu items are visible. Clicking on the three horizontal bars icon in the top-left corner of the page reveals the menu.

Three menu items are available:

Library: For management of reusable library assets. Files can be uploaded, downloaded, created, and modified on this page.

Digital Twins: For management of digital twins. A Jupyter Lab page is presented from which digital twins can be executed.

Workbench: Not all digital twins can be managed within Jupyter Lab. Additional tools are available on this page.

Library Page

Five tabs are displayed, each corresponding to one type of digital twin asset. Each tab provides help text to guide users on the asset type.

Functions

The functions responsible for pre- and post-processing of: data inputs, data outputs, control outputs. The data science libraries and functions can be used to create useful function assets for the platform. In some cases, Digital Twin models require calibration prior to their use; functions written by domain experts along with right data inputs can make model calibration an achievable goal. Another use of functions is to process the sensor and actuator data of both Physical Twins and Digital Twins.

Data

The data sources and sinks available to a digital twins. Typical examples of data sources are sensor measurements from Physical Twins, and test data provided by manufacturers for calibration of models. Typical examples of data sinks are visualisation software, external users and data storage services. There exist special outputs such as events, and commands which are akin to control outputs from a Digital Twin. These control outputs usually go to Physical Twins, but they can also go to another Digital Twin.

Models

The model assets are used to describe different aspects of Physical Twins and their environment, at different levels of abstraction. Therefore, it is possible to have multiple models for the same Physical Twin. For example, a flexible robot used in a car production plant may have structural model(s) which will be useful in tracking the wear and tear of parts. The same robot can have a behavioural model(s) describing the safety guarantees provided by the robot manufacturer. The same robot can also have a functional model(s) describing the part manufacturing capabilities of the robot.

Tools

The software tool assets are software used to create, evaluate and analyse models. These tools are executed on top of a computing platforms, i.e., an operating system, or virtual machines like Java virtual machine, or inside docker containers. The tools tend to be platform specific, making them less reusable than models. A tool can be packaged to run on a local or distributed virtual machine environments thus allowing selection of most suitable execution environment for a Digital Twin. Most models require tools to evaluate them in the context of data inputs. There exist cases where executable packages are run as binaries in a computing environment. Each of these packages are a pre-packaged combination of models and tools put together to create a ready to use Digital Twins.

Digital Twins

These are ready to use digital twins created by one or more users. These digital twins can be reconfigured later for specific use cases.

Two sub-tabs exist: private and common. Library assets in the private category are visible only to the logged-in user, while library assets in the common category are available to all users.

Further explanation on the placement of reusable assets within each type and the underlying directory structure on the server is available on the assets page.

Note

Assets (files) can be uploaded using the upload button.

The file manager is based on Jupyter Notebook, and all tasks available in Jupyter Notebook can be performed here.

Digital Twins Page

URL: https://intocps.org/digitaltwins

The digital twins page contains three tabs, and the central pane opens Jupyter Lab. The three tabs provide helpful instructions on suggested tasks for the Create - Execute - Analyze lifecycle phases of a digital twin. More explanation is available on the lifecycle phases of digital twin.

Tip

Create digital twins from tools provided within user workspaces. Each digital twin will have one directory. It is suggested that user provide one bash shell script to run their digital twin. Users can create the required scripts and other files from tools provided in Workbench page.

??? tip Execute Digital twins are executed from within user workspaces. The given bash script gets executed from digital twin directory. Terminal-based digital twins can be executed from VSCode and graphical digital twins can be executed from VNC GUI. The results of execution can be placed in the data directory.

Tip

The analysis of digital twins requires running of digital twin script from user workspace. The execution results placed within data directory are processed by analysis scripts and results are placed back in the data directory. These scripts can either be executed from VSCode and graphical results or can be executed from VNC GUI.

The reusable assets (files) displayed in the file manager are also available in Jupyter Lab. Additionally, a git plugin is installed in Jupyter Lab that enables linking files with external git repositories.

Workbench

URL: https://intocps.org/workbench

The Workbench page provides links to four integrated tools:

Tool	Description
Desktop	XFCE-based Linux desktop environment in the browser
VS Code	Browser-based VS Code editor (code-server)
Jupyter Lab	Interactive notebook environment
Jupyter Notebook	Classic Jupyter interface

Screenshots of the pages opened by clicking on first four icons are shown:

The hyperlinks open in new browser tabs.

VS Code Workspace

The VS Code interface provides:

• File explorer for navigating the workspace
• Integrated terminal for running commands
• Extensions for Python, Markdown, and other languages

XFCE Desktop

The XFCE desktop provides a full graphical Linux environment accessible from the browser. This is useful for running GUI-based tools that cannot be used from a terminal alone.

Workspace File System

Each user's workspace container mounts two directories:

/workspace/           # Private user files (read-write)
├── data/
├── digital_twins/
├── functions/
├── models/
└── tools/

/workspace/common/    # Shared library assets
├── data/
├── digital_twins/
├── functions/
├── models/
└── tools/

Files in /workspace/ are private to each user. Files in /workspace/common/ are shared across all users. Administrators can optionally mount /workspace/common as read-only via the compose configuration.

Installing Software

Users can install additional software inside their workspace (XFCE Desktop / Jupyter Lab / VSCode):

sudo apt-get install <package>
pip install <package>

Installed software is private to each user's workspace and persists across sessions.

Running Digital Twins

Digital twins stored in /workspace/digital_twins/ can be executed by running their lifecycle scripts directly in the terminal:

cd /workspace/digital_twins/<dt-name>
lifecycle/create
lifecycle/execute

Summary

The DTaaS workspace gives each user a private, persistent Linux environment with browser-based access to a desktop, terminal, and development tools. Users can install software, run digital twins, and develop new DT assets within their workspace.