Digital Copies, Digital Twins & Digital Simulations: What’s the Difference, and Why It Matters
The term digital twin is appearing everywhere, but as it’s gained popularity, it’s also started to lose precision. People often use the term “digital twin” as a catch-all for anything digital, when what they’re really talking about might be a digital copy or a simulation.
These terms aren't interchangeable, and mixing them up can create confusion, especially when you're aiming to build something that genuinely bridges the digital and physical worlds. A static digital copy, a predictive simulation, and a responsive digital twin all serve different purposes, have different behaviors, and understanding the difference isn’t just a technical detail – it’s key to setting the right expectations, choosing the right tools, and building something that solves the problems you need it to.
In this article, I’ll break it down simply: what each one actually is, where they’re useful, and why getting this right matters as we work toward a more connected, spatial web.
What’s a digital copy?
A digital copy is essentially a static replica – a one-off snapshot of a physical object or environment. Once created, it doesn’t update or interact with the real world. It’s perfect for things like showcasing a space, documenting how something looked at a certain point in time, or creating a visual for a pitch.
Think of it like the shopping mall directory map you see when you walk in the door: useful, but only accurate at the time it was printed. If shops move, close, or open, it quickly becomes out of date unless manually updated.
Or, imagine you’re creating a virtual tour of a museum. You’d take 3D scans of the exhibits and put them together into a polished virtual space. That virtual tour is a digital copy – it reflects the exhibits as they were, but unless you update the tour, it won’t change as new exhibits are added or old ones are moved around.
When you don’t need real-time data or live interaction, digital copies are very useful. They’re easier to produce, less complex, and serve a purpose in everything from marketing materials to archival documentation.
What’s a digital simulation?
A digital simulation is all about behavior. Instead of just showing what something looks like, it also shows how it acts – under different conditions, over time, or in response to change. It’s not necessarily linked to the real world, but it helps you understand how something might perform.
Imagine you’re designing a new lighting system for a building. A digital copy could show where the fixtures are placed, but a simulation would let you test brightness levels, energy usage, and how natural light changes throughout the day. It’s like running a dress rehearsal for your physical system or environment, so you can spot issues, test ideas, and make improvements.
Or think about traffic planning. You could simulate how cars would flow through a new intersection design, try out different light timings, and even model rush hour conditions, all without ever pouring concrete.
Digital simulations are powerful tools for prototyping, testing, and decision-making. While they don’t always need real-world data, they can become even more valuable when connected to live inputs. And that’s where they start to blend into the world of digital twins.
What’s a digital twin?
A digital twin is a living, breathing version of whatever it’s mirroring. It’s always on, always updating, and always in sync with the real world.
Whether it's a building, a machine, a city, or even an event, a digital twin monitors real-time data from sensors, IoT devices, and other inputs to reflect the state of its real-world counterpart.
With this data, you can not only allow digital and physical users to be truly copresent with one another, but also optimize performance, predict maintenance and make other improvements, whether it's reducing energy use in a building, managing crowd flow at a concert, improving production efficiency in a factory, or fine-tuning the operation of a machine. It’s all about making things work smarter, more efficiently, and be more accessible remotely in real-time.
Digital twins can be closed or open
Not all digital twins are created equal – and one of the biggest differences is whether they’re open or closed.
A closed digital twin locks you into a single ecosystem. It might work well – as long as everything else you use comes from the same provider. But the moment you need to connect to another system, tool, or platform you’re stuck doing extra work to make things fit, often with limited flexibility or expensive custom solutions.
On the other hand, an open digital twin is designed to integrate. It can exchange data across platforms, work with your existing tools, and evolve as your systems do – without forcing you into a specific stack.
At Magnopus, we build interoperable digital twins that are open by default. Our tech is built from the ground up to integrate with all systems, with minimal effort. No walled gardens, just open, platform agnostic technology that will work with however you work best. This means teams can work with the tools they already use, avoid duplication, and adapt systems over time as needs evolve.
| Feature | Digital Copy | Digital Simulation | Closed Digital Twin | Open Digital Twin |
|---|---|---|---|---|
| Real-time data | ❌No | ❌No | ✅Yes | ✅Yes |
| Feedback/simulation | ❌None | ⚠️Limited, not responsive to real-world changes | ✅Local | ✅Cross-system |
| Connects to the physical world | ❌No | ⚠️ Limited, not connected in real time. | ✅Yes (own system only) | ✅Yes (own and external systems) |
| Data standards/protocols | ❌Not required | ⚠️Varies, some are bespoke, others standard compliant | ❌Often proprietary | ✅Standards-based (e.g., APIs, ontologies) |
| System communication | ❌None | ❌None | ❌Isolated | ✅Communicates with other systems |
| Scalability in ecosystems | ❌No | ⚠️Limited | ⚠️Limited | ✅Designed for networks |
Why does this matter?
Choosing the right digital approach can have a direct impact on business efficiency, resilience, and growth. The table below compares a digital copy, a simulation, a closed digital twin, and an open digital twin. Each supports goals in different ways, from basic data access to system-wide optimization and collaboration.
| Reason | Digital Copy | Digital Simulation | Closed Digital Twin | Open Digital Twin |
|---|---|---|---|---|
| Efficiency & Optimization | Static view of processes. | Simulates system performance to identify potential inefficiencies, but not based on live data. | Real-time monitoring to spot inefficiencies and improve operations. | Optimization across connected systems and networks. |
| Design & Development | Reference-only material. | Provides a virtual environment for testing ideas, concepts, or products before implementation. | Live simulation and prototyping environment for testing and validation. | Collaborative design and validation across teams or organizations. |
| Real-time Decision-making | Outdated or manual data. | No real-time input. Decisions are based on pre-defined models or historic data. | Instant insights from live data inputs. | Coordinated decisions based on shared, system-wide data. |
| Predictive Maintenance | No monitoring capability. | Uses theoretical or historical data, but lacks live monitoring. | Detects issues before they happen. | Shares predictive insights across systems for proactive coordination. |
| Continuous Improvement | No feedback loop. | Can test improvements in a controlled environment, but doesn’t adapt automatically over time. | Constant data flow enables performance tuning over time. | Cross-domain feedback enables system-wide refinement. |
| Scenario Planning | Manual, limited modeling. | Simulates 'what-if' conditions to test strategies . | Simulates 'what-if' conditions with real-world data to test strategies accurately . | Simulates impact across entire ecosystems or supply chains. |
| Cross-System Collaboration | Isolated use, no system integration. | Operates in isolation. Doesn’t inherently share or receive data across systems. | Limited to local systems or vendors. | Connects and integrates data across diverse platforms and organizations. |
Where our technology fits in
Our OKO platform and Connected Spaces Platform (CSP) provide the underlying infrastructure to support persistent, interoperable real-time digital twins that are accurate, interactive, collaborative, and scalable.
Here are a few ways this could play out:
Accelerating collaborative previs for production
For live events and location-based entertainment, producers can use digital twins of real-world spaces to plan layouts, test different setups, and make collaborative decisions in real-time. This kind of previsualization makes productions faster and more efficient, without sacrificing creativity. Read more about how we used OKO to take over Times Square for a cross-reality music event.
Simulating & enhancing the customer journey
By simulating customer interactions, a digital twin allows designers to visualize how customers navigate and engage with a space, and respond to stimuli. This helps identify pain points, optimize layout, and personalize experiences. A digital twin also enables testing and predicting outcomes before making changes in the physical space, ensuring a seamless and engaging customer journey.
Giving digital reach to the physical
By creating a real-time digital twin of a venue, gallery, or installation, you can expand its reach far beyond its physical location. Remote users can interact with the space just as on-site visitors do, thanks to live integrations with spatial data, video, audio, and environmental feedback. It’s a new way of thinking about access and connection, especially for events with global audiences. We created the world’s largest digital twin for the World Expo in Dubai.
Where to start
This table breaks down a “good, better, best” progression from a basic closed digital twin to a fully interoperable one, giving a rough sense of the time, investment, and complexity involved.
| Description | Timeframe to Deploy | Budget Level | |
|---|---|---|---|
| Good | User-generated digital twin using RoomPlan scanning within OKO, anchored via GPS to a physical location. Generates a whitebox environment for quick iteration and planning. | Hours | 💰 Low |
| Better | Enhanced solution capturing real-world data, such as through photogrammetry or Gaussian splats. Enables high-accuracy, near-real-time modeling, and updates. The key focus is capturing the physical world in greater detail with rapid deployment. | Days to weeks | 💰💰 Medium |
| Best | Fully interoperable digital twin solution with deep IoT and external API integrations, allowing for dynamic updates, predictive analytics, and cross-platform communication. The key focus is IoT/real-time integration and cross-platform interoperability. | Weeks to months | 💰💰💰High |
To recap…
A digital copy is like a snapshot; useful for storing or sharing information, like a 3D model or a scanned document. It’s simple and static.
A digital simulation is a theoretical model built to explore how a system or process might behave under certain conditions. A simulation isn’t connected to a physical thing so it’s ideal for exploring what-if scenarios without real-world consequences.
While digital twins can run simulations too, they also incorporate live data and two-way interaction, making them broader in scope and more dynamic in application.
But when systems need to talk to each other — across departments, factories, or even companies — that’s where the open digital twin comes in. It connects beyond its own boundaries, enabling smarter decisions across entire networks, whether you're managing a supply chain, optimizing energy across a smart city, or integrating systems from multiple vendors.
Choosing the right one isn’t just about technology. It’s about what your business needs to see, do, and achieve.
