Structured data, such as XML and JSON, plays a critical role in data visualization when using DITA for manufacturing documentation. It provides the necessary foundation for organizing, storing, and transmitting data in a format that can be easily consumed by data visualization tools. Here’s how structured data contributes to data visualization in the context of DITA:

Data Organization

Structured data formats like XML and JSON enable the organization of manufacturing data. Information related to production metrics, machine performance, or quality control can be neatly structured, tagged, and categorized. DITA allows you to incorporate this structured data within topics, making it readily available for data visualization tools. For example, XML might contain information about daily production figures or JSON data could detail defect rates. This organized data serves as the basis for creating meaningful visualizations.

Data Accessibility

Structured data, when embedded within DITA topics, is easily accessible to data visualization tools. These tools can parse the structured data, extract relevant information, and present it in the form of charts, graphs, dashboards, or other visual elements. DITA ensures that the data remains up-to-date and synchronized with the manufacturing processes, allowing real-time or periodic visualization. For instance, you can create a DITA topic containing structured XML data about inventory levels, which can be used to generate graphs showing inventory trends over time.

Example:

Here’s an example of how structured data supports data visualization in DITA:

<topic id="production_metrics">
  <title>Production Metrics Visualization</title>
  <content>
    <p>Below is a snippet of structured data in JSON format:

    <code type="json">
    {
      "date": "2023-11-01",
      "productivity": 95,
      "defect_rate": 2.5
    }
    </code>
  </content>

In this example, a DITA topic titled “Production Metrics Visualization” contains a code snippet with structured data in JSON format. This structured data can be used for generating data-driven visualizations related to production metrics.