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What are we Talking About, When we Talk About Ontology?

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In this talk we will go back to basics with ontologies and from that project forwards to their future. I’ll base most of what I talk about on my experience in bio-ontologies, but most experience will be applicable in many domains; most domains are not as special as they think.

When it comes down to the basics, we need to know what our data represent or mean; that is where ontologies come into play; We need to know what we’re talking about. Once we have that clear we can proceed. There is much that one can do with data once we know what it means.

We can exploit those data through knowing what it represents. We can exploit these data better if our ontologies are also better. In taking this simple point of view forwards, I will use this talk to establish a set of principles for ontologists.

Published in: Data & Analytics
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What are we Talking About, When we Talk About Ontology?

  1. 1. What are we talking about? Robert Stevens School of Computer Science University of Manchester United Kingdom Robert.Stevens@Manchester.ac.UK
  2. 2. 27 What are we talking about?
  3. 3. We know it’s a length, but does the computer? 27mm What are we talking about?
  4. 4. A tail of what and what is a tail?27mm What are we talking about?
  5. 5. What is a mouse, what do we know about mice? 27mm What are we talking about?
  6. 6. mm Unit of measurement MouseTail Mouse partOf kindOf Rodent kindOf Mammal Length subClassOf subClassOf kindOf BodyPart What are we talking about?
  7. 7. GO:1905426 positive regulation of Wnt- mediated midbrain dopaminergic neuron differentiation rdfs:label Any process that activates or increases the frequency, rate or extent of Wnt signaling pathway involved in midbrain dopaminergic neuron differentiation. Textual definition: What is this thing and what is it called?
  8. 8. GO:1905426 positive regulation of Wnt- mediated midbrain dopaminergic neuron differentiation rdfs:label Any process that activates or increases the frequency, rate or extent of Wnt signaling pathway involved in midbrain dopaminergic neuron differentiation. Textual definition: positive regulation of Wingless signaling pathway involved in DA neurogenesis from midbrain floor plate oboInOwl:hasExactSynonym up regulation of Wg signaling pathway involved in midbrain DA neurogenesis up-regulation of Wingless signalling pathway involved in mDA neuron differentiation upregulation of frizzled signaling pathway involved in midbrain dopaminergic neuron production activation of Wnt- mediated midbrain DA neuron differentiation What is this thing and what is it called?
  9. 9. Neoplasm Malignant new growth New growth subClassOfsubClassOf Worry about definitions not labels
  10. 10. • Over modelling makes finer and finer distinctions • If the distinction makes no difference then don’t make it • Angels on the head of a pin: How many? No Distinction without a Difference
  11. 11. I Apple II Seed III Cotyledon IV Start V Glucose VI Carbon VII proton VIII quark Don’t model the world
  12. 12. Be as complex as necessary, not as much as you want
  13. 13. Protein EnzymeHolo protein Holo enzyme subClassOfsubClassOf subClassOf Prosthetic group hasPart hasPart Catalytic activity hasFunction hasFunction Let the reasoner do the work
  14. 14. Protein EnzymeHolo protein Holo enzyme subClassOfsubClassOf subClassOf Prosthetic group hasPart hasPart Catalytic activity hasFunction hasFunction subClassOf Let the reasoner do the work
  15. 15. • Using OWL semantics and a reasoner can help maintain structure • It won’t make the domain knowledge correct • It can reveal what we didn’t know we knew… Let the reasoner take the strain
  16. 16. Do what is necessary for the purpose Application Ontology Reference Ontology “What is necessary for the application” “All we know about a domain of interest”
  17. 17. Be wary of edge cases
  18. 18. • The purpose is to know what we’re talking about • Don’t be too beholden to a philosophical stance • Don’t model the whole world • Beware of edge cases • “Maximise the work not done” – re-use, patterns and reason • Worry about definitions not labels • Be consistent Some Principles

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