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Page 1: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

switch on Webex

Page 2: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

Examples of new ontologies using BFO

• Actionable Intelligence Retrieval System (AIRS)• US Transcom (Transportation Command)

Enterprise Ontology (http://www.securboration.com/)

• Mental Functioning Ontology (MFO), Emotion Ontology (MFO-EM)

• Financial Report Ontology: FRO– here BFO (and IAO) must be under the hood

Page 3: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

FMA: BFO under the hoodAnatomical Entity

Physical Anatomical Entity

Material Physical Anatomical Entity

-is a-

Non-material Physical Anatomical Entity

ConceptualAnatomical Entity

AnatomicalStructure

BodySubstance

BodyPart

HumanBody

OrganSystem

OrganCell

OrganPart

AnatomicalSpace

Anatomical Relationship

CellPart

Biological Macromolecule

Tissue

Non-Physical

Anatomical Entity

Physical Anatomical Entity

Material Physical Anatomical Entity

-is a-

Non-material Physical Anatomical Entity

ConceptualAnatomical Entity

AnatomicalStructure

BodySubstance

BodyPart

HumanBody

OrganSystem

OrganCell

OrganPart

AnatomicalSpace

Anatomical Relationship

CellPart

Biological Macromolecule

Tissue

Anatomical Entity

Physical Anatomical Entity

Material Physical Anatomical Entity

-is a-

Non-material Physical Anatomical Entity

ConceptualAnatomical Entity

AnatomicalStructure

BodySubstance

BodyPart

HumanBody

OrganSystem

OrganCell

OrganPart

AnatomicalSpace

Anatomical Relationship

CellPart

Biological Macromolecule

Tissue

Non-Physical

Page 4: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

Blue Force Overwatch

The Plant Ontology

Page 5: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

cROP: Common Reference Ontologies for Plants

Page 6: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

Role of BFO in OBO Foundry

• OBO Foundry and related suites of ontologies will work only if their component ontologies are orthogonal

• Orthogonality can be established only if these ontologies are comparable

• BFO is at the core of the strategy to ensure compatibility

Page 7: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

id: HP:0001943 ! Hypoglycemia = = decreased concentration of glucose in the blood

• intersection_of: PATO:0001163 ! decreased concentration• intersection_of: qualifier PATO:0000460 ! abnormal• intersection_of: towards CHEBI:17234 ! glucose• intersection_of: inheres_in FMA:9670 ! Portion of blood

Class: Hypoglycemia ≡ decreased concentration &towards some glucose & inheres_in some portion of blood & qualifier some 'abnormal‘

P. Robinson: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3224779/http://www.ncbi.nlm.nih.gov/pubmed/23104991

Page 8: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

HP:0001720 ! tachycardiaProcess: GO:0060048 cardiac muscle contractionQuality: PATO:0000912 increased rate

PATO:Rate =def. A quality of a single process inhering in a bearer by virtue of the bearer's occurrence per unit time

logically: rate(r,p) =def. p is a process & p consists of a sequence of similar sub-processes & these sub-processes repeat r times per unit time

Note that there is no reference to a quality or to inherence here

Page 9: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

Tachycardi

• Thus Tachycardia only exists if there is the sort of cyclical repetition of cardiac muscle contraction that is involved in the heart's beating.Thus Tachycardia is not a rate of cardiac muscle contraction, but rather a rate of cardiac muscle contraction repetition.

Page 10: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

Treatment of ‘process qualities’• ‘BFO:quality’ just means: a quality of an

independent continuant • PATO:process-quality uses 'quality' in a

different sense; providing this sense is well-defined, there is no objection to its use. Unfortunately most PATO:process-quality terms are currently poorly defined. The hope is that use of BFO 2.0 can help to bring improvements.

Page 11: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

rate (rough version)

rate(r,p) =def. p is a process & p consists of a sequence of similar sub-processes & these sub-processes repeat r times per unit time

increased-rate(r,p) = def. p is such that r is greater than a certain normal threshold (defined for each particular kind of patient)

There are numbers here, and time units, and thresholds for numbers.

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But there are no extra entities called ‘process qualities’

• If we observe that there are 3 apples in a bowl on Wednesday and 2 apples in the same bowl on Thursday, then we could express this by saying that the apples in the bowl had the quality of threeness on Wednesday and the quality of twoness on Thursday.

• People could talk like that if they wanted, butit would be ontologically much less adequate than just the assertion underlined above.

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Similarly,if we observe that there is a 63 bpm heart rate in a patient on Wednesday and 102 bpm heart rate in the same partient on Thursday, then we could express this by saying that the heart beat process of the patient had the quality of sixtythree-bpm-ness on Wednesday and ofonehundredandtwo-bpm-ness on Thursday. People could talk like that if they wanted, butit would be ontologically much less adequate than just the assertion underlined above/

•63bpm Wednesday and 102 bpm in the same patient on Thursday

i.e. more beats per minute on Thursday

Page 14: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

What BFO is designed to do

• BFO is not intending to constrain what people say, merely to provide a formally coherent basis for definitions (for example in PATO).

• Given this basis, it should be possible to define all the terms one needs, including all the terms one needs from PATO.

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Which general terms refer to universals?

For some general terms X we can formulate definitions of the following sort:

(C) Collection of X’s =def. collection of particulars of type X.

How do we determine whether for (C) holds of a given term ‘X’? This is the job of scientists, in an on-going process of terminology evolution through which those terms come to be selected for that are fit to serve in successive formulations of the corresponding scientific theory.

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Which general terms refer to universals?

Each scientific theory as it exists at any given stage will likely be marked by (as yet unidentified) terminologically relevant errors, and these errors will accordingly be carried over into the corresponding ontology. Hence, we cannot embrace any one-one correspondence between scientific general terms and universals in reality. Rather, we should assume, for heuristic purposes only, that at any given stage the terms used by scientists in a given discipline refer to universals, knowing full well that this assumption may be false for any given term.

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Qualities determinable and determinate

temperatureblood pressuremass...

are continuantsthey exist through time while undergoing changes

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Qualitiestemperature / blood pressure /

mass ...are dimensions of variation within the structure of the entity; a quality is something which can change while its bearer remains one and the same

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A Chart representing how John’s temperature

changes

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Qualities

temperature / blood pressure / mass ...are dimensions of variation within the structure of the entity; a quality is something which can change while its bearer remains one and the samehence only independent continuants may have qualities

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John’s temperature

the temperature John has throughout his entire life, cycles through different determinate temperatures from one time to the next

John’s temperature is a physiology variable which, in thus changing, exerts an influence on other physiology variables through time

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temperature

John’s temperature

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37ºC 37.1ºC 37.5ºC37.2ºC 37.3ºC 37.4ºC

instantiates at t1

instantiates at t2

instantiates at t3

instantiates at t4

instantiates at t5

instantiates at t6

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One issue

Chris Mungall:

BFO should have some documented position as to •determinables are still present when their value is zero •OR physics is such that no true determinable can take on a zero value.

Page 24: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

a quality is something which can change while its bearer remains one and the samehence only independent continuants may have qualities for suppose q were a quality of a processthen q would have to be something which could change while the process, its bearer, would remain one and the same – and this is not possible

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temperature course

John’s temperature

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increasing temperature

course

constant temperature

course

decreasing temperature

course

instantiates at t1

instantiates at t4

instantiates at t5

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temperature

John’s temperature

37.2º37.2ºCC

instantiates at t3

unit of measurement

ºC

measures

information artefact

measurement record

“John has temperature 37.2ºC at t3”

instantiates

about

uses

John

inheres_in

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temperature

John’s temperature

37.2ºCtemperature

instantiates at t3

unit of measurement

ºC

measures

information artefact

measurement record

“37.2ºC at t3”

instantiates

about

uses

about

about

note re IAO aboutness

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BFO: The Very Top

continuant

independentcontinuant

dependentcontinuant

quality

occurrent

temperature 28

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Blinding Flash of the Obvious

independentcontinuant

dependentcontinuant

quality

temperature types

instances

organism

John John’s

temperature 29

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Blinding Flash of the Obvious

independentcontinuant

dependentcontinuant

quality

temperature types

instances

organism

John John’s

temperature 30

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independentcontinuant

dependentcontinuant

quality

temperature types

instances

organism

John John’s

temperature

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Can sites have histories?Full process(p) =def. there is some spatiotemporal regions r & p is the sum of all processes occurring in r

A history is a full process

Participants of a history: independent continuant, site – but what if they coincide spatio-temporally

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Process profiles

Full process(p) =def. there is some spatiotemporal regions r & p is the sum of all processes occurring in r

Example of full process: history

Process profile = a process that is less than a full process

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Canonical example

• A spinning top is spinning• A spinning top is simultaneously

warming

The spinning and the warming are both proper parts of the full process (= all the processes taking place within the

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Families of process profiles

• Quality process profiles• Measurement/assay process profiles• Scientific discipline demarcated

process profiles• Diseases• Speech, music, thinking, writing,

dancing …

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Relative process profiles

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independentcontinuant

dependentcontinuant

quality

temperature

organism

John John’s

temperature

occurrent

process

life of an organism

John’s life

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independentcontinuant

dependentcontinuant

quality

temperature

organism

John John’s

temperature

occurrent

process

course of temperature

changes

John’s temperature history

38

process profile

quality process profile

Page 39: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

independentcontinuant

dependentcontinuant

quality

temperature

organism

John John’s

temperature

occurrent

process

life of an organism

John’s life

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Page 40: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

independentcontinuant

dependentcontinuant

quality

temperature

organism

John John’s

temperature

occurrent

process

metabolism of an organism

John’s metabolism

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process profile

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independentcontinuant

dependentcontinuant

quality

temperature

organism

John John’s

temperature

occurrent

process

growth of an organism

John’s growth

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process profile

Page 42: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

independentcontinuant

dependentcontinuant

quality

temperature

organism

John John’s

temperature

occurrent

process

development of an organism

John’s development

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process profile

Page 43: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

temperature

John’s temperature

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37ºC37.1º

C37.5º

C37.2º

C37.3º

C37.4º

C

instantiates at t1

instantiates at t2

instantiates at t3

instantiates at t4

instantiates at t5

instantiates at t6

Page 44: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

human

John

embryo

fetus adultneonat

einfant child

instantiates at t1

instantiates at t2

instantiates at t3

instantiates at t4

instantiates at t5

instantiates at t6

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human

John

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embryo

fetus adultneonat

einfant child

instantiates at t1

instantiates at t2

instantiates at t3

instantiates at t4

instantiates at t5

instantiates at t6

in nature, no sharp boundaries here

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portion of water

this portion of H20

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portion of ice

portion of liquid water

portion of gas

instantiates at t1

instantiates at t2

instantiates at t3

Phase transitions

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temperature

John’s temperature

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37ºC37.1º

C37.5º

C37.2º

C37.3º

C37.4º

C

instantiates at t1

instantiates at t2

instantiates at t3

instantiates at t4

instantiates at t5

instantiates at t6

in nature, no sharp boundaries here

in nature, no sharp boundaries here

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heart disease

John’s heart disease (continuant)

49

disease with asymptomatic disease, silent

infarction

disease with early lesions

and small fibrous plaques

disease with

stable angina

disease with surface disruption of plaque

disease with

unstable

angina

instantiates at t2

instantiates at t3

instantiates at t4

instantiates at t5

instantiates at t6

Page 50: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

What is the course of John’s heart disease?

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independentcontinuant

dependentcontinuant

disposition

heart disease

organism

John John’s

heart disease

occurrent

process

heart disease course

John’s heart disease course

53

process profile

Page 52: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

heart function: to

pump

John’s heart function: to pump

55

pumping function of heart after

fatality

instantiates at t7

Page 53: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

heart function: to

pump

John’s heart function: to pump

56

pumping function of

healthy heart

instantiates at t1

this portion of deoxygenated blood

1

instantiates at t1

material entity

portion of blood

this portion of oxygenated blood

instantiates at t1

material entity

portion of blood

has input has output

Page 54: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

heart function: to

pump

John’s heart function: to pump

57

instantiates at t1

this clot1

instantiates at t1

this clot

instantiates at t1

material entity

clot

has input has output

pumping function of

healthy heart

Page 55: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

heart function: to

pump

John’s heart function: to pump

58

pumping function of

healthy heart

instantiates at t1

this portion of blood

instantiates at t1

material entity

oxygenated portion of blood

this concentration

instantiates at t1

quality

concentration of oxygen

has output need to get time right

Page 56: Switch on Webex. Examples of new ontologies using BFO Actionable Intelligence Retrieval System (AIRS) US Transcom (Transportation Command) Enterprise

Continuant Occurrent

IndependentContinuant

SpecificallyDependentContinuant

Quality

ProcessGenericallyDependentContinuant

Information Artifact

Sequence…

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GDCs

• universals are unchangeable -- GDCs are always such that they are changeable (there are instances of the relevant universal which can change, e.g. successive editions of books)

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• lower levels of types do not ‘carry identity’ in OntoClean terms

• are threshold divisions (hence we do not have sharp boundaries, and we have a certain degree of choice, e.g. in how many subtypes to distinguish, though not in their ordering)

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independentcontinuant

dependentcontinuant

quality

temperature types

instances

organism

John John’s

temperature

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independentcontinuant

dependentcontinuant

quality

temperature

organism

John John’s

temperature

occurrent

process

course of temperature

changes

John’s temperature history

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independentcontinuant

dependentcontinuant

quality

temperature

organism

John John’s

temperature

occurrent

process

life of an organism

John’s life

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temperature

John’s temperature

37.2ºC temperatur

einstantiates at t3

information artefact

measurement datum

“37.2ºC at t3”

instantiates

measurement assay

quality process

temperature assay at t3

instantiates

has outputJohn

has_input

about

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BFO: The Very Top

continuant

independentcontinuant

dependentcontinuant

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dependentcontinuant

quality realizable dependentcontinuant

68

role(optional)

disposition(has physical

basis)

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dependentcontinuant

quality realizable

role(optional)

disposition(aka ‘ability’)

function(a disposition designed

or selected for)

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:.

Role of some chemical compound: to serve as analyte in an experiment

of this human being: to serve as PI of this research project

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:.

Role optional:exists because the bearer is in some special natural, social, or institutional set of circumstances in which the bearer does not have to be

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:.

Rolesoften form systems of mutual dependence

husband / wife first in queue / last in queuedoctor / patient

host / pathogen

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:.

Function - of liver: to store glycogen- of birth canal: to enable transport- of eye: to see- of mitochondrion: to produce ATP

reflection of physical makeup of bearer 73

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:.

Qualities are categorical features of reality – you just have them

Functions, roles and dispositions are potential featires of reality: they are realizable dependent continuants, realized in certain associated processes

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independentcontinuant

dependentcontinuant

role

drug role

portion of chemical compound

this portion of aspirin

role of this portion of aspirin

occurrent

process

process of drug

adminstration

John’s taking this portion of aspirin

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independentcontinuant

dependentcontinuant

role

drug role

portion of chemical compound

this portion of aspirin

role of this portion of aspirin

occurrent

process

process of drug

adminstration

John’s taking this portion of aspirin

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inheres_in

realized_in

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• The Road to Convergence

All ontologies for each given domain (anatomy, chemistry…) should be part of a single suite of interoperable ontologies

should use a common top-level corefor subdomains with many variants, should

follow the strategy of canonical ontologies with extensions

should require acceptance of common, tested guidelines on all subscribing ontology developers

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CONTINUANT OCCURRENT

INDEPENDENT DEPENDENT

ORGAN ANDORGANISM

Organism(NCBI

Taxonomy)

Anatomical Entity

(FMA, CARO)

OrganFunction

(FMP, CPRO) Phenotypic

Quality(PaTO)

Organism-Level Process

(GO)

CELL AND CELLULAR

COMPONENT

Cell(CL)

Cellular Compone

nt(FMA, GO)

Cellular Function

(GO)

Cellular Process

(GO)

MOLECULEMolecule

(ChEBI, SO,RnaO, PrO)

Molecular Function(GO)

Molecular Process

(GO)

initial OBO Foundry coverage, ontologies automatically semantically coupled

GRANULARITY

RELATION TO TIME

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Disposition (Internally-Grounded Realizable

Entity)disposition =def.

a realizable entity which if it ceases to exist, then its bearer is physically changed, and whose realization occurs when this bearer is in some special physical circumstances, in virtue of the bearer’s physical make-up

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Anatomy Ontology(FMA*, CARO)

Environment

Ontology(EnvO)

Infectious Disease

Ontology(IDO*)

Biological Process

Ontology (GO*)

Cell Ontology

(CL)*

CellularComponentOntology

(FMA*, GO*) Phenotypic Quality

Ontology(PaTO)

Subcellular Anatomy Ontology (SAO)Sequence Ontology

(SO*) Molecular Function

(GO*)Protein Ontology(PRO*) OBO Foundry Modular Organization

top level

mid-level

domain level

Information Artifact Ontology

(IAO)

Ontology for Biomedical

Investigations(OBI)

Spatial Ontology(BSPO)

Basic Formal Ontology (BFO)

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Relations

instance-instance (primitives allow definitions)instance-typetype-type

RO 2.0 type-type – All-some rule holdsadd causes dependence includes mutual dependence among

roles, functions

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Keep RO 2.0 small

‘depends_on’ is short for ‘specifically_depends_on’

‘generically_depends_on’ is written out in full

life ofhas physical basis

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address relations between

• site,• located_in• contained_in

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RO 2.0 lists simple relations (such as depends_on);

there are many complex defined relations (such as inheres_in,

is_quality_of)

A inheres_of B =def. A depends_on B and A is_a dependent continuant and B is_a independent

continuantA is_quality_of B =def. A depends_on B and A is_a

quality and B is_a independent continuant

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starting point is here (Work of Chris Mungall)

• http://www.fruitfly.org/~cjm/ro/ro.html

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Generic Dependence

• Specific Dependence • Duration of

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Get versioning right

• CL is a standard version

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keep ‘derives from’

• change examples• recommend biologists use ‘develops from’• location involves site?• vaccine, clinical outcome, effectiveness

prevention, diagnosis, treatment, clinical registry ogms

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The Relation Ontology

• immanent relations in BFO– specific dependence– generic dependence– realization

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How to use the RO all–some form

• LMO2 molecules interact with ELF2 molecules false

• LMO2 molecules have the disposition to interact with ELF2 molecules true

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Axioms

• ALL Occurrent depends_on SOME Continuant• ALL DependentContinuant depends_on SOME

IndependentContinuant• ALL IndependentContinuant occupies SOME

3D SpatialRegion• ALL Site occupies SOME 3D SpatialRegion• ALL BoundaryOfObject occupies SOME 0, 1 or

2D SpatialRegion

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Axioms

• ALL BoundaryOfObject is_part_of SOME Object

• ALL Object has_part SOME BoundaryOfObject• ALL ProcessualEntity occurs_in SOME

SpatiotemporalRegion• ALL ProcessualEntity has_participant SOME

IndependentConinuant

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Only something that holds of all As will be an assertion that holds of the type A

Hence the All-Some ruleOr analogous rules for n-ary relations

(where n > 2)

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Definitions of type-level relations presuppose underlying instance-level relations

A is_a B presupposes instance_ofAll instances of A are instances of B

A part_of B presupposes instance-level-part-ofEvery instance of A are instance-level-parts-of

some instance of B

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Rules for including relations in RO

To avoid forking, keep RO as small as possibleIf we have a relation, say, adjacent_to in RO, then we should not add lists of easily defined relations of the form

adjacent_to_organ: adjacent_to_cytoplasm:adjacent_to_neuron:

In general: include a relation only if it is lexicalized

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Rules for including relations in RO

In every case we need to check, before we add a relation A R B, that, for some set of A and B terms we have data about the As and data about the Bs which is such that

all the instances of A stand in instance-level R to some B

e.g. all the instances of cell membrane stand in instance-level part_of to cell

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Rules for including relations in RO

Some_some relations are important not to ontology but to the treatment of empirical data e.g. relating to exceptions to proposed general hypotheses

However, in developing RO, we will need to keep track of instance-level relations in any case, and then corresponding some-some relations (and also various kinds of probabilistic relations) come for free

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Thus for example

Instead of:•

results_in_reception_of_stimulus_and_conversion_into_molecular_signal_of

use just the relations:•

results_in, is_aand the types:

reception_of_stimulus, conversion_into_molecular_signal

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Or in other words:

A results_in_reception_of_stimulus_and_conversion_into_molecular_signal_of B=Def.

A results_in B & B is_a reception_of_stimulus& B is_a conversion_into_molecular_signal

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Consequences of including only all-some relations in RO

All relations will be evaluable as1. Transitive2. Symmetric3. Reflexive4. Anti-Symmetric

All relations will support reasoningis_somehow_related_to

is the worst kind of relation to create100

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True Path Rule

the pathway from a child term all the way up to its top-level parent(s) must always be true (Gene Ontology Consortium, 2001)

= both is_a and part_of are transitive

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LacksInstance-type level

p lacks U with respect to r at time t =def. there is no instance u of U such that p stands in r to u at t.

Type-type level C1 lacks C2 with respect to r =def. for all c,t, if c instance of C1 at t then c lacks C2 with respect to r at time t.

Need a way to state on top of this: that C1s normally stand in r to some C2

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To be added to the Relation OntologyRO Core (examples)

• dependent_on (between a dependent entity and its carrier or bearer)

• quality_of (between a dependent and an independent continuant)

• functioning_of (between a process and an independent continuant)

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To be added to the Relation OntologyRO Core (examples)

• dependent_on (between a dependent entity and its carrier or bearer)

• quality_of (between a dependent and an independent continuant)

• functioning_of (between a process and an independent continuant)

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To be added to the Relation OntologyRO IL (instance-level relations) (examples)

• lacks (between an instance and a type, e.g. this pig lacks tail)

• dependent_on (between a dependent entity and its carrier or bearer)

• quality_of (between a dependent and an independent continuant)

• functioning_of (between a process and an independent continuant)

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• process has_site a = process has_participant b and b part_of a

process has_site alveolar membrane = process has_participant hemoglobin and hemoglobin part_of alvealor membrane

process:injection has_site jugular vein = process has participant (some dose of compound in the form of liquid with role drug) and (some dose of compound in the form of liquid with role drug) part_of jugular vein .

Why going for such convolution ? What is the gain here ?What is the cost of adding a primitive (when there is a valid case for it)

All this is declared at instance level but surely all instances of intrajugular injection must take place in some jugular vein(I am of course talking of canonical injection, not those performed by trainees )

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disposition =def.

a realizable entity which if it ceases to exist, then its bearer is physically changed, and whose realization occurs when this bearer is in some special physical circumstances, in virtue of the bearer’s physical make-up

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function =def.

a disposition thatis such that the physical make-up of its bearer is something the bearer possesses because it came into being, either through natural [‘positive’?] selection (in the case of natural biological entities) or through intentional design (in the case of artifacts), in order to realize processes of a certain kind.

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Relation Ontology 2.0

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ROhttp://obofoundry.org/ro/

is_apart_of

has_partlocated_in

contained_inadjacent_to

transformation_ofderives_frompreceded_by

has_participanthas_agent

Multiple defined relationsplus: instance_of, instance-level relations

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Strategy

Small number of relations to be added to this listThe whole list to be incorporated into BFO 2.0Other relations

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New Proposed Relations

specific dependence (between SDC and bearer)generic dependence (between GDC and bearer)concretization of (between SDC and GDC)boundary_ofrealizesis_aboutlacksprojects_onto (region)

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LacksInstance-type level

p lacks U with respect to r at time t =def. there is no instance u of U such that p stands in r to u at t.

Type-type level C1 lacks C2 with respect to r =def. for all c,t, if c instance of C1 at t then c lacks C2 with respect to r at time t.

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Defined relations in RO 2.0

• a inheres_in b=def. a is specifically dependent on b (a and b are continuants)

• quality_of =def. a inheres_in b and a is a quality

• functioning_of (between a process and an independent continuant)

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To be added to the Relation OntologyRO IL (instance-level relations) (examples)

• lacks (between an instance and a type, e.g. this pig lacks tail)

• dependent_on (between a dependent entity and its carrier or bearer)

• quality_of (between a dependent and an independent continuant)

• functioning_of (between a process and an independent continuant)

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How to deal with shapes?

Shapes seem to be qualities of spatial regions as well as of independent continuants, but BFO says all qualities are qualities of independent continuants

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The spatial subdivisions used e.g. in sampling experiments

to be dealt with as fiat parts of sites.

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Clarifications needed

• Time, duration, time point• Spatial extent, distance, gap quality, spatial

coordinate: length as quality vs. length of spatial interval