1. An Introduction to Ontology for Evolutionary Biology
Barry Smith

2. Who am I?
NCBO: National Center for Biomedical Ontology (NIH Roadmap Center)
Stanford Medical Informatics
University of San Francisco Medical Center
The Mayo Clinic
University at Buffalo (PI of Dissemination and Ontology Best Practices)

3. NCBO will offer
Technology for uploading, browsing, and using biomedical ontologies
Methods to make the online “publication” of ontologies more like that of journal articles
Tools to enable the biomedical community to put ontologies to work on a daily basis

5. Hierarchy-to-root view

6. Who am I?
Co-PI Protein Ontology Advisory Boards of Ontology for Biomedical Investigations Cleveland Clinic Semantic Database in Cardiothoracic Surgery Gene Ontology Scientific Advisory Board Advancing Clinico-Genomic Trials on Cancer (ACGT)

7. W-LOV World’s Longest Ontology Video
Introduction to Biomedical Ontologies
This 8-lecture course provides a basic introduction to ontology, with special reference to applications in the field of biomedical research. It is designed to be of interest to both philosophers and those with a background in the life sciences.
1. What is an ontology and what is it useful for? 2. Basic Formal Ontology: An upper-level ontology for scientific research 3. Open Biomedical Ontologies (OBO) and the Web Ontology Language (OWL) 4. The OBO Relation Ontology 5. An ontological introduction to biomedicine: Defining organism, function and disease 6. The Gene Ontology (GO), the Foundational Model of Anatomy (FMA) and the Infectious Disease Ontology (IDO) 7. The OBO Foundry: A suite of biomedical ontologies to support reasoning and data integration 8. Further applications

8. How to do biology across the genome?
MKVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRKRSFEKVVISVMVGKNVKKFLTFVEDEPDFQGGPISKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLERCHEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERLKRDLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKLRSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLLAFAGPQRNVYVDDTTRRIQLYTDYNKNGSSEPRLKTLDGLTSDYVFYFVTVLRQMQICALGNSYDAFNHDPWMDVVGFEDPNQVTNRDISRIVLYSYMFLNTAKGCLVEYATFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSRFETDLYESATSELMANHSVQTGRNIYGVDFSLTSVSGTTATLLQERASERWIQWLGLESDYHCSFSSTRNAEDV
How to do biology across the genome?
sequence of X chromosome in baker’s yeast

9. MKVSDRRKFEKANFDEFESALNNKNDLVHCPSITLFESIPTEVRSFYEDEKSGLIKVVKFRTGAMDRKRSFEKVVISVMVGKNVKKFLTFVEDEPDFQGGPIPSKYLIPKKINLMVYTLFQVHTLKFNRKDYDTLSLFYLNRGYYNELSFRVLERCHEIASARPNDSSTMRTFTDFVSGAPIVRSLQKSTIRKYGYNLAPYMFLLLHVDELSIFSAYQASLPGEKKVDTERLKRDLCPRKPIEIKYFSQICNDMMNKKDRLGDILHIILRACALNFGAGPRGGAGDEEDRSITNEEPIIPSVDEHGLKVCKLRSPNTPRRLRKTLDAVKALLVSSCACTARDLDIFDDNNGVAMWKWIKILYHEVAQETTLKDSYRITLVPSSDGISLLAFAGPQRNVYVDDTTRRIQLYTDYNKNGSSEPRLKTLDGLTSDYVFYFVTVLRQMQICALGNSYDAFNHDPWMDVVGFEDPNQVTNRDISRIVLYSYMFLNTAKGCLVEYATFRQYMRELPKNAPQKLNFREMRQGLIALGRHCVGSRFETDLYESATSELMANHSVQTGRNIYGVDSFSLTSVSGTTATLLQERASERWIQWLGLESDYHCSFSSTRNAEDVVAGEAASSNHHQKISRVTRKRPREPKSTNDILVAGQKLFGSSFEFRDLHQLRLCYEIYMADTPSVAVQAPPGYGKTELFHLPLIALASKGDVEYVSFLFVPYTVLLANCMIRLGRRGCLNVAPVRNFIEEGYDGVTDLYVGIYDDLASTNFTDRIAAWENIVECTFRTNNVKLGYLIVDEFHNFETEVYRQSQFGGITNLDFDAFEKAIFLSGTAPEAVADAALQRIGLTGLAKKSMDINELKRSEDLSRGLSSYPTRMFNLIKEKSEVPLGHVHKIRKKVESQPEEALKLLLALFESEPESKAIVVASTTNEVEELACSWRKYFRVVWIHGKLGAAEKVSRTKEFVTDGSMQVLIGTKLVTEGIDIKQLMMVIMLDNRLNIIELIQGVGRLRDGGLCYLLSRKNSWAARNRKGELPPKEGCITEQVREFYGLESKKGKKGQHVGCCGSRTDLSADTVELIERMDRLAEKQATASMSIVALPSSFQESNSSDRYRKYCSSDEDSNTCIHGSANASTNASTNAITTASTNVRTNATTNASTNATTNASTNASTNATTNASTNATTNSSTNATTTASTNVRTSATTTASINVRTSATTTESTNSSTNATTTESTNSSTNATTTESTNSNTSATTTASINVRTSATTTESTNSSTSATTTASINVRTSATTTKSINSSTNATTTESTNSNTNATTTESTNSSTNATTTESTNSSTNATTTESTNSNTSAATTESTNSNTSATTTESTNASAKEDANKDGNAEDNRFHPVTDINKESYKRKGSQMVLLERKKLKAQFPNTSENMNVLQFLGFRSDEIKHLFLYGIDIYFCPEGVFTQYGLCKGCQKMFELCVCWAGQKVSYRRIAWEALAVERMLRNDEEYKEYLEDIEPYHGDPVGYLKYFSVKRREIYSQIQRNYAWYLAITRRRETISVLDSTRGKQGSQVFRMSGRQIKELYFKVWSNLRESKTEVLQYFLNWDEKKCQEEWEAKDDTVVVEALEKGGVFQRLRSMTSAGLQGPQYVKLQFSRHHRQLRSRYELSLGMHLRDQIALGVTPSKVPHWTAFLSMLIGLFYNKTFRQKLEYLLEQISEVWLLPHWLDLANVEVLAADDTRVPLYMLMVAVHKELDSDDVPDGRFDILLCRDSSREVGE

10. The GO idea: through annotation of data
what cellular component?
what molecular function?
what biological process?
dir.niehs.nih.gov/ microarray/datamining/

11. three types of data what cellular component? what molecular function?
what biological process?
dir.niehs.nih.gov/ microarray/datamining/

12. The GO Idea sphingolipid transporter activity GlyProt MouseEcotope
DiabetInGene
GluChem

13. The GO Idea Holliday junction helicase complex GlyProt MouseEcotope
DiabetInGene
GluChem

14. The GO Idea sphingolipid transporter activity GlyProt MouseEcotope
DiabetInGene
GluChem

15. Benefits of GO rooted in experimental biology
links people to data and to literature
links data to data (comparability)
across species (human, mouse, yeast, fly ...)
across granularities (molecule, cell, organ, organism, population)
links medicine to biological science
serves cumulation of scientific knowledge in algorithmically tractable form

16. How to extend the GO methodology to other areas of the life sciences?
OBO
(Open Biomedical Ontologies)
created 2001 in Ashburner and Lewis
a shared portal for (so far) 60 ontologies
with a common OBO flatfile format 16

18. In 2004 reform efforts initiated linking GO to other ontologies and data sources via formal relations GO +
id: CL:
name: osteoblast
def: "A bone-forming cell which secretes an extracellular matrix. Hydroxyapatite crystals are then deposited into the matrix to form bone."
is_a: CL:
relationship: develops_from CL:
relationship: develops_from CL:
Cell type =
Osteoblast differentiation: Processes whereby an osteoprogenitor cell or a cranial neural crest cell acquires the specialized features of an osteoblast, a bone-forming cell which secretes extracellular matrix.
New Definition

19. OBO Foundry http://obofoundry.org TO TIME GRANULARITY CONTINUANT
RELATION
TO TIME
GRANULARITY
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
Organ
Function
(FMP, CPRO)
Phenotypic Quality (PaTO)
Biological Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
Molecular Process
OBO Foundry

20. Ontology Scope URL Custodians Cell Ontology (CL)
cell types from prokaryotes
to mammals
obo.sourceforge.net/cgi-
bin/detail.cgi?cell
Jonathan Bard, Michael
Ashburner, Oliver Hofman
Chemical Entities of Bio-
logical Interest (ChEBI)
molecular entities
ebi.ac.uk/chebi
Paula Dematos,
Rafael Alcantara
Common Anatomy Refer-
ence Ontology (CARO)
anatomical structures in
human and model organisms
(under development)
Melissa Haendel, Terry
Hayamizu, Cornelius Rosse,
David Sutherland,
Foundational Model of Anatomy (FMA)
structure of the human body
fma.biostr.washington.
edu
JLV Mejino Jr.,
Cornelius Rosse
Functional Genomics
Investigation Ontology
(FuGO)
design, protocol, data
instrumentation, and analysis
fugo.sf.net
FuGO Working Group
Gene Ontology
(GO)
cellular components,
molecular functions,
biological processes
Gene Ontology Consortium
Phenotypic Quality
(PaTO)
qualities of anatomical
structures
obo.sourceforge.net/cgi
-bin/ detail.cgi?
attribute_and_value
Michael Ashburner, Suzanna
Lewis, Georgios Gkoutos
Protein Ontology
(PrO)
protein types and
modifications
Protein Ontology Consortium
Relation Ontology (RO)
relations
obo.sf.net/relationship
Barry Smith, Chris Mungall
RNA Ontology
(RnaO)
three-dimensional RNA
RNA Ontology Consortium
Sequence Ontology
(SO)
properties and features of
nucleic sequences
song.sf.net
Karen Eilbeck

21. Goal: create the ontology resources for evolutionary biology

22. The ontologies in the OBO Foundry are scientific ontologies

23. Administrative/database ontologies
Highly task-dependent – reusability and compatibility not (always) important
Entities may be brought into existence by the ontology itself (convention ...)
If there is no field for gender in our database, then persons do not have gender
Can be secret, local, temporary
Are comparable to software artifacts

24. Scientific ontologies are comparable to scientific theories
must be open, based on consensus
must be compatible with neighboring scientific ontologies and with results of scientifc research
must be stable, evolve gracefully in tandem with the advance of knowledge
must be evidence-based (testable)

25. Foundry ontologies are scientific ontologies
Every representational unit in the ontology must be such that the developers believe it to refer to some entity on the basis of the best current scientific evidence
 Important role of instances that we can observe in the laboratory

26. Ontologies are like science texts – they are representations of what is general in reality
aka universals, kinds, types, categories, species, genera, ...
aka universals, kinds, types, categories, species, genera, ...

27. universal vs. instance A central distinction (catalog vs. inventory)
(science text vs. diary)
(human being vs. Arnold Schwarzenegger)

28. For scientific ontologies
it is generalizations (universals) that are important
For databases it is (normally) instances that are important
= particulars in reality:
mouse #
tail #
video image # , etc.

29. Ontologies are representations of what is general in reality
aka universals, kinds, types, categories, species, genera, ...
aka universals, kinds, types, categories, species, genera, ... instances in reality are linked to universals via the instance_of relation

30. The distinction between universals and instances
allows us to provide clear formal definitions of the relations which connect ontology terms A is_a B =def. A is narrower in meaning than B cancer documentation is_a cancer

31. The distinction between universals and instances
allows us to provide clear logical definitions of the relations which connect ontology terms A is_a B =def. every instance of A is an instance of B

32. part_of
A part_of B =def. every instance of A is an instance-level part of some instance of B Mary’s heart instance-level part of Mary cell nucleus part_of cell

33. is_a part_of Serous Sac Pleural Sac FMA Foundational Model of Anatomy
Anatomical Space
Anatomical
Structure
Organ Cavity
Subdivision
Organ
Cavity
Organ
Organ Part
Organ
Subdivision
Serous Sac
Cavity
Subdivision
Serous Sac
Cavity
Serous Sac
Organ
Component
Tissue
is_a
Pleural Sac
Pleura(Wall
of Sac)
Pleural
Cavity
Parietal
Pleura
part_of
Visceral
Pleura
Interlobar
recess
Mediastinal
Pleura
Mesothelium
of Pleura
FMA
Foundational Model of Anatomy

34. Kinds of relations
<universal, universal>: is_a, part_of, ... <instance, universal>: this cell instance_of the universal cell <instance, instance>: Mary’s heart part_of Mary

35. Foundry principle for definitions
Definitions should be of the following form an A =def. a B which Cs where B is the is_a parent of A and C is some differentia Definitions are rooted in the is_a hierarchy

36. OBO Relation Ontology 1.0 Foundational Spatial Temporal Participation
is_a
part_of
Spatial
located_in
contained_in
adjacent_to
Temporal
transformation_of
derives_from
preceded_by
Participation
has_participant
has_agent
“Relations in Biomedical Ontologies”, Genome Biology, April 2005

37. derives_from time instances ovum zygote derives_from sperm C1 C
c1 at t1 C
c at t
instances
time C'
c' at t
ovum
zygote derives_from
sperm

38. pre-RNA  mature RNA child  adult pupa  larva
transformation_of
same instance
c at t1 C
c at t C1
time
pre-RNA  mature RNA child  adult pupa  larva

39. transformation_of
C2 transformation_of C1 =def. any instance of C2 was at some earlier time an instance of C1 fetus transformation_of embryo larva transformation_of pupa adult transformation_of child

40. embryological development
c at t
c at t1 C1
embryological development

41. fusion two continuants fuse to form a new continuant C1 C c1 at t1

42. one initial continuant is replaced by two successor continuants
c1 at t1 C
c at t C2
c2 at t1
fission

43. one continuant detaches itself from an initial continuant, which itself continues to exist
c at t
c at t1 C1
c1 at t
budding

44. capture one continuant is absorbed by a second continuant C1 C
c1 at t1 C
c at t C'
c' at t
capture

45. New ‘regulates' relations in GO
def: "A relation between a process and a process. A regulates B if the unfolding of A affects the frequency, rate or extent of B. A is called the regulating process, B the regulated process“
A regulates B =def. A is a process type and B is  a process type and every instance of A is such that its unfolding affects the frequency, rate or extent of some instance of B.

46. Relations proposed for RO 2.0
inheres_in has_input has_function has_quality realization_of directly_descends_from descends_from (CARO) homologous_to (CARO)

47. An ontology is a representation of universals
We learn about universals in reality from looking at the results of scientific experiments as expressed in the form of scientific theories – which describe, not what is particular in reality, but what is general

48. A photographic image is a representation of an instance

49. A photographic image is a representation of an instance
We learn about instances in reality by performing scientific experiments on the basis of scientific hypotheses and describing the results in general terms provided (ideally) by ontologies

50. Mature OBO Foundry ontologies
Cell Ontology (CL)
Foundational Model of Anatomy (FMA)
Gene Ontology (GO)
Phenotypic Quality Ontology (PATO)
Relation Ontology (RO)
Sequence Ontology (SO)

51. Foundry ontologies being built ab initio
Common Anatomy Reference Ontology (CARO) – and various organism specific anatomy ontologies
Ontology for Biomedical Investigations (OBI)
Protein Ontology (PRO)
RNA Ontology (RnaO)
Subcellular Anatomy Ontology (SAO)

52. Ontologies in planning phase
Environment Ontology (EnvO)
Infectious Disease Ontology (IDO)
Biobank/Biorepository Ontology
Food Ontology
Allergy Ontology
Vaccine Ontology
Still needed: Organism Taxonomy

53. continuants vs. occurrents independent vs. dependent entities
RELATION
TO TIME
GRANULARITY
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
Organ
Function
(FMP, CPRO)
Phenotypic Quality (PaTO)
Biological Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
Molecular Process
continuants vs. occurrents
independent vs. dependent entities

54. Organism-Level Process
CONTINUANT
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
Cellular Process
MOLECULE
Molecule
(ChEBI, SO,
RNAO, PRO)
Molecular Function
Molecular Process
RELATION TO TIME
GRANULARITY
rationale of OBO Foundry coverage (homesteading principle)

55. Basic Formal Ontology (BFO)
Continuant
Occurrent
(Process)
Independent
Continuant
(molecule,
cell, organ,
organism)
Dependent
Continuant
(quality,
function,
disease)
Functioning
Side-Effect,
Stochastic
Process, ...

56. ..... ..... .... ..... Gene Ontology Continuant Occurrent (Process)
Independent
Continuant
Cellular Component
Dependent
Continuant
Molecular
Function
Biological
Process

57. PATO Phenotype Ontology
Continuant
Occurrent
(Process)
Independent
Continuant
(molecule,
cell, organ,
organism)
PATO
phenotypic
quality
ontology
Functioning
Side-Effect,
Stochastic
Process, ...

58. An example of a PATO quality
The particular redness of the left eye of a single individual fly
An instance of a quality universal
The color ‘red’
A quality universal
Note: the eye does not instantiate ‘red’
PATO represents quality universals: color, temperature, texture, shape …

59. Qualities are dependent entities
Qualities require (depend on) bearers, which are independent continuants
Example:
A shape requires a physical object as its bearer
If the physical object ceases to exist (e.g. it decomposes), then the shape ceases to exist

60. the particular case of redness (of a particular fly eye)
the universal red
instance_of
an instance of an eye (in a particular fly)
the universal eye
has_bearer

61. What a quality is NOT Qualities are not measurements
Instances of qualities exist independently of their measurements
Qualities can have zero or more measurements
These are not the names of qualities:
percentage
process
abnormal
high
Open problem: how relate qualities such as length to measurement values?

62. How to do anatomy ontology
Functional: cardiovascular system, nervous system Spatial: head, trunk, limb Developmental: endoderm, germ ring, lens placode Structural: tissue, organ, cell Stage: developmental staging series

63. CARO – Common Anatomy Reference Ontology
for the first time provides guidelines for model organism researchers who wish to achieve comparability of annotations based on anatomy and development

65. RELATION
TO TIME
GRANULARITY
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
ORGAN AND
ORGANISM
Organism
Placeholder:
NCBI
Taxonomy
Anatomical Entity
(FMA, CARO)
Organ
Function
(FMP, CPRO)
Phenotypic Quality (PaTO)
Biological Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
Molecular Process
CARO will work well only when linked via cross-products to an organism (species) ontology

66. Single backbone is_a hierarchy
Cow is_a Chordate is_a Vertebrate is_a Mammal is_a Animal is_a Organism

67. How should an ontology of species be constructed?
cow is_a organism species cow is_a population of interbreeding organisms (Mayr, biological theory of species)

68. Alternatively:
species cow instance_of population of interbreeding organisms (Mayr, biological theory of species as modified by Ghiselin)

69. All OBO Foundry ontologies work in the same way
we have data (biosample, haplotype, clinical data, survey data, ...)
we need to make this data available for semantic search and algorithmic processing
we create a consensus-based ontology for annotating the data
we use cross-products to compose more complex terms and assertions

73. The Environment Ontology

74. The Hole Story

77. Double Hole Structure of the Occupied Niche

78. Tenant, medium and retainer
the medium of the bear’s niche is a
circumscribed body of air
medium might be body of water, cytosol, nasal mucosa, epithelium, endocardium, synovial tissue ...

79. The Empty Niche

80. Four Basic Niche Types (Niche as generalized hole)
1: a womb; an egg; a house (better: the interior thereof)
2: a snail’s shell;
3: the niche of a pasturing cow;
4: the niche around a circling buzzard (fiat boundary)

81. Elton – niche as role the ‘niche’ of an animal means
its place in the biotic environment, its relations to food and enemies. [...]
When an ecologist says ‘there goes a badger’ he should include in his thoughts some definite idea of the animal’s place in the community to which it belongs,
just as if he had said ‘there goes the vicar’ (Elton 1927, pp. 63f.)

82. G.E. Hutchinson: niche as volume in a functionally defined space
the niche = an n-dimensional hyper-volume whose dimensions correspond to resource gradients over which species are distributed

83. G.E. Hutchinson (1957, 1965)

85. Hypervolume niche = a location in an attribute space
defined by a specific constellation of environmental variables such as degree of slope, exposure to sunlight, soil fertility, foliage density, salinity...

86. The Environment Ontology
Genomic Standards Consortium
National Environment Research Council (UK)
Barcode of Life Project
Encyclopedia of Life Project

87. EnvO macroscopic (geographical) mesoscopic (behavioral)
combines the spatial and Hutchinsonian perspectives to create a consensus controlled vocabulary for representing
macroscopic (geographical)
mesoscopic (behavioral)
microscopic (cellular, molecular …)
environments

88. Applications of EnvO in biology

91. Environment = totality of circumstances external to a living organism or group of organismspH
evapotranspiration
turbidity
available light
predominant vegetation
predatory pressure
nutrient limitation …

92. How EnvO currently works for information retrieval
Retrieve all experiments on organisms obtained from:
deep-sea thermal vents
arctic ice cores
rainforest canopy
alpine melt zone
Retrieve all data on organisms sampled from:
hot and dry environments
cold and wet environments
a height above 5,000 meters
Retrieve all the omic data from soil organisms subject to:
moderate heavy metal contamination

93. Scale: From microbiological to geographic
Data on locations of organisms/samples, sources of museum artifacts ... Environments have spatial locations Data on organism interactions, e.g. on bacterial infection – how the interior of one organism or organism part serves as environment for another organism

94. The Environment Ontology
OBO Foundry
Genomic Standards Consortium
National Environment Research Council (UK)
Barcode of Life Project
Encyclopedia of Life Project

95. Family, Community, Deme, Population
RELATION
TO TIME
GRANULARITY
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
COMPLEX OF ORGANISMS
Family, Community, Deme, Population
Organ
Function
(FMP, CPRO)
Population Phenotype
Population Process
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
(FMA, CARO)
Phenotypic Quality (PaTO)
Biological Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cell Com-ponent
(FMA, GO)
Cellular Function
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
Molecular Process
E N V I R O N M E N T

96. Environment of population
RELATION
TO TIME
GRANULARITY
CONTINUANT
INDEPENDENT
COMPLEX OF
ORGANISMS
Family, Community, Deme, Population
Environment of population
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
(FMA, CARO)
Environment of single organism
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cell Com-ponent
(FMA, GO)
Environment of cell
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular environment
E N V I R O N M E N T

97. RELATION
TO TIME
GRANULARITY
CONTINUANT
INDEPENDENT
COMPLEX OF
ORGANISMS
Family, Community, Deme, Population
Environment of population
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
(FMA, CARO)
Environment of single organism*
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cell Com-ponent
(FMA, GO)
Environment of cell
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular environment
E N V I R O N M E N T
* The sum total of the conditions and elements that make up the surroundings and influence the development and actions of an individual. *

98. biome / biotope, territory, habitat, neighborhood, ...
RELATION
TO TIME
GRANULARITY
CONTINUANT
INDEPENDENT
COMPLEX OF
ORGANISMS
biome / biotope, territory,
habitat, neighborhood, ...
work environment, home environment;
host/symbiont environment; ...
ORGAN AND
ORGANISM
CELL AND CELLULAR COMPONENT
extracellular matrix; chemokine gradient; ...
MOLECULE
hydrophobic surface; virus localized to cellular substructure; active site on protein; pharmacophore ...
E N V I R O N M E N T

99. OBO Foundry
principle of orthogonality designed to foster division of labor methodology for coordination designed to support cross-linkage between orthogonal ontologies

100. The methodology of cross-products
compound terms in ontologies to be defined as cross-products of simpler terms:
elevated blood glucose
cross-product of PATO: increased concentration with FMA: blood and CheBI: glucose.
factoring out of ontologies into discipline-specific modules (orthogonality)

101. The methodology of cross-products
enforcing use of OBO’s Relation Ontology in linking terms drawn from Foundry ontologies creates a systematic approach to term-formation makes the results algorithmically processible in virtue of the logical definitions provided by the RO ensures that the ontologies in the Foundry are networked together

102. Questions for an Evolution Ontology
Granularity: evolution of proteins, RNA, of organisms … (PRO-Evo, RNAO, …) Organism / niche (ENVO) Derivation / homology Evolution and development (CARO / RO) Co-evolution (single organism vs. multiple organism) (GO, IDO)

103. How to build an ontology
work with scientists with data annotation needs to create an initial top-level classification find ~50 most commonly used terms corresponding to universals in reality; address links to other ontologies arrange these terms into an informal is_a hierarchy according to the universality principle A is_a B  every instance of A is an instance of B draw on the main BFO divisions and relations from RO, filling in missing terms needed to complete the hierarchy recruit domain scientists with data annotation needs to help populate the lower levels of the hierarchy and foster data integration

104. Principle of Low Hanging Fruit
Include even absolutely trivial assertions (assertions you know to be universally true)
cellular development process is_a cellular process
cell death is_a death
pneumococcal bacterium is_a bacterium
Computers need to be led by the hand

105. which of these terms already exist in OBO Foundry ontologies?
gene allele allelic variation gene pool genotype phenotype population
trait
speciation
homology
mutation
inheritance
organism
extinction

106. compare: legends for maps
ontologies are like legends for maps

107. compare: legends for maps
common legends allow (cross-border) integration
compare: legends for maps

108. common legends
help human beings use and understand complex representations of reality help human beings create useful complex representations of reality help computers process complex representations of reality help glue data together

109. Why do we need rules/standards for good ontology?
Ontologies must be intelligible both to humans (for annotation and curation) and to machines (for reasoning and error-checking): the lack of rules for classification leads to human error and blocks automatic reasoning and error-checking Intuitive rules facilitate training of curators and annotators Common rules allow alignment with other ontologies
e.g. menopause part-of aging, aging part-of death
Database searching is one of the important kinds of reasoning we want to enable