Uploaded January 2026 | Updated September 2026, 1 week ago
The Data Model Interpreter repo offers tools to convert the standard Matter data model—a ZAP file generated using the [ZAP tool](github.com/project-chip/zap)—into API calls needed to initialize the data model, encodes them to protobuf messages and stores it in a space-efficient format on the flash.
By design, this allows the application and the data model to be decoupled and stored independently. The repo also includes an IDF component that can read this serialized format and create the data model at runtime. However, the same format is usable across Matter implementations like Matter.js, rs-matter, Matter (CircuitPython) or Arduino Matter, eliminating the need for code generators to be developed for these languages.
The talk will provide an introduction to data models of IoT devices, how Matter approaches the data modeling problem, and how the Data Model Interpreter tools and components work. It will also cover the potential use cases.
Speakers: Dhaval Gujar and Amit Sheth
The Data Model Interpreter repo offers tools to convert the standard Matter data model—a ZAP file generated using the [ZAP tool](github.com/project-chip/zap)—into API calls needed to initialize the data model, encodes them to protobuf messages and stores it in a space-efficient format on the flash.
By design, this allows the application and the data model to be decoupled and stored independently. The repo also includes an IDF component that can read this serialized format and create the data model at runtime. However, the same format is usable across Matter implementations like Matter.js, rs-matter, Matter (CircuitPython) or Arduino Matter, eliminating the need for code generators to be developed for these languages.
The talk will provide an introduction to data models of IoT devices, how Matter approaches the data modeling problem, and how the Data Model Interpreter tools and components work. It will also cover the potential use cases.
Speakers: Dhaval Gujar and Amit Sheth
