What Does Dataverse Mean?

Applied Tech Review | Thursday, April 28, 2022

Dataverse lets you securely store and manage data used by business applications.

FREMONT, CA: As digital twins progress in the metaverse, the "dataverse" will evolve to support the complexity and scale of these new use cases. The dataverse in question is not the open-source project or the rebranded Microsoft Common Data Services but the data infrastructure required to support the next generation of digital twin use cases.

Digital twins are ideal for graph-based relationship management, best supported by graph databases. Azure Digital Twin, for example, is based on a graph model, and we will see more of this pattern emerge in 2022. A graph-based model's underlying benefit is that it codifies the network impact of digital twins. It subscribes to Metcalfe's law that states that "the value of a network is proportional to the square of the number of connected users." The value and benefit from digital twins will increase exponentially as more instances, and a TwinGraph connects use cases

Traditional hierarchical asset structures and frameworks will be replaced by graph-based solutions such as Azure Digital Twin, modeled with the Digital Twin definition language (DTDL), which will describe the relationships. One example is the work we're doing at XMPro to convert the ISO 14224 asset model to DTDL and Azure Digital Twins.

We will also see the rise of cloud historians to support use cases in which data from Operational Technology (OT) is combined with data from Information Technology (IT), thereby removing the siloed traditional historian structure and boundaries. This will allow business technologists, such as engineers with data science skills, to use Digital Twins to solve problems that traditional historians and analytics separation cannot.

In 2022, digital twins will face increased security threats. The work of organizations such as the Industry IoT Consortium (IIC) with their Trustworthiness framework is rapidly maturing IoT security.

The complexity of managing many models or prototypes that often house an organization's intellectual property adds to the complexity of Digital Twins. Competitive intelligence attacks will be launched against them. And having access to these models' digital twin instances will provide a fully operational competitive intelligence scenario that can be exploited in various ways. For example, it can spy on a competitor and, in extreme cases, in physical and cyber-attacks.

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