Insight · Digital Twins

Before calling a model a digital twin, ask how it stays connected to reality

A detailed digital model may be useful without representing current conditions.

By TheTechGlow Editorial Desk · Published November 3, 2026 · Updated November 3, 2026 · 1 min read
AI-generated editorial illustration of digital twins

AI-generated editorial illustration.

A detailed digital model may be useful without representing current conditions. When evaluating a proposed digital twin, ask what physical system it represents, which information updates it and which decision it supports.

A practical example

Consider a model of a building’s ventilation equipment. A team should know whether operating readings are live, periodically imported or manually entered. If a component is replaced, someone needs to update its identity and the relationship to historical records.

What to check

  • Describe the physical asset, model boundaries and information sources.
  • Record update frequency and show when a value is stale or unavailable.
  • Test whether a proposed prediction is checked against observed behaviour.

The trade-off

Fidelity should match the decision. A simpler model with maintained records may be more useful than a visually impressive representation whose assumptions and update process are unclear.

Research context

NIST’s digital-twin work explores the concepts and technical challenges of connecting digital representations with physical systems. It provides a research perspective, not a certification of commercial product descriptions.

Read the original reference material. The practical examples and evaluation questions above are TheTechGlow’s editorial application of the topic, not reported results from a product test.

Explore Digital Twins for topic coverage, or continue to Property and Real Estate Technology for the wider sector.

References and further reading

  1. nist.govhttps://www.nist.gov/digital-twins

Tags: digital-twins, technology

TheTechGlow Editorial Desk

Research-based technology explanations and practical evaluation questions. Sector articles use AI-assisted research and drafting; factual sources are linked for readers.

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