Applying Standards to Information Centric Operations
6.1 SEMANTICS IN STANDARDS
A necessary feature of information-centric architectures is the provision of common meaning . In industrial digital twins this may use a semantically-enabled systems modeling language like SysML V2 26 with its KerML 27 core semantics . For less tangible things such as financial instruments or contracts W3C based ontology standards have been used to define a formal ontology .
“ Semantics ” can refer to model semantics or real-world or domain semantics . Advances in KerML and SysML V2 bring these languages closer to being able to reflect real-world meanings of things represented in the models . These take a different approach to conventional ontology languages such as OWL .
Industrial digital twins may make use of system design models in SysML for data-centric working . The examples from ExxonMobil and Nextspace show the semantic unification of 2D and 3D assets and reality capture point clouds . The Nextspace example shows that it is possible to find a way to unify these different dimensions under a common ontology . Standardizing these approaches would be a benefit to the industry .
An ontology that is predicated on real things can also include among those real things , that which is data , thereby incorporating the relationships between the data and the things it is about . The ability to model this distinction is particularly relevant in the case of industrial digital twins , as it enables the enterprise to manage data concerns such as measurement tolerances , instrument calibration history and the like .
For ontologies that represent the real world , there is a need to standardize the ontological commitment . There is an ISO standard , ISO 21838 , in which Part 1 [ 12 ] sets out the definition of what it is to be a Top Level Ontology . In time there may be a need to further characterize the details of ontological commitments . This includes for example whether it is a Realist ontology , whether it reflects a 3D or 4D view of the world , and other similar considerations .
Every ontology used across the enterprise or project should then be able to declare these features in an unambiguous and standardized way .
6.2 METAVERSE AND DIGITAL TWINS STANDARDS
Standards cover more kinds of subject matter than data formats or modeling languages . Anything that can be stated in normative terms (“ you shall do this ”) can be proposed and formally adopted as a standard . Standards may define formats , business processes , architectures , interfaces and many other concerns . For data-centric digital twins , these may range from being able to formally state what kind of model is used and how this represents reality , through to standardizing the way data capture , storage , distribution and consumption are done .
26
Systems Modeling Language ( SysML ) V2 ( Beta ). Available : https :// www . omg . org / spec / SysML
27
Kernal Modeling Language ( KerML ) ( Beta ). Available : https :// www . omg . org / spec / KerML Journal of Innovation 25