Applying 4D ontologies to Enterprise Architecture
Matthew West
Copyright: SIPC
Reference Data Architecture and Standards Manager
– Shell
Abstract
Enterprise Architecture is the term used for a number of related models that
together describe an enterprise and its information systems. Many of these
models are ontological in nature or have ontological content. A particular
problem companies face is that historically many of their models have been
"snapshot" or "current state" models and have not been able to manage the
history of the enterprise, and of the models used to manage its information.
With increasing regulation, such as Sarbanes-Oxley legislation,this is
becoming an urgent problem.
4 Dimensionalism is a paradigm that sees objects as extended in time as well
as space. As such it has history built in, using a "God's eye view" (outside
time). Space-time maps are a technique for showing the patterns different
sorts of individuals make in space-time and are a valuable aid to analysis. We
will explore the use of these before looking briefly at one or two examples of
how they have been used to develop and support Shell's Downstream (oil
tanker to petrol pump) data model.
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What is (an) Ontology?
My Answer …
Ontology is the study of what exists.
An ontology is a theory of what exists.
Doesn’t have to be:
Formal (computer interpretable)
Use a particular form of logic
Complete (fully axiomatised)
Can be:
Philosophical (sorts, identity criteria, lots of discussion)
Artificial Intelligence, e.g. First Order or Description Logic based formal ontology.
Database structure and data in a database
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Ontologies
4
How are these ontologies held?
•
Data Model
•
Process Model
•
Locations/Networks
•
Organization/Workflow
•
Events/Business cycles
•
Business Rules
•
Data Model
•
Process Model
•
Data
•
Documents
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Ontological Rigour
The wider use of Ontologies beyond reasoning
Huge potential to apply
ontologies to traditional
systems
Small number of
sophisticated
applications
Vast bulk of
information systems
Ontology limited or
implicit
SQL
Upper Ontologies
Small but increasing
number of lower and mid
level ontologies
Entity
OWL DL
Relationship
OWL Full
First Order
Logic
Language expressiveness
Higher
Order Logic
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So what are the practical problems Shell has
been grappling with?
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Differing data models for the same thing in
different parts of Shell c1990
Comp.
Canada
C.I.A.
SUKO
MF
Aus.
Model
BOSS
CMF
Arch.
Eng.
Arch.
MF
EP
SNR
SNC
Matrix
HydroC. DataMdl Ref.Mfg. Data Str. MCSM
Area
Org'n
Loc'n
Product
Equip.
Facility
Contract
Plan
Purch.
Prod'n
Stock
Sale
Price
Account
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Data Model Notation: EXPRESS-G
entity_y
Supertype relationship (subtype at circle end)
entity
relationship
attribute
entity_x
STRING
simple data type
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2. Cardinalities that lose history
•
Sometimes cardinalities are set one-to-many (meaning one at a time), when they are really many-to-many
because the relationship is transferable.
•
Imposing restrictions through data structure means:
•
–
Arbitrary or inappropriate restrictions are placed on the data that can be held.
–
History data about a relationship cannot be held.
–
Data may be replicated to overcome the restrictions in the data structure. The different versions must be reconciled.
–
The entity type will only work within the context defined. A change in business rules may require a change in the database structure.
–
The resultant system is harder to share.
This has only become more important with regulations like Sarbanes-Oxley (US accounting rules following the ENRON
scandal)
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Example: Ship
registered_at
Port
Ship
registered_under
Name
Transferable relationships
•
What happens if you re-register a ship?
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How can ontology help?
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3D and 4D approaches to ontology
•
Data model consistency is dependent on taking a common view of how to represent things across the
business.
•
Unfortunately there are many ways in which we can model the world.
•
However, there are two main approaches, with on the whole minor variations, that dominate the
philosophical literature.
•
I will call these the 3D paradigm and the 4D paradigm.
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3D Paradigm
•
A 3D ontology treats physical objects (roughly things you can kick) as 3D objects (sometimes
called continuants) that pass through time. The principles of the 3D paradigm are:
1. Physical objects are 3-dimensional objects that pass through time and are wholly present at each
point in time.
2. Physical objects are viewed from the present. The default is that statements are true now.
3. Physical objects do not have temporal parts.
4. Different physical objects may coincide.
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3D Individual
The present
(all that exists)
space
Object passes through time.
time
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4D Paradigm
• A 4D ontology treats all individuals – things that exist in space-time - as spatio-temporal extents,
i.e. as 4D objects.
The principles of the 4D paradigm are:
1. Individuals exist in a manifold of 4 dimensions, three space and one time. So things in the past and
future exist as well as things in the present.
2. The four dimensional extent is viewed from outside time rather than from the present.
3. Individuals (including physical objects) extend in time as well as space and have both temporal
parts and spatial parts.
4. When two individuals have the same spatio-temporal extent they are the same thing
(extensionalism).
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Possible Individual
The past and the future exist as well
as the present
space
Object extended in time
time
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Which paradigm?
•
The 3D approach corresponds well with the way that language works. Language has a focus around here,
now, you and me as a context, and on the current state of affairs. This leads to efficient communication
under the most common circumstances. On the other hand dealing with change is relatively problematic.
•
What is clear is that the 3D and 4D paradigms cannot be merged into a single canonical approach, since they
are contradictory, with one requiring physical objects to have temporal parts, and the other forbidding them.
•
On the other hand, it appears that what can usefully be said using one paradigm can generally be said using
the other.
•
For ISO 15926 (and Shell’s DDM) we chose the 4D paradigm because we found it to be rigorous, and gave a
good account of some difficult cases.
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Space-Time diagrams – an aid to analysis
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Possible Individual/State – Temporal whole-part
space
Time
period
State
Individual
Events
time
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Materialised Physical Object
space
event 1
B
A
event 2
D
C
Head
Handle
time
The Broom
21
space
A game of football – the ball
2nd Half
1st Half
Football Match
time
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A game of football – some players
Object continues
Replaceable
Parts
Scattered parts
space
Owen
Rooney
Player 1
Lampard
Player 2
Gerard
Player 3
2nd Half
1st Half
Football Match
time
Note: Some replaceable parts are roles
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A game of football – Roles
Replaceable
Part/Role
Captain
space
Owen
Gerard
2nd Half
1st Half
Football Match
time
Note: Some replaceable parts are roles
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Your turn to do some work
Draw one or more space time diagrams for the participants in the following end-to-end pump impeller
replacement activity:
•
A maintenance engineer requests purchasing to buy a new impeller for a pump.
•
Purchasing order an impeller from the pump manufacturer sales dept.
•
The pump manufacturer deliveries department delivers the impeller.
•
The maintenance engineer replaces the pump impeller.
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One I prepared earlier – Part 1
End to end impeller replacement process
Customer Organization
Delivery
Impeller Replacement
Request
Engineering
space
Purchasing
Delivery
Sales
Order
Supplier Organization
time
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One I prepared earlier – Part 2
Impeller Replacement
Pump No 3 Impeller
space
Pump No 3
Engineering
time
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So what does the data model look like?
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ISO 15926 – Thing
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Possible Individual
whole
possible_
individual
9,1 event
part
composition_of_
individual
1
whole_life_
individual
9,3 participation
period_in_time
temporal_
whole_part
actual_individual
9,2 activity
9,4 temporal_bounding
physical_object
functional_
physical_object
arranged_
individual
arrangement_
of_individual
(RT) whole
1
assembly_of_
individual
materialized_
physical_object
stream
spatial_location
feature_whole_
part
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Activity
(RT) part
event
(RT) whole
(ABS)
temporal_bounding
caused
possible_individual
1
beginning
point_in_time
ending
cause_of_event
causer
involver
activity
involvement_
by_reference
(RT) whole
involved
1,1 thing
(RT) part
possible_individual
participation
recognizing
recognized
recognition
1,1 thing
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Who is involved in Buying and Selling?
Shell’s Downstream Data Model (DDM) has extended ISO 15926-2 from 201
entity types to more than 1700
Many different parties can be involved in buying and selling.
Some of these parties are defined in the Organization schema – this is shown on
the next slide
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Buy and Sell parties
participation_of_
responsible_
individual
agent
buyer
class_of_participation_
of_responsible_individual
(RT) classified_by S[1:?]
participating_part_of
2,1 responsible_individual
business_role_in_
business_transaction
invoicing_party
19,1 class_of_participation_
of_Shell_organization
19,2 participation_of_Shell_
organization
20,1 class_of_supplier
stakeholder
17,1 Shell_business_partner
20,2 class_of_customer
21,1 relationship_
administrator
shareholder
contractor
These subtypes
give us some of
the parties in
buying & selling
20,3 trading_party
originator
inspector
23,1 employee
manufacturer_
or_supplier
dunning_clerk
order_recipient
authoriser
goods_receipt_clerk
23,5 employer
dispatch_clerk
purchase_requisition_
authority
purchasing_authority
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Summary
•
Much business modelling has (or should have) ontology at its core
•
Ontology has very wide applications
– Ontology has been practised by many disciplines
– The largest area for the application of ontology is in Business Information Systems
•
The application of ontology can add considerable value to businesses
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