Digital Twin Architecture and Standards
Agreement) policies by which sharing is
allowed, protecting intellectual property and
sensitive information. Synchronized replicas
in adjacent tiers are guarded by the same
controls.
C8. Publish and subscribe notification of
CRUD transactions. Digital twins enable
clusters of processing activity in a tier by
generating
events
associated
with
repository access. The events are not
intended to directly share content. Instead,
applications use the notifications to drive
key-value pair access, like the MVC pattern.
C6. Data ingest configuration for each
column store. The Industrial IoT life blood is
collections of data, including historical
records that can be replayed as streams.
Digital twins are populated by creating key-
value pairs, and data source ingest is a
ubiquitous scenario.
C9. Filtered synchronization between tiers.
Industrial IoT data is created at the network
edge yet delivers the best business value
when
aggregated
in
the
cloud.
Communications between the edge and
cloud may not be reliable or intentionally air-
gapped for security protection. Selected
column store synchronization uses the
network bandwidth for transferring data in
bulk and reduces the cybersecurity attack
surface of a tier.
C7. CRUD data exchange with cascading
side effects based on role. Writing and
reading key-value pairs in digital twin
column stores is the fundamental
application programming model for
persistence and analysis. These fine-grained
transactions within a tier can be extended
with programmatic callbacks configured by
the repository owner, providing maximum
control over the content.
C1
C2
C3
Table 3 shows the cross references between
the six proposed digital twin interactions and
the nine evaluation criteria.
C4
C5
C6
C7
Interoperability
Information Model
Data Exchange
Administration
Synchronization
Publish / Subscribe
Table 3: Evaluation Criteria Applied to Digital Twin Interactions
IIC Journal of Innovation
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C9