1 How to build an ontology Barry Smith

2 Two types of ontology natural-science ontologies capture terminology-level knowledge used by best current science vs. administrative ontologies (e.g. billing ontologies, bloodbank ontologies, lab workflow ontologies)

3 Scientific ontologies have special features Every term in a scientific ontology must be such that the developers of the ontology believe it to refer to some entity on the basis of the best current evidence

4 For scientific ontologies reusability is crucial compatibility with neighboring scientific ontologies is crucial  it should not be too easy to add new terms to an ontology we want to introduce these features in clinical medicine...

5 For scientific ontologies the issue of how the ontology will be used is not a factor relevant for determining which entities will be acknowledged by the ontology If this decision is made on specific practical needs, this will thwart reusability of the data the ontology is used to annotate

6 Administrative ontologies Entities may be brought into existence by the ontology itself. (Convention...) Highly task-dependent – reusability and compatibility not (always) important Developers may invent dummy entities (‘surgical procedure not performed because of patient request’) e.g. for forensic reasons (reality and knowledge are confused)

7 Hypothesis Many of the shortfalls of existing administrative ontologies can be overcome by adopting the scientific approach A good theory is, in the long run, also practically useful Administrative ontologies ~ data models

An Ontological Square Ontologies in support of science Administrative ontologies

9 An Ontological Square Upper-level integrating ontologies Domain ontologies

10 An Ontological Square Upper-level integrating ontologies Domain ontologies Ontologies in support of science Administrative ontologies

11 An Ontological Square Upper-level integrating ontologies Domain ontologies Ontologies in support of science BFO (Basic Formal Ontology) DOLCE SNOMED SwissProt FMA Administrative ontologies (for e- commerce, etc.) FOAF top level: person, topic, document, primary topic... Amazon.com ontology Library of Congress Catalog

12 Problem of ensuring sensible cooperation in a massively interdisciplinary community concept type instance model representation data

13 RetailPrice hasA Denomination InstanceOf Dollar (p. 101) SI-Unit instanceof System-of-Units (p. 40) from Handbook of Ontology (Semantic Web approach)

14 from: Ontological Engineering (Semantic Web approach) location =def. a spatial point identified by a name (p. 12) arrivalPlace =def. a journey ends at a location (p. 13) facet =def. ternary relation that holds between a frame, a slot, and the facet (p. 51)

15 What must an ontology contain terms (represent types in reality) preferred labels synonyms unique IDs alphanumeric identifiers for each term namespace ID (e.g. GO) nodes edges definitions axioms

16 Entity =def anything which exists, including things and processes, functions and qualities, beliefs and actions, documents and software (Levels 1, 2 and 3)

17 what are the kinds of entity?

18 First basic distinction universal vs. instance (science text vs. diary) (human being vs. Tom Cruise)

19 For science, and thus for scientific ontologies, it is generalizations that are important = universals, types, kinds, species

20 A515287DC3300 Dust Collector Fan B521683Gilmer Belt C521682Motor Drive Belt Catalog vs. inventory

21 Catalog vs. inventory

Catalog of Universals/Types

23 Ontology Universals Instances

24 Ontology = A Representation of Universals

25 Ontology = A representation of universals Each node of an ontology consists of: preferred term (aka term) term identifier (TUI, aka CUI) synonyms definition, glosses, comments

26 An ontology is a representation of universals We learn about universals in reality from looking at the results of scientific experiments in the form of scientific theories experiments relate to what is particular science describes what is general

siamese mammal cat organism substance universals animal frog instances

28 Domain =def a portion of reality that forms the subject- matter of a single science or technology or mode of study or administrative practice...; proteomics HIV epidemiology

29 Representation =def an image, idea, map, picture, name or description... of some entity or entities.

30 Ontologies are representational artifacts comparable to science texts and subject to the same sorts of constraints (including need for update)

31 Representational units =def terms, icons, alphanumeric identifiers... which refer, or are intended to refer, to entities and which are minimal (atoms)

32 Composite representation =def representation (1) built out of representational units which (2) form a structure that mirrors, or is intended to mirror, the entities in some domain

33 Analogue representations no representational units, no ‘atoms’

34 Periodic Table The Periodic Table

35 Ontologies are here

36 or here

37 ontologies represent general structures in reality (leg)

38 Ontologies do not represent concepts in people’s heads

39 They represent universals in reality

40 “leg” is not the name of a concept concepts do not stand in the part_of connectedness causes treats... relations used by biomedical ontologies

A515287DC3300 Dust Collector Fan B521683Gilmer Belt C521682Motor Drive Belt instances universals

42 Inventory vs. Catalog: Two kinds of representational artifact Databases represent instances Ontologies represent universals

43 How do we know which general terms designate universals? Roughly: terms used by scientists to designate entities about which we have a plurality of different kinds of testable proposition (cell, electron...)

44 Language has the power to create general terms which go beyond the domain of universals studied by science (sometimes language goes on holiday: cancelled haircut)

45 Problem: fiat demarcations male over 30 years of age with family history of diabetes abnormal curvature of spine participant in trial #2030

46 Problem: roles fist patient FDA-approved drug

47 Administrative ontologies often need to go beyond universals Fall on stairs or ladders in water transport injuring occupant of small boat, unpowered Railway accident involving collision with rolling stock and injuring pedal cyclist Nontraffic accident involving motor-driven snow vehicle injuring pedestrian

48 Class =def a maximal collection of particulars determined by a general term (‘cell’. ‘electron’ but also: ‘ ‘restaurant in Palo Alto’, ‘Italian’) the class A = the collection of all particulars x for which ‘x is A’ is true