1. Why do we need upper ontologies? What are their purported benefits?
Barry Smith and Alan Ruttenberg
University at Buffalo
IAOA Summer Institute on Upper Ontologies
Toronto August 9, 2017

2. Why do we need upper-level ontologies?
Is the distinction between continuant and occurrent just a security blanket for philosophers? Poisoning

3. Wed Session 1: Why do we need upper ontologies?
1. Why do we need top-level ontologies? 2. Why do we need mid-level ontologies (for space, time, information, …)? Q: Where do we draw the line between the two?

4. Why do we need top-level ontologies?

5. Why do we need a good top-level ontology?
Q: How do we pick out the good one(s)?

6. Why do we need a good top-level ontology?
Q: How do we pick out the good one(s)? A: Aggressive testing in real-world contexts

7. What does aggressive testing in real-world contexts tell us about what a good TLO is useful for?

8. The problem facing model organism researchers with the completion of the human genome project
Human, mouse, rat, fly, fish, yeast, …
Different vocabularies for each model organism
What do you call (human:) cleft palate in zebrafish?
One approach: pair off laterally, create mappings between human and mouse, between human and rat, between human and fly, …
GO approach: move up one level, create a vocabulary for talking about attributes of gene products that is species neutral
(future proof because the approach will still apply as data pertaining to new model organisms need to be incorporated)

9. What does aggressive testing in real-world contexts tell us about what a good TLO is useful for?
RELATION
TO TIME
GRANULARITY
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
Organ
Function
(FMP, CPRO)
Phenotypic Quality (PaTO)
Biological Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
Molecular Process
Original OBO (Open Biomedical Ontologies) Foundry (Gene Ontology in yellow)

10. The problem facing model organism researchers with the introduction of the GO?
Gene product attributes = cellular component, molecular function, biological process
What about diseases, anatomy, proteins, cell types, …?
Different vocabularies for each life science domain
One approach: pair off laterally, create mappings between molecular function and diabetes, molecule function and influenza, molecular function and cancer, dendritic cell and hip replacement surgery, … … … … …
TLO approach: move up one level, create a vocabulary for talking about the phenomena of the life sciences that is domain neutral
(future proof because the approach will still apply as data pertaining to new sorts of entities need to be incorporated)

11. Wed Session 1: Why do we need upper ontologies?
1. Why do we need top-level ontologies? 2. Why do we need mid-level ontologies (for space, time, information, …)? Q: Where do we draw the line between the two? A: TLOs are domain-neutral

12. Build new ontologies to conform to the upper-level architecture of BFO
RELATION
TO TIME
GRANULARITY
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
Organ
Function
(FMP, CPRO)
Phenotypic Quality (PaTO)
Biological Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
Molecular Process
BFO provides a common starting point for definitions
+ an evolving common set of best practices

13. What you get
Safer division of labor – clarifies what sorts of ontologies (of processes, of objects, of qualities, … are needed and how they relate to the ontologies we already have)
Safer distribution of labor – there are benefits to restricting choices to only what is made available in a well-worked out scheme
Audit trail to reality – require all classes to be defined in terms of lower-level classes in such a way that we always know what the instances are that we need to check to test if an assertion is true

14. Simple examples 1. Old chemistry ontologies
oxide and aluminium oxide are both instances
but then how can you assert the relation between them?
New chemistry ontology: they are both classes
2. NeuronDB database of proteins classified into functions
(inhibitor, dopamine receptor …).
Some time later they have to link their data to data classified using PRO and the GO function ontology.
They cannot do this because they used ‘protein’ to mean ‘function of a protein’. BFO would have told them to make two ontologies (for function and for protein) from the very start

15. https://senselab.med.yale.edu/NeuronDB/NeuronalReceptors

17. Thursday Session 2:
Relationships among Upper Ontologies

18. Q: How to integrate biological and clinical data
within and across domains
across different species
across levels of granularity (organ, organism, cell, molecule)
across different perspectives (physical, biological, clinical)
A: by tagging with ontologies
What could go wrong?

19. 379 Ontologies

27. Linked Open Data

28. divided we fail

29. LOD: we can save the day with mappings

30. LOL: we can save the day with mappings
Mappings are fragile – since both sides of the mapping will change independently Mappings are expensive to maintain

31. LOL: we can save the day with mappings
between terminologies?
Mappings are fragile – since both sides of the mapping will change independently
Mappings are expensive to maintain
The goal should be to minimize the need for mappings
By finding out how to create a good, robust ontology, and by creating one ontology module for each domain

32. Original OBO Foundry ontologies
RELATION
TO TIME
GRANULARITY
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
Organ
Function
(FMP, CPRO)
Phenotypic Quality (PaTO)
Biological Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
Molecular Process
Original OBO Foundry ontologies
(Gene Ontology in yellow)

34. Mapping GFO to DOLCE

38. Mapping of DOLCE to BFO

39. principles for BFO 2.0 to DOLCE mapping
whenever possible, map to the most specific BFO 2.0 representational unit with an equivalence relation;
if there is no equivalence, map to the most specific superordinate BFO 2.0 representational unit with a subclass relation
if more than one mapping is possible, map to the union of BFO 2.0 lowest level representational units

45. BFO: Continuant Ontology

47. Thursday Session 4: Relationships among Upper Ontologies:
Upper Ontologies in Different Logics
If an upper ontology is axiomatized in Common Logic and there exists another axiomatization in OWL, in what sense are they really the same ontology?

48. ontology =def. a collection of terms and relational expressions, together with definitions and axioms expressed in a computer interpretable language
NOTE 3: The term ‘ontology’ is sometimes used in a narrow sense to refer to specific formal representations. In this standard, however, an ontology is conceived as an artefact created by humans in time, comparable in this respect to a scientific theory or to a lexicon. Thus an ontology may exist in different versions at different times, for example as a result of the fact that errors are corrected or new terms added.

49. What is a credit card number?
– not a mathematical object – not a contingent object with physical properties, taking part in causal relations – but a historical object, with a very special provenance – stands in relations analogous to those of ownership, – exists only within a system of working financial institutions of specific kinds

50. Information vs. Information Artifact
‘information’ – mass noun (Shannon and Weaver)
‘information artifact’ – count noun (Information Artifact Ontology)

51. Information Artifacts in Science
protocol
database
theory
ontology
gene list
publication
result
...

52. a credit card number is a generically dependent continuant
It requires some bearer, but it can migrate from one bearer to another (can exist in many different places at one and the same time)
It is a historical object, with a very special provenance
It stands in relations analogous to those of ownership,
It exists only within a system of working financial institutions of specific kinds

53. what is a credit card account?

54. what is an ontology? a generically dependent continuant
bearers: hard drives, paper documents, people’s brains …
a historical object, with a very special provenance
It stands in relations such as being used, being amended, being understood, being reasoned with
It exists only within a system of working socio-linguistico- computational institutions of specific kinds

55. Goal for BFO-OWL
Everything in the OWL should be interpretable in terms of the FOL
Sound with respect BFO-FOL
Maximize useful entailments
Axiomatize BFO in FOL based on:
universals in domain of discourse
time-indexed instantiation
exists_at

56. Goal for BFO-OWL (contd.)
Define OWL-Specific relations
e.g. temporalized binary relations
Show consistency of axiomatization
Prove each OWL assertion on background of BFO FOL
Extend, as needed, Lisp Semantic Web (LSW) Toolkit
Common-lisp based, incremental development, interactive evaluation
Simple, but extensible, language for writing FOL – similar to common logic, with macros
OWL construction, reasoning. OWL->FOL translation.
Provers: Prover9, Z3, Vampire, HermiT, Fact++, Pellet, Elk
Translators: prover9 syntax, SMT-LIB, Common Logic, Latex
Checks: satisfiability, proof, non-entailment, model construction/checking

57. Working with LSW Basic checks Definitions of OWL relations, theories,
Proofs expectations of their properties

58. 3.13
top-level ontology (TLO)
an ontology that is created to represent the categories that are shared across a maximally broad range of domains