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Field Semantics

Intro

Field Semantics is a powerful new feature in Datacake that introduces context-awareness into your IoT data. It enables the platform to understand the meaning behind each measurement field (e.g., temperature, humidity, CO₂), allowing automated generation of dashboards, KPIs, and device overviews at scale. This documentation explains the concept, how to use it, and how it enhances the overall Datacake experience.

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🚀 What Are Field Semantics?

Field Semantics are predefined labels or roles that you can assign to measurement fields on your devices. These semantics tell the Datacake platform what kind of data a field represents.

Examples of current numerical semantics:

  • Temperature

  • Humidity

  • CO₂

  • Fill Level

  • Soil Moisture

  • Air Pollution

  • Ambient Light

  • Energy Consumption

Assigning these semantics helps Datacake:

  • Automatically generate KPI dashboards

  • Visualize sensor metrics across workspaces and device groups

  • Enable context-specific views (e.g. CO₂ health analysis)

🔧 How to Use Field Semantics

Step 1: Navigate to Device Configuration

  • Go to your device in Datacake

  • Click the Configuration tab

  • Select Fields under "Product & Hardware"

Step 2: Edit Field and Assign Semantic

  • Click the three-dot menu next to a field (e.g., CO₂)

  • Choose Edit Field

  • In the Semantic dropdown, select the appropriate semantic (e.g., CO₂, Temperature)

  • Save by clicking Update Field

Access Field Settings
Set Field Semantic

📊 Automatic KPI Dashboards

Once semantics are assigned, you gain immediate access to:

  • Workspace-level metrics (min/max/avg per semantic)

  • Semantic-specific KPI views (e.g., detailed CO₂ quality breakdown)

  • Device filtering by semantic (e.g., all temperature sensors)

This means less manual configuration and quicker rollout of projects at scale.

CO2 Semantic Overview

🧩 Cross-Product Compatibility

Semantics work across different products and devices. If multiple devices have a field assigned with the same semantic (e.g., CO₂), they are automatically aggregated in dashboards and KPI cards — regardless of whether the devices belong to the same product.

This also enables global insights, such as:

  • Average temperature across an entire building

  • CO₂ levels on all floors

  • Alerting based on grouped sensor semantics

📁 Semantic-Based Device Groups (Coming Soon)

Upcoming features will allow you to:

  • Create device groups (e.g., rooms, floors)

  • Apply tags and group filters to dashboards

  • Use semantics within these groups to generate group-specific KPIs

This supports fully automated monitoring of spaces without needing custom dashboards.

💡 Summary

Field Semantics help you:

  • Add meaningful context to raw IoT data

  • Automate the creation of dashboards and KPIs

  • Scale projects faster and more reliably

  • Enable cross-product data harmonization

Start using it today by assigning semantics to your fields in the device configuration section.

Feedback is welcome – we’re continuously improving this feature!

For more help, check our Documentation or contact Support.

Stay tuned for more semantic types and automation capabilities coming soon!

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