The challenge of making ontologies useful and usable

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The challenge of making ontologies useful and
usable

• Alan RectorSchool of Computer Science /
  Northwest Institute of Bio-Health
  Informaticsrector_at_cs.man.ac.uk
• www.co-ode.orgwww.clinical-escience.orgwww.openg
  alen.org

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Tree of Knowledge
Courtesy of Hodgson, TopQuadrant
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SWRL
OWL-QL
RDQL
Courtesy of Berners-Lee
http//www.w3.org/2003/Talks/05-gartner-tbl/slide3
0-0.html
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Users face a complex landscape
Courtesy of Hodgson, TopQuadran via Carole Goblet
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Inhabited by many tribes,Each tribe in its own
teepee
Descriptionlogic
Complexity theory
Fuzziness
Defaultlogics
KR Logics
BeliefRevision
Logic programming
NaturalLanguage
Bayesiananalysis
Argumentation
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and what feel like class divides
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The chain of theorem envy
The chain of value
No one person can understand it all - must manage
the chain
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but logicians are often seen as policemen
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or insist users understand the solution space
The semantics isyour job! Meet users where
they are
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So what is an ontology?

• Deborah McGuinness, Stanford

General Logical constraints
Frames (properties)
Formal Is-a
Thesauri
Catalog/ ID
Disjointness, Inverse, partof
Formal instance
Informal Is-a
Terms/ glossary
Value restrictions
Arom
Gene Ontology
TAMBIS
EcoCyc
Mouse Anatomy
PharmGKB
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My definition of an ontology

• Short versiona representation of the shared
  background knowledge for a community
• Long versionan implementable model of the
  entities that need to be understood in common in
  order for some group of software systems and
  their users to function and communicate at the
  level required for a set of tasks
• ... and it doesnt make the coffeeJust one of
  at least three components of a complete system

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But whats it for?
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Ontologies in Information Systems

• What information systems can say and how -
  Models of Meaning
• Mathematical theories - although usually weak
  ones
• evolved at the same time as Entity Relation and
  UML style modelling
• Managing Scalabilty / complexity - Knowledge
  driven systems
• Housekeeping tools for expert systems
• Organising complex collections of rules, forms,
  guidelines, ...
• Interoperability
• The common grounding information needed to
  achieve communication
• Standards and terminology
• Communication with users
• Document design decisions
• Testing and quality assurance
• sufficient constraints to know when it breaks
• Empower users to make changes safely
• ... but They dont make the coffee
• just one component of the system / theory

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The scaling problem The combinatorial explosion

• It keeps happening!
• Simple brute force solutions do not scale up!

• Conditions x sites x modifiers x activity x
  context?
• Huge number of terms to author
• Software CHAOS

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Combination of things to be done time to do
each thing

• Terms and forms needed
• Increases exponentially

• Effort per term or form
• Must decrease tocompensate
• To give the effectiveness we want
• Or might accept

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The means Logic as the clips for
Conceptual Lego
gene
protein
polysacharide
cell
expression
chronic
Lung
acute
infection
inflammation
bacterium
deletion
polymorphism
ischaemic
virus
mucus
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Logic as the clips for Conceptual Lego
SNPolymorphism of CFTRGene causing Defect in
MembraneTransport of Chloride Ion causing
Increase in Viscosity of Mucus in CysticFibrosis
Hand which isanatomically normal
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Build complex representations from
modularisedprimitives
Species
Genes
Function
Disease
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and more forms
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A conceptual Coat rackFractal tailoring of
reusable resourcesexample of data collection
forms for trials
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• Solution space
• Ontologies
• Information Models
• Logics
• Rules
• Frames
• Planners
• Logic programming
• Bayes nets
• Decision theory
• Fuzzy sets
• Open / closed world

• Problem space
• Answer questions
• Advising on actions
• Hazard monitoring
• Creating forms
• Discovering resources
• Constraint actions
• Assess risk

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Problem space solution space
Problem space
Solutionspace
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Matching problems and solutions is worthwhile
sciencen craft

• Patterns, guidelines and tools
• Reformulations of users solutions
• Collaborations with behavioural scientists
• Challenges and demonstrations

Some observations
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By way of User Centred DesignOntologies were a
solution, not a goal
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Motivation - automation
Courtesy of Semigix
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Inter-rater variability
ART ARCHITECTURE THESAURUS (AAT) Domain art,
architecture, decorative arts, material
culture Content 125,000 terms Structure 7
facets, 33 polyhierarchies Associated concepts
(beauty, freedom, socialism) Physical attributes
(red, round, waterlogged) Style/Period (French,
impressionist, surrealist) Agents (printmaker,
architect, jockey) Activities (analysing,
running, painting) Materials (iron, clay,
emulsifier) Objects (gun, house, painting,
statue, arm) Synonyms Links to associated
terms Access lexical string match
hierarchical view
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And to real world problemsThe Coding of
ChocolateAn international conversion guide
SNOMED-CT

• C-F0811
• C-F0816
• C-F0817
• C-F0819
• C-F081A
• C-F081B
• C-F081C
• C-F0058

?
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Technology is improving

• Understanding of the Web stack is improving
• OWL is improving
• OWL 1.1
• but we are just beginning to learn how to use it
• Tools are improving
• Protege4, NEON, ...
• Applications are happening
• In Bioinformatics
• In Health Informatics
• Moores law is coming to the rescue
• We are crossing a critical threshold

... but for human issues we are just starting
almost ready to ask the important questions
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Challenges

• Understanding problems
• From users perspective
• From value perspective
• Matching solutions to problems
• Solutions exist to solve problems
• ... solution designers exist to make better
  solutions
• Understanding misunderstandings
• Not trying to do the impossible
• Chocolate bars on the two sides of the Atlantic
  are different
• Improving the technology
• The dog just barely walks on its hind legs
• So
• What can we do?
• Whats it good for?
• Is it useful and usable?

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