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Applying 4D ontologies to Enterprise Architecture

Matthew West

Reference Data Architecture and Standards Manager – Shell

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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

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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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The wider use of Ontologies beyond reasoning

Language expressiveness

Ont

olog

ical

Rig

our

SQL Entity Relationship

OWL DL OWL Full First Order Logic

Higher Order Logic

Upper Ontologies

Vast bulk of information systemsOntology limited or

implicit

Small number of sophisticated applications Small but increasing

number of lower and mid level ontologies

Huge potential to apply ontologies to traditional systems

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So what are the practical problems Shell has been grappling with?

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Matrix

Account

Org'n

Loc'n

Contract

Plan

Product

Equip.

Facility

Prod'n

Stock

Purch.

Sale

Price

Canada C.I.A. SUKO SNRAus.MF MF EP SNC

BOSS CMF Arch. Ref.Mfg.Arch.Eng. HydroC. DataMdl MCSM

Comp.

Model Data Str.

Area

Differing data models for the same thing in different parts of Shell c1990

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Data Model Notation: EXPRESS-G

entity entity_xrelationship

STRING

simple data type

attribute

entity_y

Supertype relationship (subtype at circle end)

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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

• What happens if you re-register a ship?

Ship

Port

Name

registered_at

registered_under

Transferable relationships

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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

time

space

The present

(all that exists)

Object passes through 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

time

space

Object extended in time

The past and the future exist as well as

the present

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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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State

Time period

Individual

Possible Individual/State – Temporal whole-part

time

space

Events

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A

B

C

D

event 1 event 2

Materialised Physical Object

time

space

The Broom

HeadHandle

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A game of football – the ball

time

space

Football Match

1st Half 2nd Half

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A game of football – some players

time

space

Football Match

1st Half 2nd Half

Player 1

Player 3

Player 2

Owen

Lampard

Gerard

Rooney

ReplaceablePartsScattered

parts

Note: Some replaceable parts are roles

Object continues

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A game of football – Roles

time

space

Football Match

1st Half 2nd Half

CaptainOwen

Gerard

ReplaceablePart/Role

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

time

space

Supplier Organization

Customer Organization

End to end impeller replacement process

Request

Engineering

Purchasing

Delivery

Sales

Order

Impeller Replacement

Delivery

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Pump No 3

One I prepared earlier – Part 2

time

space

Pump No 3 Impeller

Impeller Replacement

Engineering

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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

possible_individual

arranged_individual

9,1 event

period_in_time

physical_object

materialized_physical_object

functional_physical_object

stream

spatial_location

9,2 activity

actual_individual

whole_life_individual

composition_of_individual

1

arrangement_of_individual

1

assembly_of_individual

feature_whole_part

(RT) whole

whole

temporal_whole_part

9,3 participation

9,4 temporal_bounding

part

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Activity

event

point_in_time

activityparticipation

(RT) whole

(ABS)temporal_bounding

1

ending

beginning

(RT) part

cause_of_event

caused

causer

involvement_by_reference

involved 1,1 thing

involver

recognitionrecognized

1,1 thingrecognizing

(RT) part possible_individual

(RT) whole possible_individual

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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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These subtypes give us some of the parties in buying & selling

Buy and Sell parties

class_of_participation_of_responsible_individual

business_role_in_business_transaction

19,1 class_of_participation_of_Shell_organization

20,1 class_of_supplier

20,2 class_of_customer

participation_of_responsible_

individual

17,1 Shell_business_partnerstakeholder

shareholder

contractor

20,3 trading_party

23,5 employer

19,2 participation_of_Shell_organization

(RT) classified_by S[1:?]

inspectorgoods_receipt_clerk

dispatch_clerk

dunning_clerk

authoriser

purchase_requisition_authority

purchasing_authority

originatororder_recipient

manufacturer_or_supplier

buyer

agentinvoicing_party

21,1 relationship_administrator

23,1 employee

participating_part_of 2,1 responsible_individual

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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