Contextualize Overview
Contextualize is the data intelligence layer of the HiveMQ Platform. In Contextualize, you build and manage your Unified Namespace (UNS), a shared model that gives structure and meaning to your MQTT data. Use Contextualize to discover data streams, build your Unified Namespace, and compute values from live data.
Open Contextualize from the top navigation bar.
What Is a Unified Namespace?
A Unified Namespace is a single, standardized model for how data flows across devices, brokers, and AI agents. The namespace gives every data consumer (dashboards, analytics, and AI agents) the same view of your data, so they all read data the same way.
What You Can Do in Contextualize
Contextualize provides four capabilities:
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Build your namespace: model your operation as a hierarchy of sites, areas, lines, assets, and signals, based on the ISA-95 standard.
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Discover data streams: Detect the MQTT traffic that is currently flowing on your connected brokers and approve topics into the namespace.
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Create reusable data models: Define a structure once, version it, and apply it anywhere in the namespace.
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Compute values from your data: Derive new values, such as unit conversions and key performance indicators (KPIs), directly on your brokers.
Two Ways to Build a Namespace
You can build your namespace top-down, bottom-up, or with both approaches combined:
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Top-down: Design the structure first, then align your data to the model. See Build Your Namespace. The top-down approach suits new projects and designs that do not depend on connected infrastructure.
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Bottom-up: Detect active data flows on your brokers, then approve them into the namespace. See Discover Data Streams. The bottom-up approach suits projects with infrastructure that already produces valuable data.
To combine both approaches, start with discovery to populate the namespace quickly. Then refine the model top-down for governance and long-term manageability.
Why Contextualize First?
When you standardize topic structures and schemas in Contextualize, all downstream consumers work with trustworthy, well-described data. This includes analytics in Analyze and AI agents in Act. Standardized data replaces raw, inconsistently shaped streams.
Contextualize builds on the brokers you manage in Connect. The brokers carry the raw MQTT traffic. The Unified Namespace gives the traffic a shared structure.