The promise and pitfalls of the metaverse for science

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Anticipating various potential opportunities for science, here we build on existing early-stage applications to assess how the metaverse could help address several current issues of concern to the research firm.


Academic institutions and meetings are geographically dispersed across the globe, creating an accessibility barrier for researchers who are not co-located or have mobility issues. Additionally, hectic schedules, prohibitive travel costs, travel restrictions, lack of access to childcare, and increasing greenhouse gas emissions make access difficult for many researchers. While video conferencing and online communication platforms are extremely helpful, they do not offer the advantages of a face-to-face meeting6. Screens limit scientists’ attention and focus by filtering out other stimuli that are essential for generating new ideas7. Conducting meetings via video reduces the possibility of random discussions in the hallways and impairs social contact and the sense of social presence. The 3D nature of the metaverse could alleviate some of these issues and further facilitate collaboration and communication. Additionally, recorded 3D meetings in the Metaverse can faithfully recreate the space, participants and their real-time reactions, expanding access around the world.

The metaverse can also enable personalized, immersive 3D environments for simulation and connection to remote labs. Scientists could visit them remotely, share them with other research groups, and tweak their operations virtually before making physical changes. This allows distant scientists to come together to collaborate and work with the same instruments and facilities. For example, scientists at the UCL School of Pharmacy have developed a digital replica of their laboratory that can be visited via virtual reality2.

In both meeting and lab settings, artificial intelligence (AI) models could embody or become part of the environment as virtual agents in the metaverse, all with the effect of enhancing collaborative scientific output and human-AI collaboration. For example, large language models can be implemented natively as virtual assistants to gather information, make recommendations, or translate conversations to overcome language barriers.


The reproducibility of experimental results is a crucial factor for the credibility of science, which often depends on precise recording. With the advent of the metaverse, instead of recording with handwritten or electronic lab notebooks, scientists could combine the use of cameras and sensors to record and then reproduce lab conditions and procedures in immersive 3D simulations. Researchers can use headsets to record what they are doing, creating a 3D first-person perspective. The resulting records – including the researchers, devices, rooms, materials, and how the process unfolds – could then be uploaded to the metaverse. Unlike video recordings, the metaverse can integrate the states of materials, objects, and devices manipulated by researchers, and automatically include data streams from instruments in the labs. Such immersive recordings would allow anyone to re-enact what the scientists did. When questions arise, collaborators or reviewers can participate in the experiment in the metaverse, either synchronously or asynchronously, along with the original researchers. Additionally, implementing blockchain technologies for these records could make them immutable and trustworthy8th – Attributes that are particularly important for expensive experiments or valuable devices and samples. Due to cost and logistics reasons, such solutions could not be widely implemented, but would be useful for high-impact studies where replication might be challenging for a variety of reasons.

training and learning

One of the biggest challenges in maintaining a research program is adequately training new group members. The details of scientific processes can vary significantly between groups, and the long-established approach of training through one-on-one face-to-face interactions is time-consuming, dependent on shared location, prone to disruption due to staff turnover, and often limits the ability to share techniques between groups.

The metaverse has the potential to improve the process of such knowledge transfer. Research teams can use virtual reality technologies to design experiences and share them at scale. Of course, repeating and experiencing previous explorers and being fully immersed in the metaverse—perhaps in the presence of a remote trainer—would help trainees to replicate and learn laboratory procedures. Such training conducted on the metaverse could also reduce research disparities by providing access to institutions around the world. An example we can consider is this virtual lab training developed by the Centers for Disease Control and Prevention. Using a head-mounted display, learners are immersed in a virtual lab where they must identify key parts of the lab, demonstrate how instruments remain functional, use safe work practices, and conduct emergency response. An added benefit would be that, unlike traditional training, virtual simulation would allow learners to make costly mistakes with no real-world consequences.

New experimental environments

A common challenge for researchers of all disciplines is the visualization of data and experimental conditions, which are often essential for conducting research and communicating results. Although 3D objects can be visualized on screens, they are limited by the dimensions of the screen, which do not fully reflect the materiality, depth, or size of objects. In contrast, virtual reality technology has enabled network scientists to design the VRNetzer platform, for example4 to explore large-scale networks in 3D. Similarly, modelers have interacted with molecular structures using Microsoft HoloLenses9and a medical team has visualized the brains of individuals as such holograms. A networked metaverse implementation of this type of technology would allow scientists from multiple locations to jointly examine data, change the parameters of that data, run simulations, and create complex slices through data in multiple dimensions.

Visualization in the metaverse can go beyond analyzing data and enable the creation of research programs that would otherwise be difficult to realize. Freed from the limitations of experimental conditions in laboratories and observation rooms, the metaverse could allow behavioral scientists to design virtual and immersive environments that are prohibitively expensive to develop in real laboratories, violate physical laws, or present new dimensions of complexity. For example, a research team developed FreemoVR3, a virtual reality platform for conducting animal experiments. Using this platform, animals move freely in the experimental room and the walls and floors display computer projections that change depending on the animals’ behavior. This allows scientists to study the animals’ brain activity and responses. A similar structure for humans could offer behavioral researchers a wide range of interactive experimentation options. In addition, the metaverse can also help scientists delve into remote, dangerous, or extinct environments, such as the landscape of Mars. From the preserved images Curiosity Rover already allows scientists to explore the terrain of Mars, helping plan rover trips, exploring the planet and running simulations with astronauts. Using the metaverse could also allow explorers from around the world to synchronously occupy and explore the virtual Martian landscape10. This technology can be extended to a wide range of inaccessible environments – including potential exploration of microscopic phenomena in the style of the 1966 sci-fi classic The Fantastic Voyage.

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