AAS Query Language

AAS Query Language#

In industrial Digital Twin environments, large numbers of Asset Administration Shells (AAS), Submodels, and Concept Descriptions are managed across distributed systems. While standard AAS APIs provide structured access to individual elements, advanced use cases require powerful, flexible, and efficient search capabilities across the entire AAS landscape.

The AAS Query Language addresses this need by providing a unified, expressive query mechanism to search for AAS, Submodels, Concept Descriptions, and their descriptors. It enables users to perform complex filtering, logical operations, and semantic-based searches across all registered Digital Twin data.

Internally, the BaSyx query functionality is backed by Elasticsearch, providing scalability, high performance, and fuzzy search capabilities while exposing a domain-specific query interface tailored to the AAS meta-model.

Note

A fully working example of the AAS Query Language is available in the official BaSyx examples on GitHub.

Motivation and Use Case#

As Digital Twin environments grow, organizations quickly face challenges such as:

  • Finding specific assets among thousands of AAS

  • Searching Submodels by semantic identifiers or versions

  • Locating assets by endpoints, asset kind, or metadata

  • Filtering Concept Descriptions by language or reference relations

  • Querying registries for deployment, discovery, and orchestration

The AAS Query Language enables all of these scenarios through a single, consistent query interface that works across multiple BaSyx repositories and registries.

Example Setup Overview#

The example provides a preconfigured BaSyx environment with:

  • Multiple Asset Administration Shells

  • Several Submodels per AAS

  • Concept Descriptions

  • Registries for AAS and Submodels

  • An integrated Elasticsearch backend

All components are deployed as Docker containers to ensure easy setup and reproducibility.

Running the AAS Query Language Example#

To start the example environment:

  1. Open a terminal in the example folder

  2. Start all BaSyx containers:

    docker-compose up -d

Note

Docker must be installed on your system in order to run this example.

Exploring the Query Functionality via Web UI#

After starting the containers, you can interact with the query system using the BaSyx AAS Web UI:

  • Open the BaSyx Web UI

  • Navigate to the AAS Query Language Module

  • Select the target component (Repository or Registry)

  • Enter your query in the text area

  • Execute the query and inspect the result set

Inspecting Elasticsearch via Kibana#

The BaSyx query infrastructure uses Elasticsearch as its search backend. To explore the indexed data directly, you can access Kibana:

  • URL: http://localhost:5601

  • Username: elastic

  • Password: vtzJFt1b

Kibana allows you to:

  • Inspect AAS, Submodel, and Concept Description indices

  • Perform raw Elasticsearch queries

  • Visualize indexed Digital Twin data

  • Debug indexing and query behavior

Query Endpoints Overview#

Component

Endpoint

AAS Repository

/query/shells

Submodel Repository

/query/submodels

Concept Description Repository

/query/concept-descriptions

AAS Registry

/query/shell-descriptors

Submodel Registry

/query/submodel-descriptors

Getting Started#

  1. Start the BaSyx Docker environment

  2. Explore the Web UI query module

  3. Inspect Elasticsearch via Kibana

  4. Execute the example queries

  5. Integrate the query endpoints into your own applications

Additional Resources#

For more information about AAS Query Language: