EPFL Lausanne January 30 2017 Niagara Falls 2 Canadian Falls 3 4 American Falls 5 Niagara River 6 beau fleuve Buffalo 7 University at Buffalo 8 9 10 How Siri Works Interview with Tom Gruber CTO of SIRI ID: 933866
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Slide1
Building Ontologies
Barry Smith
EPFL, Lausanne
January 30, 2017
Slide2Niagara Falls
2
Slide3Canadian Falls
3
Slide44
American Falls
Slide55
Niagara River
Slide66
“beau
fleuve
”
Slide7Buffalo
7
Slide8University at Buffalo
8
Slide99
Slide1010
Slide11How Siri Works – Interview with Tom Gruber, CTO of SIRI
January 26th, 2010
Nova Spivack
: Siri seems smart, at least about the kinds of tasks it was designed for. How is the knowledge represented in Siri – is it an ontology or something else?Tom Gruber: Siri’s knowledge is represented in a unified modeling system that combines ontologies, inference networks, pattern matching agents, dictionaries, and dialog models. … Siri can look at what it knows and think about similarities and generalizations at a semantic level.
11
Slide12Aristotle (384 –
322 BC): First ontologist
Metaphysics
– the lectures he gave after the physics
CategoriesHistory of Animals, Generation of Animals, and Parts of Animals– earliest empirical biology
Constitution of Athens
– part of a (lost) database of 158 constitutions
12
Slide1313
Aristotle's Ontology of Constitutions
Slide14Hierarchy from
Porphyry’s Introduction to Aristotle’s
Categories
14
Slide1515
Slide16Hierarchy from Linnaeus
16
Slide17Rediscovery of Ontology 1:
Quine
1950s: Quine’s
‘ontological commitment’
What would have to exist in the world for this scientific theory to be true?
Electrons, energy, time, matter, …
Colors, thoughts, beliefs, emotions, …
17
Slide18Rediscovery of Ontology 1:
AI and Robotics
1970s:
AI, Robotics: John McCarthy, Pat Hayes
What would a robot have to believe / know in order to simulate human common sense (for example as involved in buying a salad in a restaurant)?
Can we
axiomatize
human common sense?
Can we create a qualitative physics?
18
Slide19Rediscovery of Ontology
2
:
Semantic Web
1980s: KIF: Knowledge Interchange Format, Tom Gruber … Watson … SIRIKnowledge representation and reasoningDescription logicsDAML (DARPA Agent Markup Language)RDF, RDF(S), OWL …
19
Slide20Rediscovery of Ontology 3:
Biology
1998– genomes for
c.
elegans, fly, human, mouse …
1998– Gene Ontology (GO)
2000– Cell, Protein, Sequence, Anatomy, Disease ontologies …
2004– Basic Formal Ontology
20
Slide21Old biology data
21
/
Slide22MKVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRKRSFEKVVISVMVGKNVKKFLTFVEDEPDFQGGPISKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLERCHEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERLKRDLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKLRSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLLAFAGPQRNVYVDDTTRRIQLYTDYNKNGSSEPRLKTLDGLTSDYVFYFVTVLRQMQICALGNSYDAFNHDPWMDVVGFEDPNQVTNRDISRIVLYSYMFLNTAKGCLVEYATFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSRFETDLYESATSELMANHSVQTGRNIYGVDFSLTSVSGTTATLLQERASERWIQWLGLESDYHCSFSSTRNAEDVDISRIVLYSYMFLNTAKGCLVEYATFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSRFETDLYESATSELMANHSVQTGRNIYGVDFSLTSVSGTTATLLQERASERWIQWLGLESDYHCSFSSTRNAEDV
New biology data
22
Slide23How to do biology across the genome?
MKVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRKRSFEKVVISVMVGKNVKKFLTFVEDEPDFQGGPISKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLERCHEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERLKRDLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKLRSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLLAFAGPQRNVYVDDTTRRIQLYTDYNKNGSSEPRLKTLDGLTSDYVFYFVTVLRQMQICALGNSYDAFNHDPWMDVVGFEDPNQVTNRDISRIVLYSYMFLNTAKGCLVEYATFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSRFETDLYESATSELMANHSVQTGRNIYGVDFSLTSVSGTTATLLQERASERWIQWLGLESDYHCSFSSTRNAEDVMKVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRKRSFEKVVISVMVGKNVKKFLTFVEDEPDFQGGPISKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLERCHEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERLKRDLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKLRSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLLAFAGPQRNVYVDDTTRRIQLYTDYNKNGSSEPRLKTLDGLTSDYVFYFVTVLRQMQICALGNSYDAFNHDPWMDVVGFEDPNQVTNRDISRIVLYSYMFLNTAKGCLVEYATFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSRFETDLYESATSELMANHSVQTGRNIYGVDFSLTSVSGTTATLLQERASERWIQWLGLESDYHCSFSSTRNAEDVMKVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRKRSFEKVVISVMVGKNVKKFLTFVEDEPDFQGGPISKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLERCHEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERLKRDLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKLRSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLLAFAGPQRNVYVDDTTRRIQLYTDYNKNGSSEPRLKTLDGLTSDYVFYFVTVLRQMQICALGNSYDAFNHDPWMDVVGFEDPNQVTNRDISRIVLYSYMFLNTAKGCLVEYATFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSRFETDLYESATSELMANHSVQTGRNIYGVDFSLTSVSGTTATLLQERASERWIQWLGLESDYHCSFSSTRNAEDVMKVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRKRSFEKVVISVMVGKNVKKFLTFVEDEPDFQGGPISKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLERCHEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERLKRDLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKLRSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLLAFAGPQRNVYVDDTTRRIQLYTDYNKNGSSEPRLKTLDGLTSDYVFYFVTVLRQMQICALGNSYDAFNHDPWMDVVGFEDPNQVTNRDISRIVLYSYMFLNTAKGCLVEYATFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSRFETDLYESATSELMANHSVQTGRNIYGVDFSLTSVSGTTATLLQERASERWIQWLGLESDYHCSFSSTRNAEDV
23
Slide24how to link the kinds of phenomena represented here
24
Slide25MKVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRKRSFEKVVISVMVGKNVKKFLTFVEDEPDFQGGPIPSKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLERCHEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERLKRDLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKLRSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLLAFAGPQRNVYVDDTTRRIQLYTDYNKNGSSEPRLKTLDGLTSDYVFYFVTVLRQMQICALGNSYDAFNHDPWMDVVGFEDPNQVTNRDISRIVLYSYMFLNTAKGCLVEYATFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSRFETDLYESATSELMANHSVQTGRNIYGVDSFSLTSVSGTTATLLQERASERWIQWLGLESDYHCSFSSTRNAEDVVAGEAASSNHHQKISRVTRKRPREPKSTNDILVAGQKLFGSSFEFRDLHQLRLCYEIYMADTPSVAVQAPPGYGKTELFHLPLIALASKGDVEYVSFLFVPYTVLLANCMIRLGRRGCLNVAPVRNFIEEGYDGVTDLYVGIYDDLASTNFTDRIAAWENIVECTFRTNNVKLGYLIVDEFHNFETEVYRQSQFGGITNLDFDAFEKAIFLSGTAPEAVADAALQRIGLTGLAKKSMDINELKRSEDLSRGLSSYPTRMFNLIKEKSEVPLGHVHKIRKKVESQPEEALKLLLALFESEPESKAIVVASTTNEVEELACSWRKYFRVVWIHGKLGAAEKVSRTKEFVTDGSMQVLIGTKLVTEGIDIKQLMMVIMLDNRLNIIELIQGVGRLRDGGLCYLLSRKNSWAARNRKGELPPKEGCITEQVREFYGLESKKGKKGQHVGCCGSRTDLSADTVELIERMDRLAEKQATASMSIVALPSSFQESNSSDRYRKYCSSDEDSNTCIHGSANASTNASTNAITTASTNVRTNATTNASTNATTNASTNASTNATTNASTNATTNSSTNATTTASTNVRTSATTTASINVRTSATTTESTNSSTNATTTESTNSSTNATTTESTNSNTSATTTASINVRTSATTTESTNSSTSATTTASINVRTSATTTKSINSSTNATTTESTNSNTNATTTESTNSSTNATTTESTNSSTNATTTESTNSNTSAATTESTNSNTSATTTESTNASAKEDANKDGNAEDNRFHPVTDINKESYKRKGSQMVLLERKKLKAQFPNTSENMNVLQFLGFRSDEIKHLFLYGIDIYFCPEGVFTQYGLCKGCQKMFELCVCWAGQKVSYRRIAWEALAVERMLRNDEEYKEYLEDIEPYHGDPVGYLKYFSVKRREIYSQIQRNYAWYLAITRRRETISVLDSTRGKQGSQVFRMSGRQIKELYFKVWSNLRESKTEVLQYFLNWDEKKCQEEWEAKDDTVVVEALEKGGVFQRLRSMTSAGLQGPQYVKLQFSRHHRQLRSRYELSLGMHLRDQIALGVTPSKVPHWTAFLSMLIGLFYNKTFRQKLEYLLEQISEVWLLPHWLDLANVEVLAADDTRVPLYMLMVAVHKELDSDDVPDGRFDILLCRDSSREVGELIGLFYNKTFRQKLEYLLEQISEVWLLPHWLDLANVEVLAADDTRVPLYMLMVAVHKELDSDDVPDGRFDILLCRDSSREVGELIGLFYNKTFRQKLEYLLEQISEVWLLPHWLDLANVEVLAADDTRVPLYMLMVAVHKELDSDDVPDGRFDILLCRDSSREVGE
25
to data which look
like this?
Slide26Answer
Create an ontology: a controlled logically structured consensus classification of the types of entities in the relevant domain
All scientists in the domain use the same ontology aggressively to tag their data
26
Slide2727
The Gene Ontology
– a species-neutral vocabulary for describing attributes of gene and protein sequences
Slide2828
Nodes in the graph are terms
Edges are relations such as
subtype (is-a)
part-of
regulates …
Each term in the ontology has a logical definition
Slide29GO provides a controlled system of terms for use in tagging experimental data
multi-species, multi-disciplinary, open source
compare: use of kilograms, meters, seconds … in formulating experimental results
29
Slide30GO coverage
generic biological entities of three sorts:
cellular components
molecular functions
biological processes GO does not provide representations of diseases, symptoms, anatomy, pathways, …
30
Slide31RELATION
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
(GO)
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
(GO)
Molecular Process
(GO)
Original OBO Foundry ontologies
(Gene Ontology in yellow)
31
Slide3232
Slide33Patient Demographics
Phenotype
(Disease, …)
Disease processes
Data
about all of these things
including
image
data …
Algorithms, software,
protocols, …
Instruments, Biomaterials,
Functions
Parameters, Assay types, Statistics
…
Anatomy
Histology
Genotype (GO)
Biological processes (GO)
Chemistry
Independent Continuant
(~Thing))
Dependent Continuant
(~Attribute)
Occurrent
(~Process)
IAO
Information Artifact Ontology
OBI
Ontology for Biomedical Investigations
Basic Formal Ontology (BFO)
33
Slide34Figure 2. Core terms of the Biological Collections Ontology (BCO) and their relations to upper ontologies.
Walls RL, Deck J, Guralnick R, Baskauf S, Beaman R, et al. (2014) Semantics in Support of Biodiversity Knowledge Discovery: An Introduction to the Biological Collections Ontology and Related Ontologies. PLoS ONE 9(3): e89606. doi:10.1371/journal.pone.0089606
http://journals.plos.org/plosone/article?id=info:doi/10.1371/journal.pone.0089606
Biological Collections Ontology (BCO)
BFO
OBI
BFO
OBI
34
Slide35part_of
is_a
35
GO’s three sub-ontologies
is_a
cellular component
molecular function
biological process
Slide36BFO generalizes GO
Continuant
Occurrent
Independent
Continuant
Dependent
Continuant
cellular component
biological process
molecular function
Slide3737
BFO: Continuant Ontology
Slide3838
Slide39Hole
Setting
Slide4040
Slide41RELATION
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
(GO)
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
(GO)
Molecular Process
(GO)
Original OBO Foundry ontologies
(Gene Ontology in yellow)
41
Slide42CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
Organ
Function
(FMP, CPRO)
Phenotypic Quality
(
PaTO
)
Organism-Level Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
(GO)
Cellular Process
(GO)
MOLECULE
Molecule
(ChEBI, SO,
RNAO, PRO)
Molecular Function
(GO)
Molecular Process
(GO)
rationale of OBO Foundry coverage
GRANULARITY
RELATION TO TIME
Slide4343
https://mitpress.mit.edu/building-ontologies
Slide44DOLCE, SUMO, BFO
DOLCE: Domain Ontology for Linguistic and Cognitive Engineering
SUMO: Suggested Upper Merged Ontology
BFO: Basic Formal Ontology
44
Slide4545
Slide46NEW WORK ITEM PROPOSAL
Information Terminology / Ontologies / Top-Level Ontologies
Part 1: Describes general framework for ontologies and ontology suites such as OBO Foundry, their applications, governance, management, version control, role of terms, relations, definitions, axiomatizations
Part 2: Describes BFO, demonstrates conformance to Part 1
46
Slide47BFO-based approach extended into other biological domains
NIF Standard
Neuroscience Information Framework
IDO Core
/ IDO extensions
Infectious
Disease Ontology Suite
CROPS
Common Reference Ontologies
for Plants
Slide48… and now being extended to the ontology of social reality
UNEP SDG Ontology Framework
Unite
d Nations Environment
Programme Sustainable Development Goals Interface Ontology
USGS
National Map
United States Geological
Survey
TRIP Ontologies
Federal Highway Administration (FHWA) Transportation Research Informatics Platform (TRIP)
Common Core Ontologies (CCO)
US
Army / I2WD and ARL,
IARPA, JIDO, ONR, AFRL,
IC, …
48
Slide4949
http://pre-uneplive.unep.org/portal#ontologies
Slide50The general approach:
Semantic enhancement
50
enhance data through annotation with ontologies
to make data discoverable and retrievable even by those not involved in their creationsupport integration of data deriving from heterogeneous sources allow unanticipated secondary uses
Slide51Ontology and Interoperability: Definitions
Ontology
=def. a representation of the types of entities in a given domain and of the relations between them.
Controlled vocabulary
= def. the terminological part of an ontology, including definitions of all terms in both a human and a computer readable form. Interoperability =def. The ability of systems, units, or forces to provide data, information, materiel, and services to, and accept the same from, other systems, units, or forces, and to use the data, information, materiel, and services exchanged to enable them to operate effectively together. (DoD Instruction 8330.01)Ontologies support interoperability by providing a common controlled vocabulary and common definitions to enable all units, forces and IT systems to speak the same language.
51
Slide5252
https://mitpress.mit.edu/building-ontologies
Slide53Ontology
=def. a representation of the
types
of entities in a given domain and of the
relations between them. types = universals, classes, kinds, categories – roughly that which is general in reality, including
types of aircraft
types of aircraft part
types of aircraft maintenance process
as contrasted with individuals, particulars, instances of these types – this specific aircraft, that specific aircraft part
relations:
is a subtype of
(
is_a
),
is part of
,
has part
,
…
53
Slide54Ontologies represent types of entities
physical entities: planets, aircraft, organisms, lives, …
information entities: databases, words
cognitive entities: ideas, beliefs, speech acts
Rules:don’t confuse entities with the words we use to describe themdon’t confuse entities with our knowledge about entitiesdon’t confuse types of entities with ‘concepts’ in our heads
54
Slide55For problems such as this, too much ontology is a bad thing
The original idea behind ontology-based technology was to break down silos via common controlled vocabularies for the tagging of data
The very success of this approach led to the creation of ever new controlled vocabularies –
semantic silos
– as ever more ontologies were created in ad hoc waysEvery organization and sub-organization wanted to have its own “ontology” 55
Slide56Linked Open Data (chaos rules)
Linking Open Data cloud diagram 2014, by Max
Schmachtenberg
, Christian
Bizer
, Anja
Jentzsch
and Richard
Cyganiak
. http://lod-cloud.net/
56
Slide57Building Ontologies 2
Barry Smith
EPFL, Lausanne
January 30, 2017
Slide58Anatomy Ontology
(FMA*, CARO)
Disease Ontology (OGMS, IDO, HDO, HPO)
Information Artifact Ontology (IAO)
Database, Document,
Publication, Citation
…
Biological Process Ontology (GO)
Ontology of Biomedical Invesigations (OBI)
Experiment,
Assay,
Measurement
Process,
…
Cell Ontology
(CL)
Subcellular Anatomy Ontology (SAO)
Phenotypic Quality
Ontology
(PATO)
Sequence Ontology
(SO)
Molecular Function Ontology
(GO)
Protein Ontology
(PRO)
Basic
Formal Ontology (BFO)
58
Fundamental idea behind BFO:
to constrain ontology development
Slide59Top level ontology defined by GO
Continuant
Independent
Continuant
thing
Dependent
Continuant
attribute
59
p
rocess
Occurrent
Slide60BFO and the 3 Gene Ontologies (GO)
Continuant
Occurrent
Independent
Continuant
Dependent
Continuant
cell component
biological process
molecular function
Slide61Continuant
thing, quality …
Occurrent
process, event
61
BFO’s Fundamental Dichotomy
Continuants can change over time
while preserving their identity
Occurrents
are
changes
Slide6262
An application of Basic Formal Ontology
to the Ontology of Services and Commodities
Slide63Application of BFO to the ontology of commodities and services
Commodities are things (including software) which survive their act of creation, can be transported, stored, rented, …
Services are processes (where production and consumption always coincide)
Utilities involve both a commodity side (you rent e.g. the phone network) and a service side (you use the phone network when you make a call)
Car dealerships sell cars, which are commodities, but selling is a service
Slide64Continuant
c
ommodity
…
Occurrent
service …
64
BFO’s Fundamental Dichotomy
both commodities and services are entities with economic value
Slide65Basic Formal Ontology
continuants
continue to exist
through time
processes occur in time, cycling through a succession of phases (beginning middle end)
Slide6666
Is music a commodity or a service?
Consumer’s perspective
Producer’s perspective
Taxation authority’s perspective
What is a music CD, which (in olden times) people used to buy in stores?
Slide6767
Is a music CD a commodity? (because it is a physical object)
Or is it a
service
? (because it is a musical performance?)
Slide6868
A similar problem with outsourcing
Many manufacturing companies used to do everything in-house. Their jobs were counted as manufacturing (commodities)
Now many companies outsource as much as possible: janitors, accounting, data processing, sales, human resources, etc.
Now, since the same jobs are part of an out-sourcing firm, they are considered service jobs
Are people right to say that Western economies are becoming service economies?
Slide6969
Definition
Service = an economic good which is a process and which is such that production and consumption coincide
Examples
Haircutting
nursing
prostitution
teaching
transport
Slide7070
‘splintered’ (‘disembodied’) services a
CDs
books, newspapers
painting
advertising
television, telephone
software on the net
are classified as services even though their production and consumption do not coincide
Slide7171
Two Kinds of Commodities
consumable (bananas)
non-consumables (roads, telephone lines)
The latter
afford
services
as an ocean affords swimming
Slide7272
Are telecommunications
commodities
?
Do we rent the telephone system for 5 seconds?
Do we rent
services
(like buying a hairdresser’s services for 5 minutes)?
Are telecommunications like water or electricity? = Commodities which come down pipes
Slide7373
Television and telecommunications
are similar ontologically: each has two components: the network and the utilization of the network
= continuants plus occurrents
Slide7474
From the consumer’s perspective however
Television is a service industry:
We watch television in order to enjoy the services of the actors.
The network and delivery mechanism are secondary.
Not so for telephone ‘service’:
telecommunications is an industry
analogous to car rental
.
We want to use the actual physical mechanical network object.
Slide75Is car rental a service or a commodity?
Slide7676
Car rental is like home rental
it is the purchase
of an object
(a commodity) for a certain time.
Slide7777
For services
production and consumption coincide both spatially and temporally
Therefore
–services are characterized by the fact that
renting is impossible
.
Services can only be
purchased
.
Slide7878
Is your telephone provider providing a service or a commodity
The telecommunication
system
, like the phone
itself, is a commodity, which we rent in just the same way that we rent a free-standing public telephone in an airport
You still pay for your telephone connection when no one is using the line
Slide7979
Telephones
are physical goods. They have traditionally been regarded as services because they afford usage (they have the dispositional property of providing services).
The traditional categorization is erroneous, because this dispositional property applies no less to cars, pianos, rice.
Slide80Basic Formal Ontology
Continuant
Occurrent
(Process, Event)
Independent
Continuant
Dependent
Continuant
https://github.com/BFO-ontology
80
Slide81Continuant
Occurrent
process, event
Independent
Continuant
thing
Dependent
Continuant
quality
.... ..... .......
quality depends
on bearer
Slide82Continuant
Occurrent
process, event
Independent
Continuant
thing
Dependent
Continuant
quality, …
.... ..... .......
event depends
on participant
Slide83Occurrents depend on participants
instances
15 May bombing
5 April insurgency attack
occurrent types
bombing
attack
participant types
explosive device
terrorist group
Slide84specifically_depends_on
Continuant
Occurrent
process, event
Independent
Continuant
thing
Dependent
Continuant
quality
.... ..... .......
m
ass of phone depends on phone
84
Slide85process depends_on participant
Continuant
Occurrent
Independent
Continuant
participant
Dependent
Continuant
disposition
.... ..... .......
85
Process of
realization
Slide86Continuant
Occurrent
Independent
Continuant
participant
Dependent
Continuant
disposition
86
Process of
realization
example: disposition of phone to use up battery
Slide87skills, talent, knowledge are dispositions of people
Continuant
Occurrent
Independent
Continuant
participant
Dependent
Continuant
disposition
87
Process of
realization
.... ..... .......
87
Slide88a function is a special kind of disposition (it is designed …)
Continuant
Occurrent
Independent
Continuant
participant
Dependent
Continuant
function
Process of
realization
example: function
of phone to transmit signal
88
Slide89a disposition is always a matter of the physical make-up of its bearer
Continuant
Occurrent
Independent
Continuant
participant
Dependent
Continuant
disposition
Process of
realization
example: your d
isposition
to get tired
89
Slide90a role is a matter not of physics but of social ascription; it is always optional
Continuant
Occurrent
Independent
Continuant
participant
Dependent
Continuant
disposition
Process of
realization
example: the role of president, professor, pet …
90
Slide91Four Fundamental Dichotomies
Continuant vs. occurrent
Dependent vs. independent
Role vs. disposition
Type vs. instance
91
Slide92Continuant
Independent
Continuant
Specifically
Dependent
Continuant
..... .....
Quality
Realizable
Dependent
Continuant
(
function
,
role
,
disposition
)
92
Slide9393
more examples of BFO continuant entities
qualities
the pattern of hair on your head that is an outcome of the haircutting process
the pattern of connectedness of the plumbing system in your house that is an outcome of the plumbing process
dispositions
your knowledge of Greek that is the outcome of a teaching process
Slide94Continuant
Independent
Continuant
Specifically
Dependent
Continuant
Non-realizable
Dependent
Continuant
(
quality
)
Realizable
Dependent
Continuant
(
function
,
role
,
disposition
)
94
Material
Entity
Immaterial
Entity
Slide95Independent
Continuant
95
Material
Entity
Immaterial
Entity
Site,
setting
Generically
Dependent
Continuant
Information
Artifact
Slide9696
An ontology of marketing
must include
Continuants
(manufactured goods, including software)
Processes (services, of selling ...)
Settings (contexts in which selling takes place ...)
See: http://ontology.buffalo.edu/smith/articles/napflion.pdf
Slide9797
The value of a service is dependent upon the setting in which it exists at the moment of delivery.
This is not true of the value of a commodity
Slide9898
Examples of settings
of purchase
of delivery (for commodities)
of use (for commodities)
of delivery (for services)
of assessment for tax purposes (of commodities and services ...)
Slide9999
Settings
When you buy a service you also buy a delivery setting.
And the delivery setting has the same temporal extent as the service itself.
The delivery setting for commodities is transient. They bring you the car and leave.
Slide100100
The Ontology of Real Estate
The value of a building is dependent on the setting in which it exists
Can you buy a setting?
When you buy real estate, you buy a house and you also buy its setting (which was there before the house was built)
http://ontology.buffalo.edu/smith/articles/lz.htm
Slide101Foundations of a CAD Ontology
101
Slide102102
Slide103103
Slide104Foundations of a CAD Ontology
104
Slide105Hole
Setting
Slide106The Airbus A380 disaster of 2004
106
Slide107Hole
Setting
Slide108108
Slide109109
Slide110Digital Thread/Digital Twin initiative
Goal: To address the stovepipe problems resulting from the fact that
airforce
bases import data, models, and information from a huge variety of different sources, all of which use their own local terminologies and data models
110
Slide111RELATION
TO TIME
MULTI-SCALE
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
AIRCRAFT
Fleet Ontology
Design Specification Attribute
Ontology
Air Operations Ontology
Aircraft Ontology
AIRCRAFT COMPONENT
Aircraft Subsystem Ontologies:
Airfame
, Propulsion, Energy Storage …
System Function Ontology
Realized Attribute
Ontology
Air Sustainment Ontology
Aircraft Component
Ontology
Sensor Ontology
Structural Mechanics
Ontology
Fault
Ontology
Test Ontology
MOLECULE
Materials Ontology
Materials Attribute Ontology
Materials
Process
Ontology
111
Draft of a set of ontology modules for air force logistics
Slide112All ontologies descend from BFO + CCO
top level
mid-level
domain level
Common Core Ontologies (CCO)
Basic Formal Ontology (BFO)
Fleet Ontology
Design Specification Attribute
Ontology
Air Operations / Mission Ontology
Aircraft Ontology
Aircraft Subsystem Ontologies:
Airfame, Propulsion, Energy Storage …
System Function Ontology
Realized Attribute
Ontology
Air Sustainment Ontology
Aircraft Component
Ontology
Sensor Ontology
Structural Mechanics
Ontology
Fault
Ontology
Test Ontology
Materials Ontology
Materials Attribute Ontology
Materials
Process
Ontology
112
/24
Slide113http://www.ritsumei.ac.jp/~y-kita/pub/kita-dx99.pdf
113
Slide114Types of fault
Y. Kitamura and R. Mizoguchi, “An Ontological Analysis of Fault Process and Category of Faults”, Tenth International Workshop on Principles of Diagnosis (DX-1999), 118-128.
model
114
Slide115115
Slide116http://www.tinker.af.mil/shared/media/document/AFD-140606-042.pdf
116
Slide117http://www.irss.ca/development/documents/CODES%20&%20STANDARDS_02-28-08/ASME%20V%201998/ASME%20V%20Art%2030%20Terms.pdf
117
Slide118Glossary
ACTIVITY
=def. a measure of how radioactive a particular radioisotope is. Activity is calculated by the number of atoms disintegrating per unit of time. Its unit of measurement is the curie. See SPECIFIC ACTIVITY.
SPECIFIC ACTIVITY
(RT) =def. a measure of the activity per unit weight generally measured in curies per gram (SI) dis/sec-dm
118
Slide119Glossary
‘activity’ is used 88 times in this document
to mean
maintenance activity
engineering activityinspection activityprocuring activityetc. etc.
119
Slide120Glossary
VISCOSITY:
Quality, state or degree of being viscous. That property of a body by virtue of which, when flow occurs inside it, forces arise in such a direction as to opposite the flow.
VISCOSITY:
A measurement of a liquids resistance to change of shape or flow. Also referred to as flow resistance.120
Slide121Common Core Ontologies
Basic Formal Ontology (BFO)
Extended Relation Ontology
Time Ontology
Quality Ontology
Information Entity Ontology
Geospatial Ontology
Event Ontology
Artifact Ontology
Agent Ontology
Occupation Ontology
Units of Measure Ontology
Upper Ontology:
Common Core Ontology:
Domain Ontology:
Sensor Ontology
Agent Information Ontology
Atmospheric Conditions Ontology
Aircraft Maintenance Ontology
Flight Operation Ontology
Aircraft Ontology
Aircraft Engine Ontology
Aircraft Testing Ontology
Aircraft Production Ontology
DT/
DTw
TBD Ontology:
121
with thanks to Ron
Rudnicki
Slide122Modularity as a Development Guideline for Common Core Ontologies
Ontologies are distinguished by levels of
generality
Content and structure is inherited from higher levels
Upper Ontologies
Describe the Structure of the World
Mid-Level Ontologies
Add General Content to the Structure
Domain Level Ontologies
Add Content Relevant to a Community
Upper and mid-level ontologies are stable and of manageable scale
122
with thanks to Ron
Rudnicki
Slide123Modularity as a Development Guideline
The ontologies are distinguished by the interrelations among objects and processes as specified by the upper ontology: Basic Formal Ontology (BFO)
Attribute
Process
Site
Temporal Region
Physical Object
has
participates in
occurs at
occurs on
Site
contained in
123
with thanks to Ron
Rudnicki
Slide124Draft of a Generic PLC Ontology based on BFO
Barry Smith (NCOR, Buffalo) and Dimitris
Kiritsis
(EPFL, Lausanne)
September 29, 2016
124
Slide125Top Level organization of BFO
125
Process
Information
Entity
Material
Entity
Attribute
BFO:Continuant
BFO:Occurrent
Slide126Four major top-level categories in BFO
126
Process
Information
Entity
Material
Entity
Attribute
BFO:Continuant
BFO:Occurrent
Slide127Four major top-level categories in BFO
127
Process
Information
Entity
Material
Entity
Attribute
Crack
Fault
Discontinuity
Status
State
Productivity
Quality
Function
BFO:Continuant
BFO:Occurrent
Slide128Top Level organization of BFO
128
Process
Information Entity
Material
Entity
Attribute
BFO: Continuant
BFO: Occurrent
Temporal Region
occupies
Spatial Region
occupies
Slide129Process
Information
Entity
Material
Entity
We focus here on these three
BFO:categories
and ignore ‘Attribute’ for the sake of simplicity
The following slides contain illustrative examples of terms used
129
Slide130Process
Information
Entity
Material
Entity
130
Portion of Material
Part/Component
Switch
Boiler
Furnace
Tank
Factory
Access road
Delivery vehicle
Slide131Process
Information
Entity
Material
Entity
Product Model (output of CAD system)
Requirement Specification
Process Plan
Production Plan
Part/Component List
Maintenance Plan
Maintenance Report
Maintenance History
131
Slide132Process
Information
Entity
Material
Entity
Design Process
Production Process
Production Plan Generation Process
Product Use Process
Product Maintenance Process
Product Inspection Process
End Of Life Process
132
Slide133Process
Information
Entity
Material
Entity
133
Slide134Process
Information
Entity
Material
Entity
134
Slide135Process
Information
Entity
Material
Entity
time
135
Slide136Top Level organization of BFO
136
Process
Information Entity
Material
Entity
Attribute
BFO: Continuant
BFO: Occurrent
Temporal Region
occupies
Spatial Region
occupies
For some processes we have also process boundaries (beginning of process, end of process) at determinate Temporal Intervals. For some processes beginnings or endings may be indeterminate
Slide137Process
Information
Entity
Material
Entity
P
r
o
c
e
s
s
P
l
a
nn
e
d
P
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o
c
e
s
s
P
r
odu
c
t
L
if
e
C
y
c
l
e
(
P
L
C
)
BFO:
P
r
o
c
e
s
s
137
Slide138Process
P
r
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c
e
s
s
P
l
a
nn
e
d
P
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c
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s
s
P
r
odu
c
t
L
if
e
C
y
c
l
e
(
P
L
C
)
BFO:
P
r
o
c
e
s
s
P
r
o
du
c
t
i
o
n
P
l
an
G
e
n
eration
P
r
o
c
e
s
s
D
e
s
i
g
n
P
r
o
c
e
s
s
Follows
Mainten-ance
Process
U
s
e
P
r
ocessEnd of Life ProcessPart ofPart ofPart ofPart ofPart of
Follows
Follows
Inter-
sperses
Follows
Part of
P
r
o
du
c
t
i
o
n
P
r
o
c
e
s
s
Information
Entity
Material
Entity
138
Slide139P
r
odu
c
t
L
if
e
C
y
c
l
e
(
P
L
C
)
P
r
o
du
c
t
i
o
n
P
l
an
G
e
n
eration
P
r
o
c
e
s
s
D
e
s
i
g
n
P
r
o
c
e
s
s
Follows
Mainten-ance
Process
U
s
e
P
r
o
c
e
s
s
E
nd of
Life Process
Part of
Part of
Part of
Part of
Part of
Follows
Follows
Inter-
sperses
Follows
Part of
P
r
o
du
c
t
i
o
n
P
r
o
c
essParthood Structure of PLC
139
Slide140BFO:
P
r
o
c
e
s
s
P
r
o
du
c
t
i
o
n
P
l
an
G
e
n
eration
P
r
o
c
e
s
s
D
e
s
i
g
n
P
r
o
c
e
s
s
Follows
Mainten-ance
Process
U
s
e
P
r
o
c
e
s
s
E
nd of
Life Process
Is-a
Is-a
Is-a
Is-a
Is-a
Follows
Follows
Inter-
sperses
Follows
Is-a
P
r
o
du
c
t
i
o
n
P
r
o
c
e
s
s
Is-a (Subtype-of)
Structure of the PLC
P
r
odu
c
t
L
if
e Cycle (
P
L
C
)
The PLC is a process
Is_a
140
Slide141BFO:
P
r
o
c
e
s
s
P
r
o
du
c
t
i
o
n
P
l
an
G
e
n
eration
P
r
o
c
e
s
s
D
e
s
i
g
n
P
r
o
c
e
s
s
Follows
Mainten-ance
Process
U
s
e
P
r
o
c
e
s
s
E
nd of
Life Process
Is-a
Is-a
Is-a
Is-a
Is-a
Follows
Follows
Inter-
sperses
Follows
Is-a
P
r
o
du
c
t
i
o
n
P
r
o
c
e
s
s
Is-a (Subtype-of) Structure
of the PLC
P
r
odu
c
t
L
if
e Cycle
(
P
L
C
)
But the successive parts of the PLC are also processes
Is_a
141
Slide142Process
P
r
o
c
e
s
s
P
l
a
nn
e
d
P
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s
s
P
r
odu
c
t
L
if
e
C
y
c
l
e
(
P
L
C
)
BFO:
P
r
o
c
e
s
s
P
r
o
du
c
t
i
o
n
P
l
an
G
e
n
eration
P
r
o
c
e
s
s
D
e
s
i
g
n
P
r
o
c
e
s
s
Follows
Mainten-ance
Process
U
s
e
P
r
ocessEnd of Life ProcessPart ofPart ofPart ofPart of
Part of
Follows
Follows
Inter-
sperses
Follows
Part of
P
r
o
du
c
t
i
o
n
P
r
o
c
e
s
s
Requirement
Planning
Concept Development
Product
Definition
Product Development
Product Introduction
Product
Support
Disposal and Recycling
Generic perspective from the manufacturing industry
142
Slide143Follows
Process
P
r
o
c
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s
s
P
l
a
nn
e
d
P
r
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c
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s
s
P
r
odu
c
t
L
if
e
C
y
c
l
e
(
P
L
C
)
BFO:
P
r
o
c
e
s
s
P
r
o
du
c
t
i
o
n
P
l
an
G
e
n
eration
P
r
o
c
e
s
s
D
e
s
i
g
n
P
r
o
c
e
s
s
Part of
Follows
P
r
o
du
c
t
i
onProcessInformationEntityPart ofMaintenance ProcessPart ofFollowsPart ofProduction PlanHas output
Guides
143
Slide144Follows
Process
P
r
o
c
e
s
s
P
l
a
nn
e
d
P
r
o
c
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s
s
P
r
odu
c
t
L
if
e
C
y
c
l
e
(
P
L
C
)
BFO:
P
r
o
c
e
s
s
P
r
o
du
c
t
i
o
n
P
l
an
G
e
n
eration
P
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o
c
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s
s
D
e
s
i
g
n
P
r
o
c
e
s
s
Part of
Follows
P
r
o
du
c
t
i
onProcessInformationEntityPart ofMaintenance ProcessPart ofFollowsPart ofProduction PlanHas output
Guided-by
Material EntityHas-output
P
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odu
c
t
144
Slide145Maintenance Process
Ma
in
t
e
n
a
n
c
e
P
l
an
G
eneratio
n
P
r
o
c
e
s
s
H
a
s
o
utp
u
t
Maintenance
P
l
an
Guided-by
145
Slide146Follows
Process
P
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c
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s
s
P
l
a
nn
e
d
P
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c
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s
s
P
r
odu
c
t
L
if
e
C
y
c
l
e
(
P
L
C
)
BFO:
P
r
o
c
e
s
s
P
r
o
du
c
t
i
o
n
P
l
an
G
e
n
eration
P
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c
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s
s
D
e
s
i
g
n
P
r
o
c
e
s
s
Part of
Follows
P
r
o
du
c
t
i
onProcessInformationEntityPart ofMaintenance ProcessPart ofFollowsPart ofHas outputGuided-by
Ma
intenance Plan Generation Process
H
a
s
o
utp
u
t
Maintenance
P
l
an
Guided-by
P
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c
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i
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n
P
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an
146
Slide147Follows
P
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c
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s
s
P
l
a
nn
e
d
P
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c
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s
s
P
r
odu
c
t
L
if
e
C
y
c
l
e
(
P
L
C
)
BFO:
P
r
o
c
e
s
s
P
r
o
du
c
t
i
o
n
P
l
an
G
e
n
eration
P
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o
c
e
s
s
D
e
s
i
g
n
P
r
o
c
e
s
s
Part of
Follows
P
r
o
du
c
t
i
o
nProcessPart ofMaintenance ProcessPart ofFollowsPart ofHas outputGuided-byHas output
Maintenance Plan
Guided-byProduction Plan
Maintenance
Report
Ma
in
t
e
n
a
n
c
e
P
l
an
G
eneratio
n
P
r
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c
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s
s
147
In what sense is the maintenance process ‘Guided-by’ the maintenance plan? To deal with this we need to introduce the dimension of inspection and decision to maintain (similarly we need to add the dimension of market research and decision to produce, prior to the design and production plan generation processes)
Slide148Follows
Process
P
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s
s
P
l
a
nn
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d
P
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s
s
P
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c
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L
if
e
C
y
c
l
e
(
P
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C
)
BFO:
P
r
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s
s
P
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du
c
t
i
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n
P
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an
G
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n
eration
P
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s
s
D
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s
i
g
n
P
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c
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s
s
Part of
Follows
P
r
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du
c
t
i
onProcessInformationEntityPart ofMaintenance ProcessPart ofFollowsPart ofProduction PlanHas output
Guided-by
Material EntityHas-output
P
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odu
c
t
148
Slide149Follows
P
r
o
c
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s
s
P
l
a
nn
e
d
P
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s
s
P
r
odu
c
t
L
if
e
C
y
c
l
e
(
P
L
C
)
BFO:
P
r
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c
e
s
s
P
r
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du
c
t
i
o
n
P
l
an
G
e
n
eration
P
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c
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s
s
D
e
s
i
g
n
P
r
o
c
e
s
s
Part of
Follows
P
r
o
du
c
t
i
o
nProcessPart ofMaintenance ProcessPart ofFollowsPart ofHas output*Guided-byHas output
Maintenance Pl
anGuided-byProduction Plan
Maintenance
Report
Ma
in
t
e
n
a
n
c
e
P
l
an
G
eneratio
n
P
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c
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s
s
149
P
r
odu
c
t
H
a
s
o
utp
u
t
*
*Two different senses of ‘Has output’? or two different senses of ‘Product’?
Slide150150
Slide151P
r
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s
s
P
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a
nn
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d
P
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s
P
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c
t
L
if
e
C
y
c
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e
(
P
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C
)
BFO:
P
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s
s
P
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du
c
t
i
o
n
P
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an
G
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n
eration
P
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s
s
Follows
P
r
o
du
c
t
i
o
n
P
r
o
c
e
s
s
Part of
Maintenance Process
Part of
Follows
Part of
H
a
s outputGuided-byHas output Maintenance PlanGuided-byProduction Plan Maintenance Report
Maintena
nce Plan Generation ProcessMaintenance
History
T
e
c
hn
i
c
al
Manual
151
Slide152Transformed-into
Material
Entity
Product
W
a
s
te
Material
R
aw
Material
Has-input
152
We need to deal with the fact that the end-of-life process normally occurs not merely after some process of use, but after long sequence of processes of use or after a long time period has elapsed
Slide153P
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P
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P
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D
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p
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Follows
P
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P
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153
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Slide154Transformed-into
Material
Entity
Product
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te
Material
R
aw
Material
Has-input
154
Slide155End of Life
Process
EOL
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155
Slide156Material
Entity
Person
Aggregate
of persons
(Team, Staff, …)
156
Slide157Material
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157
Slide158Material
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Procurement Staff,
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People
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Engineer…
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158
Slide159Material
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Maintenance System
Supply System
(
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Infrastructure
(
Transport / Delivery System
…
)
Facilities
+
Systems
Machine, Vehicle
159
Slide160P
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160
Slide161How to Build the
Industry Ontology Foundry
Barry Smith
NIST, December 8, 2016
161
Slide162Why do people repeatedly choose to build their own ontology for X, rather than reuse an existing one?
Because they do not find reusable components
Because they do not find tested design patterns
Because of a lack of trust in externally built ontologies
162
Slide163First steps
Collect the principal ontologies in the field and create a library
Bring together selected leaders in the field to identify principles for convergence on a suite of generic reference ontologies
Select ontologies (stubs) to form initial parts of this suite
Create a governance structure – Coordinating Editorial Board
163
Slide164164
http://ieportal.ncor.buffalo.edu
IE
Slide165165
Slide166OBO Foundry Principles
commitment to collaboration
open
common formal language (OWL, CL)
maintenance in light of scientific advance
166
Slide167OBO Foundry Principles
common architecture
all terms should be singular common nouns
provide terms with definition (formal + text)
locus of authority, trackers, help deskorthogonality – one ontology for each domain
167
Slide168Ontology’s networked through definitions
compound terms in ontologies should be defined wherever possible by using terms from other OBO Foundry ontologies
elevated blood glucose concentration =
def
PATO:
increased concentration
of CHEBI:
glucose
in FMA:
blood
168
Slide169Everything is incremental
Principle of low hanging fruit – build the easy bits first
Even a small ontology, if shared, and aggressively used, brings immediate benefits
169
Slide170Orthogonality
For each domain, there should be convergence upon a single
generic reference ontology
that is recommended for reuse by the wider community
a single Protein Ontology a single Disease Ontology a single Cell Ontology …
170
Slide171Orthogonality for IOF
For each domain, there should be convergence upon a single
generic reference ontology
that is recommended for reuse by the wider community
a single Materials Ontology a single PLM Ontology a single Function Ontology …
171
Slide172Current state
Peer review: Candidate ontologies for membership in the
the
Foundry most undergo a process of peer review for biological and logical accuracy
OBO Foundry Board of Coordinating Editors
172
Slide173all definitions should be of the Aristotelian genus-species form
173
E
is_a
F
is_a
is_a
B
A
a B =def. an A which Cs
A = genus
B = species
C = differentia
Slide174Common architecture
Basic Formal Ontology (BFO)
174
Slide175http://
http://mitpress.mit.edu/building-ontologies
175
Slide176Example: The Cell
Ontology
Slide177Common architecture
Basic Formal Ontology (BFO)
encapsulates tested ontology design patterns applied in more than
350
ontology initiatives:http://ifomis.uni-saarland.de/bfo/usersprovides root nodes for domain ontologies as a starting point for downward population
177
Slide178ISO Standard under review
ISO/IEC JTC 1/SC 32/WG 2
Title
(Information Technology — Ontologies — Top-Level Ontologies)
Part 1: Requrements Part 2: Basic Formal Ontology)
178
Slide179These principles
offer a solution to the problem of ontology silos that is
modular
incremental
empirically basedincorporates a strategy for motivating potential developers and users
179
Slide180These principles
offer a solution to the problem of trust
there is one generic reference ontology for each domain, and the editor(s) of that ontology are invested in its correctness and in its sustainability
the coordinating editorial board and the peer review process provide an extra layer of security in case of failure at the level of single ontologies
180
Slide181Benefits of orthogonality
Building modular reference ontologies brings benefits of division of labor and of ownership: motivates specialists to commit themselves over the long term to maintaining the ontology for their domain
This in turn motivates users to commit themselves to adoption
they see strong positive network effects from use of the ontology
they gain reassurance from long-term commitment
181
Slide182Benefits of orthogonality
It helps those new to ontology who need to know where to look in finding an ontology relating to their subject-matter
it obviates the need for ‘mappings’ between ontologies, which are
difficult to create and use
error-prone hard to keep up-to-date when mapped ontologies change on either side of the mapping at irregular intervals
182
Slide183Basic Formal Ontology (BFO)
183
INDEPENDENT
CONTINUANT
DEPENDENT CONTINUANT
INFORMATION ARTIFACT
OCCURRENT
Materials
Functions
Materials Attributes
Product Attributes
Software
Drawings
Specifications
Manuals
Images
Sensor Data
Processes
Product Life Cycle
Equipment
Products
And now similarly for IOF
Slide184Reference Ontologies vs. Application Ontologies
Reference Ontologies designed for aggressive reuse
Application Ontologies designed to address needs of specific products, projects, …
Recommendation: Application ontologies should wherever possible reuse terms taken from reference ontologies within the Foundry
Following MIREOT / OntoFox
184
Slide185http://www.tinker.af.mil/shared/media/document/AFD-140606-042.pdf
185
Slide186http://www.irss.ca/development/documents/CODES%20&%20STANDARDS_02-28-08/ASME%20V%201998/ASME%20V%20Art%2030%20Terms.pdf
186
Slide187Glossary
ACTIVITY
=def. a measure of how radioactive a particular radioisotope is. Activity is calculated by the number of atoms disintegrating per unit of time. Its unit of measurement is the curie. See SPECIFIC ACTIVITY.
SPECIFIC ACTIVITY
(RT) =def. a measure of the activity per unit weight generally measured in curies per gram (SI) dis/sec-dm
187
Slide188Glossary
‘activity’ is used 88 times in this document
to mean
maintenance activity
engineering activityinspection activityprocuring activityetc. etc.
188
Slide189Glossary
VISCOSITY:
Quality, state or degree of being viscous. That property of a body by virtue of which, when flow occurs inside it, forces arise in such a direction as to opposite the flow.
VISCOSITY:
A measurement of a liquids resistance to change of shape or flow. Also referred to as flow resistance.189
Slide190Semantic Sensor Network Ontology
190
http://www.sciencedirect.com/science/article/pii/S1570826812000571
Slide191W3C Stimulus-Sensor-Observation Ontology Design Pattern
191
Stimuli =def. detectable changes in the environment
Sensors =def. physical objects that perform observations
https://www.w3.org/2005/Incubator/ssn/wiki/Foundational_Layer
Slide192W3C Stimulus-Sensor-Observation Ontology Design Pattern
192
“Observations act as the nexus between incoming stimuli, the sensor, and the output of the sensor, i.e., a symbol representing a region in a dimensional space. Therefore, we regard observations as social, not physical, object.”
Slide193DOLCE
Descriptive Ontology for Linguistic and Cognitive Engineering
193
Slide194SSN alignment to DOLCE
194
Slide195SSN alignment to DOLCE
195
Slide196196
Slide197ssn:Observation subclass of:
DUL:Situation
, things that have a
ssn:observedProperty
property who must be a ssn:Property, things that have exactly ssn:sensingMethodUsed property that is a ssn:Sensing, things that have exactly ssn:featureOfInterest property that is a ssn:FeatureOfInterest, things that have a ssn:sensingMethodUsed property who must be
ssn:Sensing
, things that have a
DUL:includesEvent
property who may be a
ssn:Stimulus
, things that have a
ssn:observationResult
property who must be a
ssn:SensorOutput
, things that have exactly
ssn:observedBy
property that is a
ssn:Sensor
, …
197
Slide198W3C paraphrase
A Observation is something that is a Situation and has a observedProperty property who must be a Property and has exactly sensingMethodUsed property that is a Sensing and has exactly featureOfInterest property that is a FeatureOfInterest and has a sensingMethod-Used property who must be a Sensing and has a includesEvent property who may be a Stimulus and has a observationResult property who must be a SensorOutput and has exactly observedBy property that is a Sensor …
Copyright 2009 - 2011 W3C
198
Slide199Development Principles of the Common Core Ontologies
Top-Down/Bottom-Up Approach – The content of ontologies is constrained by science and informed by data
Common Upper Level Ontology – The ontologies extend from the common upper level ontology BFO
Delineated Content - Each ontology has a well defined content that does not overlap with the content of any other ontology
Composable Content – Classes in the ontologies represent entities at a level of granularity that can be composed in various ways to map to terms in sources
199
Slide200OBI: Measuring
the glucose concentration in blood
200
Slide201OGMS
Ontology for General Medical Science,
http://code.google.com/p/ogms/
201
Slide202202
Slide203Big Picture
203
Slide204Nociceptive System
204
Slide205Pain Ontology
http://philpapers.org/archive/SMITAO-12.pdf
205
Slide206Symptoms
Signs
Physical Basis
Examples
Canonical Pain
PCT: Pain with concordant tissue damage
Pain
Manifestation of tissue damage
Signals sent to
nociceptive
system
Activation of emotion- generating brain centers, which can produce increased heart rate, blood pressure, galvanic skin response.
Peripheral tissue damage
Intact
nociceptive
system
Primary sunburn
Pain from strained muscle
Pain from fracture
Pulpitis
Variant Pain
PNT: pain without concordant tissue damage
Pain
Manifestation of some disorder in the patient
Signals sent to
nociceptive
system
Patient reports of pain are either exaggerated or muted relative to disorder
Activation of emotion generating brain centers
Physical disorder of amplitude control mechanisms associated with the
nociceptive
system
Intact
nociceptive
system
Myofascial
pain disorder
Tension-type headache
Chronic back pain
NN:
neuro-pathic
nociception
Pain
Neurological test confirming nerve damage
Disorder in the
nociceptive
system
Trigeminal neuralgia
Post-herpetic neuralgia
Diabetic neuropathy
Central pain
PRP: Pain-Related Phenomena Without Pain
PBWP: pain behavior without pain
Aaargh
!
Report of pain
Sick role behaviors accompanied by normal clinical examination
Grossly exaggerated pain behaviors
Identified external incentives
Mental states such as anxiety, rather than peripheral tissue locus
Disordered emotional or cognitive systems misinterpreting sensory signals
Factitious pain
Malingering
Anxiety-induced pain report
TWP: tissue-damage without pain
No pain
Manifestation of tissue damage normally of the sort to cause pain
Suppression of pain system by one or other mechanism
Stress associated with sudden emergencies
Physiological damping of the pain process caused by endorphins
Placebo-induced
opioid
analgesia
Genetic insensitivity to pain
206
Slide207The Pain Ontology as subtype of Sensing Ontology
207
Slide208Four types of (pain) sensor failure
triggered by design inputs
triggered without inputs
triggered by self
generates
ungrounded outputs
not triggered by design inputs
208
Slide209209
Slide210Deep learning – Gold standard problem
210