Small enterprises eCommerce Ontology

1
Small enterprises eCommerce Ontology

LdV Project Languages for eCommerce Work
Packages 2 and 5 Language analysis and tool
development terminology and ontology. Prof.
Wolf Paprotté, ICOS GmbH, Münster
2
Small enterprises eCommerce Ontology

• While the Internet successfully enables the
  exchange of multimedia information among human
  users, eBusinesses have not seen software
  solutions for successful information access.
• However, for the last decade, ontology has
  been the buzzword which promised that this
  semantic tool for business environments would
  enable not only human agents but also machines to
  interact and to acquire, share and exchange
  information.

3
Small enterprises eCommerce Ontology

• Key to success for all online marketeers is not
  to pay for the keyword in search engines but a
  consistent company defined vocabulary or
  marketing ontology
• quotation, loc. ?

4
Small enterprises eCommerce Ontology

• The goals of this presentation are
• - to explain the concept ontology
• to mention some methodological problems in
  ontology development
• to suggest extensions of the notion ontology in
  line with our project
• to point to available solutions for Ontology
  Management Systems (OMSs), e.g. Protegé and
  SymOntoX, OMSs for the eBusiness domain
• to draft a concept map.

5
Agenda

• What is an Ontology?
• Why ontologies?
• Methodology of Constructing Domain Models
• Describing ontologies with (in)formal language
• Methodological problems
• The Enterprise Ontology (TEO) and SNAP Ontology
• Possible extensions
• Bibliography

6
What is an ontology?

• the explicit formal specifications of the terms
  in the domain and relations among them (Gruber
  1993, 1995)
• formal explicit descriptions of concepts in a
  domain of discourse (Noy, McGuinness 2001)
• a coding of terms, to capture and describe an
  enterprise, its products, processes, strategy,
  organisational structure, resources, goals,
  constraints and environment (TEO, p.1)

7
What is an ontology (opt)

• Ontologies are agreements about shared
  concep-tualizations. Shared conceptualizations
  include conceptual frameworks for modeling domain
  knowledge content specific protocols for
  communication among inter-operating agents and
  agreements about the representation of particular
  domain theories.
• In the knowledge sharing context ontologies are
  specified in the form of definitions or
  representational vocabulary. A very simple case
  would be a type hierarchy, specifying the classes
  and their subsumption relationships.
• Quotation, p.6 Tove

8
What is an Ontology a common sense view

• Ontologies are models of a slice of reality,
  for example of the business world. The concepts
  and relations of the ontology must reflect this
  worlds reality.

9
Uses of Ontologies (opt)

• An ontology formalizes the semantics of the
  objects and relations in a universe of discourse
• - Its concepts and relations structure data
  and classify information.
• It serves mutual understanding and sharing of
  knowledge among human and non-human agents.
• - It makes domain assumptions explicit and
  analyses domain knowledge.
• It separates domain knowledge from operational
  knowledge.

10
Communication and Ontology

• Uses of ontologies
• Vocabulary versus a meta-level specification of
  a logical language

between
Communication between organsiations people
Interoperability
systems
Reliability Specification systems engineering
Reusable components
11
Why ontologies?

• An ontology defines the terms used to describe
  and represent an area of knowledge
• (W3C-OWL Specification, 1.1 What is an
  ontology)
• An eCommerce ontology describes a knowledge
  domain which is a part of to-days reality, that
  is of
• - technologically oriented enterprises,
• - global markets or the home market
• - the multilingual European Union
• - short life-cycles of IC technology
• The ontologys form follows function it is
  normally a
• complete and consistent inheritance taxonomy.

12
Why Ontologies - The Aims

• An enterprise Ontology
• a communication medium between people, machines
  and ORGs
• standardizes business communication
• focusses on multilingual corporate application
  domains (eCommerce, B2B, B2C )
• improves existing modelling methods integrates
  methods and tools for enterprise modelling
• specifies business requirements
• recovers and captures knowledge (e.g. data
  mining)
• contributes to interoperability

13
Methodology of Constructing Domain
Models (opt)

• Domain models are complex, take an effort to
  code, a long time to develop and are usually
  short of funding.
• It is also a necessity to build-up expertise.
• Therefore
• ? try to reuse an existing ontology,
• ? trim old, add and combine with new
  material
• ? use tools such as ONTOLINGUA PROTEGE,
• CML Editor, etc

14
Methodology of Constructing Domain
Models (opt)

• Obvious problems
• - concepts are equivalent, incompatible or over-
  lapping,
• - as in a dictionary entry, concepts are
  polysemous
• (A) The classical solution in lexicography
  concept crea- tion by additive feature
  specification (add differentiae)
• - intuition
• - distribution tests of paradigmatic
  substitutability
• (B) cross linguistic evidence for concepts
  (terms)

15
Methodology of Constructing Domain
Models (opt)

• How to arrive at a complete, correct, consistent
  ontology?
• (C) Noy and McGuinness solution
• Step 1. Determine domain and scope of the
  ontology
• Step 2. Consider reusing existing ontologies
• Step 3. Enumerate important terms in the ontology
• Step 4. Define the classes and the class
  hierarchy.
• Step 5. Define the properties of classes / slots
  
• Step 6. Define the properties / facets of the
  slots
• Step 7. Create instances  

16
Methodology of Constructing Domain
Models (opt)

• (C) Hovys solution hierarchical graduated
  refinement
• - Start with a word and a number of example
  sentences representing all / most of its
  meanings
• - Identify and split out the semantically most
  different sense cluster and create a node in the
  evolving tree.
• - For each branch repeat the process downwards.
• Stop process if the expected granularity has been
  reached
• or continue with further material to separate
  word senses from concepts.
• Iterate.

17
Methodology of Constructing Domain Models
(OPT)

• drive

ltother, variousgt
ltmove in desired directiongt
ltdrive madgt
ltnon-physicalgt
ltphysicalgt
ltbusinessgt
ltdemons
ltdollargt
ltpropelgt
ltdirectgt
ltmotivategt
ltlegsgt
ltcargt
ltcattlegt
18
Methodology of Constructing Domain
Models (opt)

• WordNet distinguishes for drive (v) 22 senses
• Hovy reduces the 22 senses to 7 which can be
• mapped into 3 distinct concepts
• Cause-mental-instability,
• Cause-state-change-toward-desired-value,
• Cause-movement-in-desired-direction

19
Methodology of Constructing Domain
Models (opt)

• S (n) drive, thrust, driving force (the act of
  applying force to propel something) "after
  reaching the desired velocity the drive is cut
  off"
• S (n) drive (a mechanism by which force or power
  is transmitted in a machine) "a variable speed
  drive permitted operation through a range of
  speeds"
• S (n) campaign, cause, crusade, drive, movement,
  effort (a series of actions advancing a principle
  or tending toward a particular end) "he supported
  populist campaigns" "they worked in the cause of
  world peace" "the team was ready for a drive
  toward the pennant" "the movement to end
  slavery" "contributed to the war effort"
• S (n) driveway, drive, private road (a road
  leading up to a private house) "they parked in
  the driveway"
• S (n) drive (the trait of being highly
  motivated) "his drive and energy exhausted his
  co-workers"
• S (n) drive, driving (hitting a golf ball off of
  a tee with a driver) "he sliced his drive out of
  bounds"
• S (n) drive (the act of driving a herd of
  animals overland)
• S (n) drive, ride (a journey in a vehicle
  (usually an automobile)) "he took the family for
  a drive in his new car"
• S (n) drive (a physiological state corresponding
  to a strong need or desire)
• S (n) drive ((computer science) a device that
  writes data onto or reads data from a storage
  medium)
• S (n) drive, parkway (a wide scenic road planted
  with trees) "the riverside drive offers many
  exciting scenic views"
• S (n) drive ((sports) a hard straight return (as
  in tennis or squash))

20
Methodology of Constructing Domain Models
(opt)

• S (v) drive (operate or control a vehicle)
  "drive a car or bus" "Can you drive this
  four-wheel truck?"
• direct troponym / full troponym verb group
  domain category direct hypernym / inherited
  hypernym / sister termderivationally related
  formsentence frame
• S (v) drive, motor (travel or be transported in
  a vehicle) "We drove to the university every
  morning" "They motored to London for the
  theater"
• S (v) drive (cause someone or something to move
  by driving) "She drove me to school every day"
  "We drove the car to the garage"
• S (v) force, drive, ram (force into or from an
  action or state, either physically or
  metaphorically) "She rammed her mind into focus"
  "He drives me mad"
• S (v) drive (to compel or force or urge
  relentlessly or exert coercive pressure on, or
  motivate strongly) "She is driven by her passion"
  
• S (v) repel, drive, repulse, force back, push
  back, beat back (cause to move back by force or
  influence) "repel the enemy" "push back the urge
  to smoke" "beat back the invaders"
• S (v) drive (compel somebody to do something,
  often against his own will or judgment) "She
  finally drove him to change jobs"
• S (v) drive (push, propel, or press with force)
  "Drive a nail into the wall"
• S (v) drive (cause to move rapidly by striking
  or throwing with force) "drive the ball far out
  into the field"
• S (v) tug, labor, labour, push, drive (strive
  and make an effort to reach a goal) "She tugged
  for years to make a decent living" "We have to
  push a little to make the deadline!" "She is
  driving away at her doctoral thesis"

21
Methodology of Constructing Domain Models (opt)

• S (v) drive, get, aim (move into a desired
  direction of discourse) "What are you driving
  at?"
• S (v) drive, ride (have certain properties when
  driven) "This car rides smoothly" "My new truck
  drives well"
• S (v) drive (work as a driver) "He drives a
  bread truck" "She drives for the taxi company in
  Newark"
• S (v) drive (move by being propelled by a force)
  "The car drove around the corner"
• S (v) drive (urge forward) "drive the cows into
  the barn"
• S (v) drive, take (proceed along in a vehicle)
  "We drive the turnpike to work"
• S (v) drive (strike with a driver, as in teeing
  off) "drive a golf ball"
• S (v) drive (hit very hard, as by swinging a bat
  horizontally) "drive a ball"
• S (v) drive (excavate horizontally) "drive a
  tunnel"
• S (v) drive (cause to function by supplying the
  force or power for or by controlling) "The
  amplifier drives the tube" "steam drives the
  engines" "this device drives the disks for the
  computer"
• S (v) drive (hunting search for game) "drive
  the forest"
• S (v) drive (hunting chase from cover into more
  open ground) "drive the game"

22
Ontologies formal quality criteria

• A minimalist ontology is a vocabulary of terms
  and definitions which is not normative but
  in-formal and related to a specific domain
• A scale of precision
• informal definitions ( natural language)
• semi-formal ( e.g. OIL, OWL, DAML, )
• rigorously formal ( formal semantics)
• The sources
• Common Sense Semantics or Wortfeld Theory
• or theories of action and of situation

23
Ontology Overview

• The Enterprise Ontology (TEO)
• Meta Ontology
• Sections
• ACTIVITY, PLAN, CAPABILITY , RESOURCE
• Organisation
• Strategy
• Marketing
• TIME
• cf. The Enterprise Ontology 1996, U of Edinburgh
  lt(TEO)gt

24
TEO Section Meta-Ontology

• Meta Ontology terms used to describe the terms
  of the Ontology
• ENTITY RELATIONSHIP ROLE
• A human being is an Entity
• A plan is an Entity
• An ENTITY may participate in
• RELATIONSHIPS with other
• ENTITIES
• RELATIONSHIP the way that
• two or more ENTITIES can
• be associated with each
• other.

• A RELATIONSHIP is itself an
• ENTITY that can participate in
• further RELATIONSHIPS.
• ROLE the way in which an ENTI
• TY participates in a RELATION-
• SHIP a participating ENTITY is
• said to be playing a role.
• VENDOR IS A ROLE played by
• an entity in a sale relationship

25
TEO Meta-Ontology

• ACTOR ROLE
• a ROLE in a RELATIONSHIP
• playing the Role entails a notion of
• doing or cognition.
• Set of Potential Actors is not
• limited to PERSONS MACHINES
• RELATIONSHIPS with ACTOR
• ROLES
• Perform-Activity performer
• HaveCapability haver
• Hold-Authority holder
• Delegate delegator delegatee
• Hold purpose holder
• Hold-Assumption holder
• Ownership owner owner

• RELATIONSHIP
• ATTRIBUTE A RELATIONSHIP
• between 2 ENTITIES called attri-
• buted and Value. The Relation-
• ship may exist with only one value
• ENTITY.
• State of Affairs a set of Relation
• ships between particular ENTI-
• TIES. ACHIEVE the realisation of
• a STATE OF AFFAIRS (being
• made true)

26
Informal coding, section 1

• 1. ACTIVITY and PROCESS The notion of ACTIVITY
  
• anything that involves actual doing, in
  particular action
• can (Past), may (Present) will (Future)l happen
  link to TIME INTERVAL.
• refers explicitly to specifications or plans for
  ACTIVITY ACTIVITIES
• SPECIFICATION
• EXECUTED ACTIVITY SPECIFICATION must have a
  corresponding A
• Concept of ACTIVITY is linked to the idea of the
  DOER which executes an ACTIVITY SPECIFICATION by
  performing the specified ACTIVITIES.
• A DOER may be a person, ORGANISATIONAL UNIT or
  MACHINE.
• The ability of a POTENTIAL DOER of an ACTIVITY
  is denoted by CAPABILITY
• or SKILL ACTORS may have other ROLES such as
  ACTIVITY OWNER,
• ACTIVITY may have EFFECTS (outputs)
• ACTIVITY SPECIFICATION with INTENDED PURPOSE /
  PLAN

27
TEO, section 1

• ACTIVITY ltcentral conceptgt actual doing /
  action, at time present
• or past or future
• ACTIVITY SPECIFICATION specifies plans for
  activity
• EXECUTED ACTIVITY SPECIFICATION has correspon-
  ding action /
  activity the thing done
• DOER who executes the specified activity
• DOER as PERSON or MACHINE AGENT, ORGANISATIONAL
  UNIT (potential actors)
• DOER of Activity Spec needs capability / skill
• POTENTIAL ACTOR may become DOER may have
• AUTHORITY the right of an actor to EXECUTE an
• ACTIVITY SPECIFICATION

28
Informal coding section 2

• 2. The section ORGANISATION has LEGAL ENTITY
  and
• ORGANIZATIONAL UNIT as central terms. LE is
  recognised as
• having rights and responsibilities in the world
  by legal jurisdiction
• whereas OU need only have full recognition
  within an organisation.
• A machine is non-human, non-legal entity that may
  play certain roles
• otherwise played by a person performing an
  action.
• Legal and non-legal OWNERSHIP. Management
  structure is repre-
• sented by management links. MANAGE represents
  assigning
• purposes to OUs

29
Informal coding section 3

• 3. SECTION STRATEGY
• Central concept is purpose with (a) the intended
  reason for executing
• an activity spec what a Plan is for. (b) what
  an ORG can be
• responsible for.
• Strategic purpose is relatively high level on
  long time scale the other
• purposes may be short term. Strategy is defined
  as a plan to achieve
• a strategic purpose. Strategic planning can be
  represented with the
• terms DECISION ASSUMPTION RISK.

30
Informal coding section 4 5

• 4. SECTION MARKETING
• Central concept SALE. A SALE is an agreement
  between two LES
• for the exchange of a product for a SALE PRICE.
• LEs play the ROLES of VENDOR and CUSTOMER. A
  product
• targeted at a specific customer is referred to a
  SALE OFFER,
• otherwise it is just FOR SALE.
• 5. SECTION TIME
• Basic concepts TIME LINE, TIME POINT derived
  terms
• DURATION, TIME INTERVAL CALENDER DATE. BEFORE
  and
• AFTER are represented as Relationships between
  TIME POINTS
• Overlaps relationships between time intervals

31
COMPARING ONTOLOGIES (TEO 7)

• MARKETING
• central notion SALE ( Agreement between two
  Legal Entities with ROLE VENDOR or CUSTOMER
  (BUYER) for the transaction PRODUCT for SALE
  PRICE.
• MARKET is all SALES and POTENTIAL SALES.
• including SALES by COMPETITOR
• MARKET decomposed in MARKET SECTIONS
• PRODUCTS have FEATURES, CUSTOMERS have NEEDS

32
eBusiness Ontology - SNAP

• SNAP applications business problems
• focus on products services
• automated product recommendation,
• finance , banking and telephony
• The fundamental concepts of SNAP
• situations, fluents, needs, and actions
• basic and derived relations of agent interaction
  which
• Is an efficient reasoning mechanism.

33
eBusiness Ontology - SNAP

• The SNAP ontology (2005)
• situation calculus with concepts Situation,
  Fluent, Event (or Action)
• theories of planning, with concepts desire,
  intention Needs.
• A distinct concept Agent does not appear but each
  concept of SNAP refers implicitly to agents.
• Situation slice of time of the world (describes
  how the world is at moment m). We are interested
  in the facts that are true in m hold (sm,f)

34
eBusiness Ontology - SNAP

• Fluent describes how the world is at moment m
  (the situation of interest) a description which
  is true in m (holds (s, f)
• As an example type of fluent agent having 2
  minor children.
• Types of Fluents
• Life Stages fluents that describe some major
  stage of a persons life.
• Age Life Stages Child, Teenager, Adult,
  Middle-Aged
• Career Stages Starting a job, Owning a
  business, Being a retiree
• Family Stages Parent, Parent of minor children,
  Empty nester

35
eBusiness Ontology - SNAP

• Types of Fluents
• Demographics These include such facts as
  marital status, income, and education.
• Life Style a persons habits, such as living
  expensively, living frugally, or taking frequent
  vacations.
• Obligations Obligations include financial and
  non-financial commitments. a persons outstanding
  loans to take care of an aging parent.
• Needs. Some thing desirable which an agent does
  not yet
• have.

36
eBusiness Ontology - SNAP

• Events noteworthy happenings or occurrences over
  the course of a persons life a single event is
  either
• planned action or observed behavior Life
  events (major life events), (minor),
  (eventualities )
• e.g. important events eCommerce events directly
  connected to an eComm transaction.
• Transactions such as purchasing a product or
  service come with features, selections and
  options one re- ceives a feature, makes a
  selection, chooses an option.

37
eBusiness Ontology - SNAP

• Basic relations
• 1. Planning relations
• (triggers (Fluent, Need) (having minor
  children, triggers need to provide for
  children)
• Servedby (Fluent, Need) need to improve health,
  is served by exercising
• Generates (Need, Need) need to buy a house
  generates need to finance the house
• Anticipates (Fluent, Need) life stage adult
  anticipates the need to retire comfortably

38
eBusiness Ontology - SNAP

• Causal Type Relations
• Causes (Event, Fluent) buying a house causes
  (owning a home) to be true
• DevelopsAfterTime (Life Stage, Life Stage)
  child becomes adult
• Leads to (Life Event, Life Event) getting
  married leads to move into larger house
• Constraint-type Relations Constrain (Fluent,
  Fluent) Constrain (Event, Fluent) Constrain
  (Event, Event)
• Derived relations basic building blocks
  correspond to types of
• reasoning. Some formal definitions to derive
  relations -Enhanced
• semantic networks

39
Some remarks

• 1. Large number of concepts in hierarchical
  taxonomy (TEO) SNAP, elegant, few basic
  concepts plus a large number of derived
  relations.
• situation, entity vs situation, fluents,
• 2. There are divergent asumptions TEO uses
  ACTOR , DOER
• as active Person / Machine / Organisation
  vs. Need / Goal in
• SNAP (ontological semantics)
• Communication between the two is impossible
  without translation or an Interlanguage.
• There is little agreement on the set of key terms
  for a domain

40
some remarks

• 5. No two ontologies rest on the same
  assumptions. Standardization is not achieved.
  Communication between ACTORS is difficult.
• 6. The position of concepts in the conceptual
  structure is negotiable, mediated by and
  influencing relevance.
• When concepts face technical terms without a
  Terminology and semantics specific knowhow is
  needed this means manual work.
• 8. Every eCom enterprise has a divide between
  proprietary and general, established uses of
  concepts
• 9. An eCom enterprise needs a specialist for the
  company ontology and authority for trouble
  shooting to ensure correct understanding of a
  discourse in B2B contacts.

41
shortcomings / critical remarks

• 10. The more semantic consistency is required,
  the sharper the tradeoff between complexity and
  scale of the ontology .
• Broad agreement on the concepts is easy to get
  in a small group of users. A large group of users
  will only agree on a small number of problems.
  To have both scale and complexity as well as many
  users is impossible.

42
shortcomings / critical remarks

• Differences in the ontology capture result from
• Methodological problems, and subjectivity when
  deciding
• on finding the important concepts
• selecting concepts for an established level of
  granularity and detail,
• not suitably contextualized concepts
• Incompletely defined and disambiguated concepts
  supported by a standardized terminology

43
Methodological assumptions

• No standard methodology is available.
• - Suggested steps define purpose and scope
• - Capture key concepts relationships
  unambiguous
• definitions for concepts
• Coding stick to basic terms (meta-ontology)
  explicit
• representation of conceptualisation degrees of
  formality
• choosing a representation language
• - integration of existing ontologies
• - Evaluation, documentation, guidelines

44
Desiderata missing sections - an ontology for
SMEOE

• Electronic Payment Systems
• Legal Aspects, Licencing, naming, branding
• (new form of Customer Relationship Management -gt
  no direct contact)
• Electronic Communication Interoperability of
  Actors, Persons and Machines
• Home page design for functionality, information
  and communication
• Multilingual web appearance

45
Communication and Ontology

• Communication difficulties between orgs and
  agents
• Lacking shared understanding
• Communication and understanding is never
  straight forward
• driven by needs, background, interest, other
  viewpoints, capability
• limits on inter-operability, re-use and sharing

46
Communication and Ontology

• Effects of ontology on communication
• Creates normative models
• Builds up networks of relationships
• Provides unambiguous definitions for terms
• consistent lack of ambiguity
• Integrating different user perspectives

47
Methodology

• Skeletal methodology for building ontologies
• Determine purpose and scope
• Why is onto built? What are intended uses?
• Build ontology onto capture identify key
  concepts and relationships
• onto coding production of
  precise text definitions
• Explicit representation
• integrating existing ontologies
• Evaluation
• Documentation inadequate doc of DBs maybe
  desirable to have effective knowledge sharing
• Guide line for every step

48
Goals, needs, aims

• Inter-operability system to system
• Use integrated enterprise models spanning
  activities, resources, organisation,,goals,
  products, services
• Ontologies as inter-lingua

49

• fundamental terms in each work area move on to
  more abstract more specific terms
• Doing something (physical activity)
• Specific kind of thing (go from a to b)
• Go to train station in York
• Ride train to London
• Go to local destination in London
• Ensure
• Produce nat lg text def, ensure consistencywith
  terms already in use, avoid circularity give
  examples

50
Methodology

• A formal approach to ontology design evaluation
• declarative specification, has benefits
• Extra-ontological assumptions
• No hidden assumptions
• Design options
• Ontological commitments
• Modifyability, reuseability, adequacy criteria

51

• Overview of formal methodology

52
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