Towards an Ontology Design Methodology - PowerPoint PPT Presentation

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Towards an Ontology Design Methodology

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this makes the process of creating the ontology seem very intimidating ... the ontology interacts with every other part of the project... ontology modelling ... – PowerPoint PPT presentation

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Title: Towards an Ontology Design Methodology


1
Towards an Ontology Design Methodology
  • Initial work

Lars Marius Garshol CTO, Ontopia ltlarsga_at_ontopia.n
etgt TMRA 2006 2006-10-11
2
Agenda
  • Background
  • why this is important
  • what it includes
  • The process
  • some background
  • roles
  • steps
  • The guidelines
  • examples
  • Conclusion
  • further work

3
Background
  • Why this is important
  • What it includes

4
The ontology challenge
  • For many customers, creating the ontology is the
    biggest hurdle
  • its something new to them, and they dont know
    how to approach it
  • the technology is new, and so most consultants
    are not familiar with it
  • this makes the process of creating the ontology
    seem very intimidating
  • it also means that the costs and challenges are
    unknown
  • Successfully developing an ontology is
    non-trivial
  • it can be politically challenging
  • the ontology interacts with every other part of
    the project...
  • ontology modelling requires analytical skill
  • the ontology is constrained by economical and
    technical considerations

5
The methodology vision
  • A defined process
  • roles involved in the process
  • a defined series of steps to follow
  • A set of modelling guidelines
  • essentially heuristics for the correct use of the
    constructs in Topic Maps
  • A pattern library
  • common solutions to common problems
  • A base ontology
  • PSIs for common concepts like person,
    description, ...

6
Scope
  • There are two general classes of applications
  • information retrieval-type applications
  • portals, library systems, publishing solutions,
    KM solutions, ...
  • traditional applications
  • CRM systems, product configuration applications,
    business process modelling, ...
  • Ontology design is different for these two
    applications
  • in traditional applications
  • the domain is already well-understood
  • the needs of the end-users are well-understood
  • none of this applies to information retrieval
    applications
  • Methodology focuses on information retrieval
    applications
  • process especially
  • guidelines are general

7
The process
  • Background
  • Roles
  • Steps

8
Simplified process view
Lacking source data
Lack of project consensus
Vision
Cant analyse domain
9
The process exists to handle these challenges
  • Source data gap or analysis gap
  • make sure you discover the gap in time
  • make sure you can find ways to plug it, or work
    around it
  • Project consensus
  • including the right people in the right way at
    the right time builds consensus
  • it also ensures people know what they need to
    know
  • Manage dependencies
  • keep track of what depends on the ontology

10
Roles
  • Project manager
  • runs the project
  • Developers
  • write the code
  • System owners
  • make the decisions regarding the project
  • Data source owners
  • manage systems which provide data to the new
    system
  • usually not part of the project
  • End-user
  • user of the final system
  • Ontology modeller
  • person responsible for ontology
  • Editors
  • people responsible for data in the system
  • Authors
  • people who write the content in the system
  • Domain expert
  • someone with knowledge of the domain

11
The role of the ontology
Ontology
12
Ontology considerations
Ontology
13
Startup
Analysis
Drafting
Interaction design
Verification
Startup
End-user
  • Usually a workshop
  • project manager, editors, ontology modeller
  • presentation QA
  • Key goals
  • establish requirements
  • get overview of data sources

14
Analysis
Analysis
Drafting
Interaction design
Verification
Startup
End-user
  • Usually interviews with data source owners
  • extract documentation, schemas, exports, ...
  • use torture if necessary
  • Key goals
  • understanding of what really is in the data
    sources

15
End-user
Analysis
Drafting
Interaction design
Verification
Startup
End-user
  • Well-known IA/UX exercise
  • competency questions
  • personas
  • end-user interviews
  • card sorting
  • ...
  • Ontology modeller IA/UX person end-user
    examples

16
Drafting
Analysis
Drafting
Interaction design
Verification
Startup
End-user
  • The ontology modeller produces a draft
  • should use diagrams to communicate design
  • UML, ORM, boxes-and-arrows, or (later) GTM
  • Draft must be reviewed with project team
  • editors, developers, project manager
  • nobody reads documentation
  • if they do, they dont understand it, anyway

17
Interaction design
Analysis
Drafting
Interaction design
Verification
Startup
End-user
  • A well-known exercise
  • experienced interaction designers are out there
  • Ensure that
  • ontology supports proposed design
  • ontology and proposed design use a consistent
    vocabulary
  • Output
  • normal interaction design documentation
  • updated ontology

18
Verification
Analysis
Drafting
Interaction design
Verification
Startup
End-user
  • Final quality assurance on ontology
  • first conversion from data sources
  • review interaction design against ontology
  • verify ontology against output from end-user
    phase
  • verify ontology against requirements from startup
    phase
  • final team review of ontology

19
Guidelines
  • Some examples

20
What is in the guidelines
  • Heuristics for the correct use of Topic Maps
    constructs
  • topic types
  • type hierarchy
  • association types
  • occurrence types (internal and external)
  • name types
  • The Ontopia ontology design course has the full
    set
  • taught in Kevin Trainors tutorial yesterday
  • only a small subset covered here for illustration
    purposes

21
Criteria for a good topic type
  • Instances should, by their intrinsic nature, be
    instances of the type
  • when shown an example instance and asked what is
    this? end-users should reply with the name of
    the topic type
  • instances should be instances of this topic type
    from the moment they come into being, until they
    cease existing
  • Should not be context-dependent
  • not a role type (like composer, employee, or
    subject)
  • The topic type should be a natural kind

22
Heuristics for association types
  • Keep number of roles as low as possible
  • decompose n-ary associations if possible
  • Have a consistent set of role types
  • all instances should have the same set of role
    types
  • omissible roles is acceptable
  • do not attach semantics to variation in role
    types
  • Create a topic for an n-ary association if (and
    only if)
  • you want to say something more about the
    association

23
Conclusion
  • Further work

24
Further work
  • The methodology has moved on since the draft was
    written
  • need to flesh it out and bring it into line with
    this presentation
  • Pattern library and base ontology need to be
    developed
  • this will follow in a separate phase after the
    paper is done
  • Input from practitioners wanted!
  • ltlarsga_at_ontopia.netgt
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