Towards an Ontology of Philosophy
Barry Smithhttp://ontology.buffalo.edu/smith
APA, Vancouver, April 2, 2015
World’s most successful ontology
“Siri: An Ontology-driven Application for the
Masses”, A. Cheyer and T. Gruber (2010)
3
4Aristotle's Ontology of Constitutions
World’s oldest ontology
The problem these ontologies were built to solve
You have a lot of data / literature
The data is described in heterogeneous ways
You need to access and reason with the data in a uniform way
1. Create a controlled vocabulary of preferred labels for describing the data
2. Provide logical (computable) definitions
3. Tag (‘semantically enhance’) the data with ontology term URIs
Ontology-based methodology of information-driven science
Most successful example: the Gene Ontology
Old biology data
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GAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKLRSPNTPRRL
RKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVA
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WLGLESDYHCSFSSTRNAEDVDISRIVLYSYMFLNTAKGCLVEYA
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SATSELMANHSVQTGRNIYGVDFSLTSVSGTTATLLQERASERWI
QWLGLESDYHCSFSSTRNAEDV
New biology data
8
How to do biology across the genome?MKVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRKRSFEKVVIS
VMVGKNVKKFLTFVEDEPDFQGGPISKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLER
CHEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERL
KRDLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVC
KLRSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGIS
LLAFAGPQRNVYVDDTTRRIQLYTDYNKNGSSEPRLKTLDGLTSDYVFYFVTVLRQMQICALGNSYDAFNHDPWM
DVVGFEDPNQVTNRDISRIVLYSYMFLNTAKGCLVEYATFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSR
FETDLYESATSELMANHSVQTGRNIYGVDFSLTSVSGTTATLLQERASERWIQWLGLESDYHCSFSSTRNAEDVM
KVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRKRSFEKVVISV
MVGKNVKKFLTFVEDEPDFQGGPISKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLERC
HEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERLK
RDLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCK
LRSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLL
AFAGPQRNVYVDDTTRRIQLYTDYNKNGSSEPRLKTLDGLTSDYVFYFVTVLRQMQICALGNSYDAFNHDPWMD
VVGFEDPNQVTNRDISRIVLYSYMFLNTAKGCLVEYATFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSRF
ETDLYESATSELMANHSVQTGRNIYGVDFSLTSVSGTTATLLQERASERWIQWLGLESDYHCSFSSTRNAEDVMK
VSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRKRSFEKVVISVM
VGKNVKKFLTFVEDEPDFQGGPISKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLERCH
EIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERLKR
DLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKL
RSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLL
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VGKNVKKFLTFVEDEPDFQGGPISKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLERCH
EIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERLKR
DLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKL
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how to link the kinds of
phenomena represented here
10
or here
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or here
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MKVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRK
RSFEKVVISVMVGKNVKKFLTFVEDEPDFQGGPIPSKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSL
FYLNRGYYNELSFRVLERCHEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLL
HVDELSIFSAYQASLPGEKKVDTERLKRDLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNF
GAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKLRSPNTPRRLRKTLDAVKALLVSSCACTARDLD
IFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLLAFAGPQRNVYVDDTTRRIQLYTDY
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PPGYGKTELFHLPLIALASKGDVEYVSFLFVPYTVLLANCMIRLGRRGCLNVAPVRNFIEEGYDGVTDL
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to this?
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or this?
answer: by tagging data with terms from a
controlled vocabulary such as the Gene Ontology
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sphingolipid transporter activity
Holliday junction helicase complex
age-dependent behavioral decline
MouseEcotope GlyProt
DiabetInGene
GluChem
sphingolipid
transporter
activity
such tagging allows virtual integration of
heterogeneous databases
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MouseEcotope GlyProt
DiabetInGene
GluChem
Holliday junction
helicase complex
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fosters discoverability of information in
heterogeneous databases
Figure 3.
Shotton D, Portwin K, Klyne G, Miles A (2009) Adventures in Semantic Publishing: Exemplar Semantic Enhancements of a
Research Article. PLoS Comput Biol 5(4): e1000361. doi:10.1371/journal.pcbi.1000361
http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000361
… allows tagging of literature RB Reis, GS Ribeiro, RDM Felzemburgh, et al., Impact of Environ-
ment and Social Gradient n Leptospira Infection in Urban Slums
coordinated tagging of literature and data
Ontology journals
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Ontology portals
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Ontology portals
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Ontology authoring and editing
software
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http://protege.stanford.edu/
Ontologies in domains relevant to
philosophy and cognitive science
Mental Functioning Ontology (MFO)
Ontology for Biomedical Investigations
(OBI) – philosophy of science
Basic Formal Ontology – analytic
metaphysics
Information Artifact Ontology – linguistics,
aboutness
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http://bioportal.bioontology.org/ontologies/1666
Saturday, April 4, 2015 26The Emotion Ontology
with thanks to Janna Hastings, European Bioinformatics Institute
Example: Emotional personality trait
An emotional personality trait
=def. a stable enduring characteristic of a person
which involves a predisposition (i.e. a disposition which gives rise to an increased risk)
to undergo emotions of a particular sort, both occurrents and dispositions.
Saturday, April 4, 2015 27
all terms provided with definitions
Saturday, April 4, 201528
The Emotion Ontology
Types of emotion
Saturday, April 4, 2015 29
Types of emotions
Types of appraisal
Saturday, April 4, 2015 30
Types of appraisal
Types of feeling
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Types of Physiological Response to Emotion
built by downward population from MF (which is in turn
built from BFO)
MFO-EM affective representation is_a
MFO:cognitive representation
MFO:cognitive representation is_a
BFO:specifically dependent continuant33
BFO:Entity
BFO:Continuant BFO:Occurrent
BFO:ProcessBFO:Independent
Continuant
BFO
MFO
BFO:Dependent Continuant
Cognitive Representation
Affective Representation
Mental Process
Bodily ProcessBFO:Disposition
MFO-EM
Emotion Occurrent
Organism
Emotional Action Tendencies
Appraisal
Subjective Emotional Feeling
Physiological Response to
Emotion Process
inheres_in
is_output_of
Emotional Behavioural Process
Appraisal Process
has_part
agent_of
Emotion Ontology Top Level
http://www.ifomis.org/bfo/users35
BFO:Entity
BFO:Continuant BFO:Occurrent
BFO:ProcessBFO:Independent Continuant
BFO:Dependent Continuant
BFO:Disposition
To ensure the interoperability needed for data integration, ontologies must share a common,
stable domain-neutral top level
BFO = Basic Formal Ontology
Anatomy Ontology(FMA*, CARO)
Environment Ontology(EnvO)
Infectious Disease
Ontology(IDO*)
Biological Process
Ontology (GO*)
Cell Ontology
(CL)
CellularComponent
Ontology(FMA*, GO*) Phenotypic
QualityOntology
(PaTO)Subcellular Anatomy Ontology (SAO)
Sequence Ontology(SO*) Molecular
Function(GO*)Protein Ontology
(PRO*)
Extension Strategy + Modular Organization 36
top level
mid-level
domain level
Information Artifact Ontology
(IAO)
Ontology for Biomedical
Investigations(OBI)
Spatial Ontology(BSPO)
Basic Formal Ontology (BFO)
Example: biochemical basis of emotion
Emotions are effected in part by neurotransmitters such as dopamine, tryptophan
with thanks to Janna Hastings, European Bioinformatics InstituteSaturday, April 4, 2015 37
dopamine(CHEBI:25375)
molecular entity (CHEBI:25375)
biological role (CHEBI:24432)
neurotransmitter(CHEBI:25512)
has role
neurotransmitter receptor activity
(GO:0030594)
Molecular function (GO:0003674)
realized in
happiness(MFOEM:42)
part of
emotion(MFOEM:1)
subtype
Is-a overloading
Toronto is a city
capital city is a city
It is a disgrace to the human race that it has chosen to employ the same word ‘is’ for these two entirely different ideas (predication and identity) – a disgrace which a symbolic logic language of course remedies. (Russell 1919:172)
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Three kinds of Relations
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Relations between types (or ‘classes’)
is_a (= is a subtype of)
Relations between instances (or ‘individuals’)
author_of, teacher_of
Relations connecting instances to types
is_an_expert_on
is_allergic_to
is_an_instance_of
An ontology is a representation of types of entities and of the relations between
them
The result of applying an ontology to a body of data about instances is a
knowledge base
Gene Ontology (GO) vs. Gene Ontology Annotation Database (GOA)
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Manual ontology building vs. NLP
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Natural language processing and machine reasoning more generally are making progress
But (so far) only ontologies built by manual experts have proven value
Ontology of Philosophy
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- text vs. structured data
- conflicts of interpretation affecting the goals of ontology itself
- no neutral perspective
- for GO and other scientific ontologies science itself provides a neutral perspective
- what can provide the neutral perspective here?
Examples of philosophical knowledge bases
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1. Low hanging fruit, authoritative data
The Philosophy Family TreeAn academic genealogy of philosophers
Only one type of link: is_Doktorvater_of
• as wiki
• as indented list
• as linked graph
140,000 entries
The largest (and longest) chain of links begins with Leibniz
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as wiki (still working)
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http://philosophyfamilytree.wikispaces.com
46/http://ontology.buffalo.edu/philosophome
as indented list
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http://ontology.buffalo.edu/philosophome 48
as linked graph
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50/
51/
52/
Examples of philosophical knowledge bases
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2. Not low hanging fruit
With thanks to Alois Pichler
(Wittgenstein Archive, Bremen)
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Wittgenstein Ontology
– http://wab.uib.no/cost-a32_philospace/wittgenstein.owl
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Upper Level
– http://wab.uib.no/cost-a32_philospace/wittgenstein.owl
Top-Level: Source
Alois Pichler (WAB). CCPL BY-
NC-SA
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Top-Level: Subject
Alois Pichler (WAB). CCPL BY-
NC-SA
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Subject branch• Place
– Instances: Skjolden; Cambridge
• Date– Instances: 11 May 1936
• Issue – Instances: philosophy; logical analysis
• Point – Example of instance: Logical analysis is essential to philosophy
• Field (a field of philosophical discussion) – Has subclasses:
• Epistemology
– Scepticism
» Rule-FollowingScepticism
• Perspective – Has subclasses: APichler_Course_TLP; APichler_Course_PI
– Instances: contradiction; state_of_affairs …
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Examples of Relations
isArguedForIn– [Philosophical analysis is essential to philosophy]
isArguedForIn [W-TLP]
isPublishedInWork− [Ms-114,48v[5]et49r[1]] isPublishedIn [W-
PG1969:PartI:II:sect19]
isReferredToIn– [Augustinus, Aurelius: Confessiones]
isReferredToIn [Ms-114,48v[5]et49r[1]]
Alois Pichler (WAB). CCPL BY-
NC-SA
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Interlinked browsing of texts (data) and
relations (metadata)
Alois Pichler (WAB). CCPL BY-
NC-SA
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Checking Wittgenstein’s references to
Augustine
Alois Pichler (WAB). CCPL BY-
NC-SA
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Checking PG 1969, Part II, §17, and
focusing on one of its sources
63http://philosophyideas.com/
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No controlled vocabulary
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Mixes instances with types
pi
67/http://philpapers.org/
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Simple ontological traffic rules
1. avoid is_a overloading
2. use exclusively singular nouns and noun phrases
3. do not suppose that A is a kind of A & B
4. true path rule (asserting A is_a B is to assert something that is grammatical, and universally true)
Principal lesson of scientific ontologies: reasoning power depends on rule 4
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Breaking traffic rules
• moral rationalism is_a the a priori
• the a priori is_a epistemological sources
• epistemological sources is_a epistemology
• epistemology is_a metaphysics and epistemology
The first generation of scientific ontologies broke these rules too. But they have learned since then to do it right.
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Another ontological traffic rule
• Do not populate an ontology through multiple unmonitored human sources
• Do not create an ontology on the basis of a single source of data
– the principal value of a well-built ontology is in its secondary uses, uses which were not anticipated when the ontology was first developed
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PhilOntoAn example of an Ontology of
Philosophy that tries to do it right
http://ontology.buffalo.edu/philosophome/pdcphilontology-v1.owl
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philosopher
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instance_of
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Kinds and subkinds Instances
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philosopher
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instance_of
Subkinds of philosopher
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Features of PhilOnto
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PRO• Built on the basis of tested best practice
principles for ontology development• Built to be extendible through an
evolutionary process• Built manually, on the basis of careful
thinking about structure and definitions
Features of PhilOnto
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CON• Still a fragment
Clear distinction in InPhO between is_a and instance_of
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ethicist is_a [type of] philosopher
Carnap instance_of philosopher
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85
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InPhO Top-Level in Protégé
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no definitions
InPhO Top-Level in Protégé
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only one branch is populated
InPhO second-level under ‘Idea’
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“ethics is_a Idea” seems not to conform to the expectations of statistically typical end-users
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Third-level under ‘ethics’ seems quite coherent
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change is_a metaphysicsmetaphysics is_a Idea
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is_a and subclass
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change is_a metaphysicsmetaphysics is_a Idea
are not helped if we read ‘subclass of’ in place of ‘is_a’
since ‘subclass of’ is to be understood set-theoretically
what would every member of the class change is a member of the class metaphysics mean?
‘instances’ in InPhO
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What does ‘instance’ mean?
Colin: [it is a] kind of meaning in use, i.e., a specification of how instances are assigned and a contextual interpretation, supplied by end users, in which it makes sense to say that ideas about Japanese Zen Buddhist Philosophy are instances of ideas about Japanese Philosophy more generally. It is this latter, more pragmatist approach to meaning that I prefer …
6 Put more precisely, we take a computational ontology to be a directed acyclic graph where nodes represent concepts and the links between concepts represent the taxonomic “isa” relation … everything that “is a” instance of Red Wine “is a” instance of Wine …
everything that “is a” instance of Racism “is a” instance of African and African-American philosophy
Further mysteries
How is it decided what gets listed under ‘Instances’ of feminist philosophy and what gets listed under ‘Related Terms’.
Is there any right and wrong for any of this?
And still further mysteries
Eh?
Features of InPhO
PRO
• Impressive tooling
• Authoritative data sources such as the Philosophy Family Tree being used to populate the InPhOknowledge base
• Secondary uses being explored (e.g. as part of a robotics application to try to detect contexts in which there are ethically significant issues in play)
Features of InPhO
CON
• full of mysteries
• does not follow established best practices
• no concern for interoperability with other ontologies
• no concern for correctness of is_a hierarchies and
• no concern for logical definitions (as far as I can see)
• thus many opportunities for reasoning with the ontology are foreclosed
Challenges for InPhO
• OWL provides reasoners to check consistency• Were inconsistencies ever found when building InPhO?
• One secondary use for ontologies is to detect errors in databases
• Can InPhO be used to detect errors in the SEP?
• One secondary use for ontologies is to enhance existing classification and tagging systems
• Can InPhO be used to improve the classifications in PhilPapers?
• by finding redundancies?• by aiding more coherent classification by identifying subsumption
relations?• via semantic enhancement?