This document defines digital twins and related concepts. It discusses that a digital twin is a virtual representation of a physical object that continuously updates based on real-time data. The document outlines the origin and components of digital twins, provides examples of their use, and discusses related technologies like JSON-LD, RDF, and DTDL that are used to define digital twin models and exchange data.
2. Definition
A digital twin is a virtual
representation that serves as the
real-time digital counterpart of a
physical object or process.
It’s a result of continual
improvement in the creation of
product design and engineering
activities.
3. Origin
The concept and model of the digital
twin was publicly introduced in 2002
by Grieves.
The first practical definition of digital
twin originated from NASA in an
attempt to improve physical model
simulation of spacecraft in 2010.
4. DMST
A digital twin consits of the following
three parts:
1. Digital model.
2. Digital shadow.
3. Digital twin.
5. Example
• 3D modeling can be used to view the
status of physical object and protect
from sudden incidents.
• Sensors collect data from physical
objects forward them to digital twin
to update the digital copy as well in
real-time.
• Virtual copy will always be up-to-date
and accurate with physical objects.
6. Use case
Digital twins are useful to almost all
industrial places:
1. Airlines industry.
2. Healthcare industry.
3. Automotive industry.
4. Construction industry.
5. Manufacturing industry.
7. Available tools
Companies like Microsoft
offer tools and services to
create Digital Twin virtually
of physical environments.
9. JSON-LD
JSON stands for JavaScript Object Notation;
is an open standard file format that uses
human-readable text to store and transmit
data objects.
• It consists of key-value pairs or serialise
values.
• Its language independent thus, use for
various types of projects. i.e., headless
API, HTTP requests, and even on Digital
Twins.
10. DTDL
DTDL stands for Digital Twin Definition Language that is a
standard for Digital Twins.
• DTDL is based on JSON-LD and is programming language
independent.
• DTDL and JSON-LD helps defining model in human-readable
format.
• Microsoft Azure has full support for DTDL in their Digital Twin
service.
11. Example
A basic model written as a DTDL
interface using JSON.
• This model describes a Home, with
one property for an ID.
• The Home model also defines a
relationship to a Floor model, which
can be used to indicate that a Home
twin is connected to certain Floor
twins.
12. RDF
RDF stands for Resource Description
Framework; is a World Wide Web
Consortium (W3C) standard originally
designed as a data model for metadata.
• It is used as a general method for
description and exchange of graph
data.
• Digital Twin model requires DTDL and
not RDF thus, tools are available to
convert from RDF to DTDL format.
13. VOCABULARIES
• Classes
• Properties
Vocabulary is used as a foundation
for RDF Schema, where it is
extended.
SERIALIZATION FORMATS
• Turtle
• N-Triples
• N-Quads
• JSON-LD
• N3
• RDF/XML
• RDF/JSON
Example
14. RDF
• r d f : X M L L i t e r a l – t h e c l a s s o f X M L l i t e r a l v a l u e s
• r d f : P r o p e r t y – t h e c l a s s o f p r o p e r t i e s
• r d f : S t a t e m e n t – t h e c l a s s o f R D F s t a t e m e n t s
• r d f : A l t , r d f : B a g , r d f : S e q – c o n t a i n e r s o f
a l t e r n a t i v e s , u n o r d e r e d c o n t a i n e r s , a n d o r d e r e d
c o n t a i n e r s ( r d f s : C o n t a i n e r i s a s u p e r - c l a s s o f
t h e t h r e e )
• r d f : L i s t – t h e c l a s s o f R D F L i s t s
• r d f : n i l – a n i n s t a n c e o f r d f : L i s t r e p r e s e n t i n g t h e
e m p t y l i s t
RDFS
• rdfs:Reso ur c e – the class resou r ce ,
everythin g
• rdfs:Lit er al – the class of literal values,
e.g. string s and integer s
• rdfs:Class – the class of classe s
• rdfs:Dataty pe – the class of RDF dataty pe s
• rdfs:Conta i ner – the class of RDF contain e r s
• rdfs:Conta i ner M em b e rs hi p P r op e r ty – the
class of containe r member sh i p
prope rtie s , rdf:_1, rdf:_2, ..., all of which
are sub- pr o pe r ti e s of rdfs:m em be r
Classes
15. RDF
• r d f : t y p e – a n i n s t a n c e o f r d f : P r o p e r t y u s e d t o s t a t e t h a t
a r e s o u r c e i s a n i n s t a n c e o f a c l a s s
• r d f : f i r s t – t h e f i r s t i t e m i n t h e s u b j e c t R D F l i s t
• r d f : r e s t – t h e r e s t o f t h e s u b j e c t R D F l i s t a f t e r r d f : f i r s t
• r d f : v a l u e – i d i o m a t i c p r o p e r t y u s e d f o r s t r u c t u r e d v a l u e s
• r d f : s u b j e c t – t h e s u b j e c t o f t h e R D F s t a t e m e n t
• r d f : p r e d i c a t e – t h e p r e d i c a t e o f t h e R D F s t a t e m e n t
• r d f : o b j e c t – t h e o b j e c t o f t h e R D F s t a t e m e n t
r d f : S t a t e m e n t , r d f : s u b j e c t , r d f : p r e d i c a t e , r d f : o b j e c t a r e
u s e d f o r r e i f i c a t i o n .
RDFS
• r d f s : s u b C l a s s O f – t h e s u b j e c t i s a s u b c l a s s o f a c l a s s
• r d f s : s u b P r o p e r t y O f – t h e s u b j e c t i s a s u b p r o p e r t y o f a
p r o p e r t y
• r d f s : d o m a i n – a d o m a i n o f t h e s u b j e c t p r o p e r t y
• r d f s : r a n g e – a r a n g e o f t h e s u b j e c t p r o p e r t y
• r d f s : l a b e l – a h u m a n - r e a d a b l e n a m e f o r t h e s u b j e c t
• r d f s : c o m m e n t – a d e s c r i p t i o n o f t h e s u b j e c t r e s o u r c e
• r d f s : m e m b e r – a m e m b e r o f t h e s u b j e c t r e s o u r c e
• r d f s : s e e A l s o – f u r t h e r i n f o r m a t i o n a b o u t t h e s u b j e c t
r e s o u r c e
• r d f s : i s D e f i n e d B y – t h e d e f i n i t i o n o f t h e s u b j e c t r e s o u r c e
Properties
17. SPARQL
To query the RDFs graph, another langua ge
called ‘SPAR Q L ’ is used.
• It’s like an SQL languag e to query data
from databa s e .
• It’s not just SPARQ L that can query RDFs
graph but there are several others as well.
• For example, the code snippe t of SPARQL
query the country capital s in Africa.