AMWA MS-04 NMOS Identity and Timing Model Specification
(c) AMWA 2019, CC Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
This AMWA Data Model Specification documents a model for identity and timing that applies to AMWA NMOS specifications associated with the identification and processing of content.
As the broadcast and media production industry adopts technologies based upon the Internet Protocol (IP) and commodity IT hardware, there is an opportunity to re-imagine how content is captured, processed and delivered. By shifting the focus away from where each ‘logical wire’ is connected and instead focusing upon the content and the processes we wish to apply to it, more innovative tools and techniques can be developed.
In order to enable this, we require mechanisms to associate identity and timing metadata with the content, and crucially to persist this data with the content as it passes through production processes. This specification defines an approach to achieve this goal, using concepts which were introduced by the JT-NM Reference Architecture.
Crucially, this approach separates the content of business value (
Flows) from the systems which process it (Devices). This ensures that as production facilities are upgraded and replace their underlying technology (including migration to new architectures such as the cloud), a consistent language can be applied to the processing of content.
This Specification defines a model for identity and timing, with guidance on how to apply it to a number of scenarios. The Specification does not cover the detail of how this identity and timing data should be implemented by common file and streaming formats. The definition of mappings to these formats is intentionally left to be defined by future specifications which use this model and its associated guidance as a foundation.
The documentation is split into three sections as follows:
The identity and timing model and in-depth description of its concepts.
Guidance on how to apply the model to media, considering common equipment and scenarios.
Background information on how the model was developed, and details of further work required.