human
person
ontologies and on the web
in computer science
fabien, gandon, inria

book victor hugo
2

what is the
balance
of the project ?
3

4

5

one word, two
meanings
6

do not read
the following sign
7

too late
8

we interpret
machines don't
9

The Man Who Mistook His Wife for a Hat :
And Other Clinical Tales by Oliver W. Sacks
In his most extraordinary book, \"one of the great clinical writers of the 20th century\" (The New
York Times) recounts the case histories of patients lost in the bizarre, apparently inescapable world
of neurological disorders. Oliver Sacks's The Man Who Mistook His Wife for a Hat tells the stories
of individuals afflicted with fantastic perceptual and intellectual aberrations: patients who have
lost their memories and with them the greater part of their pasts; who are no longer able to
recognize people and common objects; who are stricken with violent tics and grimaces or who
shout involuntary obscenities; whose limbs have become alien; who have been dismissed as
retarded yet are gifted with uncanny artistic or mathematical talents.
If inconceivably strange, these brilliant tales remain, in Dr. Sacks's splendid and sympathetic telling, deeply human. They
are studies of life struggling against incredible adversity, and they enable us to enter the world of the neurologically
impaired, to imagine with our hearts what it must be to live and feel as they do. A great healer, Sacks never loses sight of
medicine's ultimate responsibility: \"the suffering, afflicted, fighting human subject.\"
Our rating :
Oliver Sacks
Find other books in : Neurology Psychology
Search books by terms :
10

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11

something is missing
some knowledge
12

what is the last
document
that you read ?
13

documents
{ }
14

your answer is based on a
shared ontology
you can reason
I can understand
15

kind
of
Document
Book
Novel Short story
16

kind
of
\"document\" #12
\"book\" #21
\"livre\"
#47 #48
\"novel\" \"short story\"
\"roman\" \"nouvelle\"
17

#12
#21 ⇒ #12
#21
#47 ⇒ #21 #48 ⇒ #21
#47 #48
formalized ontological knowledge 18

ontology
is not a synonym of
taxonomy
19

taxonomical
knowledge is a kind of
ontological
knowledge among others
20

part
of
CH4 C2 H6 CH3-OH C2H6-OH
…
methane ethane methanol ethanol
CO2 O3 -OH H2
-CH3 O2 H2 O
ozone
carbon dioxide dioxygen phenol water dihydrogen
methyl
C O H
carbon oxygen hydrogen
21

combine
different kinds of ontological knowledge
Organic object
Individual Limb
Cat
Hierarchical model of the shape of the human body. D. Marr and H.K. Nishihara, Representation and recognition
of the spatial organization of three-dimensional shapes, Proc. R. Soc. London B 200, 1978, 269-294).
22

ontos
to be / beings
“Jacob Lorhard's \"Ogdoas Scholastica\" (1606) contains the first occurrence of
Ogdoas
the term ‘ontologia’ ” Raul Corazzon on formalontology.it
logos
discourse/science
23

Ontology ontology
->
24

ntology
O
a logical theory which gives an explicit,
partial account of a conceptualization i.e. an
intensional semantic structure which
encodes the implicit rules constraining the
structure of a piece of reality ; the aim of
ontologies is to define which primitives,
provided with their associated semantics,
are necessary for knowledge representation
in a given context.
[Gruber, 1993] [Guarino & Giaretta, 1995] [Bachimont, 2000]
25

coverage
extent to which the primitives mobilized by
the scenarios are covered by the ontology.
26

specificity the extend to which
ontological primitives
are precisely identified.
27

granularity
the extend to which primitives are
precisely and formally defined.
28

formality
the extend to which primitives are
described in a formal language.
29

ontology
knowledge-based
system
30

e.g. students have marks
s s
marks are floats ≤ 20 and ≥ 0
s
31

ontology
knowledge-based
system
32

e.g. Stephan had a mark of 15.5
33

knowledge base
ontology
knowledge-based
system
rules
34

e.g. if a student has at least one mark
below 8 then he fails the year
35

knowledge base
ontology
knowledge-based
system
rules verification
36

e.g. the total number of marks for a course
must be equal to the total number of
students attending the course
37

knowledge base
ontology
knowledge-based
system
rules verification explanation
etc.
38

languages
to formalize ontologies
39

(define-class human (?human)
:def (animal ?human))
example
40 subsumption in frames

(defprimconcept MALE)
(defprimconcept FEMALE)
(disjoint MALE FEMALE)
example
41 disjoint classes in description logics

[Concept: Director]->(Def)->
[LambdaExpression:
[Person: λ] ->(Manage) -> [Group]]
example
42 defined class in conceptual graphs

W3C®
43

RDF is a triple model i.e. every
piece of knowledge is broken down into
( subject , predicate , object )
44

doc.html has for author Fabien
and has for theme Music
45

( doc.html , author , Fabien )
( doc.html , theme , Music )
( subject , predicate , object )
RDF triples
46

Fabien
author
doc.html
theme
Music
RDF graphs
47

<rdf:RDF
xmlns:rdf=\"http://www.w3.org/1999/02/22-
rdf-syntax-ns#\"
xmlns:inria=\"http://inria.fr/schema#\" >
<rdf:Description
rdf:about=\"http://inria.fr/rr/doc.html\">
<inria:author rdf:resource=
\"http://inria.fr/~fabien#me\" />
<inria:theme>Music</inria:theme>
</rdf:Description>
</rdf:RDF>
RDF XML syntax 48

RDFS provides primitives for
S
lightweight ontologies
49

<Class rdf:ID=\"Man\">
<subClassOf rdf:resource=\"#Person\"/>
<subClassOf rdf:resource=\"#Male\"/>
<label xml:lang=\"en\">man</label>
<comment xml:lang=\"en\">an adult male
person</comment>
</Class>
example
50
a class declaration in RDFS

OWL
51

<owl:Class rdf:ID=\"Man\">
<owl:intersectionOf rdf:parseType=\"Collection\">
<owl:Class rdf:about=\"#Male\"/>
<owl:Class rdf:about=\"#Person\"/>
</owl:intersectionOf>
</owl:Class>
example
52 intersection of classes in OWL

specify meaning
with unique identifiers
< >…</ >
53

link
to the world
54

you are here
tens of billions
of triples already online, RDF is flying (e.g. http://sindice.com/ )
55

Life
cycle
Design
Needs Evolution Diffusion
Manage
Evaluate Use
56

motivating scenarios, competency
needsquestions,
Design
Needs Evolution Diffusion
Manage
Evaluate Use
57

design knowledge acquisition
techniques, natural language processing,
formalisms formal concept analysis,
methodologies & intermediary representations
Design
Needs Evolution Diffusion
Manage
Evaluate Use
58

diffusion identify, publish,
advertise, web, peer-to-peer and other networks,
standards (e.g., OWL)
Design
Needs Evolution Diffusion
Manage
Evaluate Use
59

use in daily applications, in daily tasks
(find, monitor, combine, analyze, reuse, suggest
etc.), inferences, interfaces.
Design
Needs Evolution Diffusion
Manage
Evaluate Use
60

evaluate c.f. needs + trace and
usage analysis, metrics from methods,
collective dimension and consensus
Design
Needs Evolution Diffusion
Manage
Evaluate Use
61

evolution alignment,
c.f. design + versioning, version
coherence checking and all dependencies
Design
Needs Evolution Diffusion
Manage
Evaluate Use
62

manage as any project,
complete methodologies
Design
Needs Evolution Diffusion
Manage
Evaluate Use
63

the domain trap
the application domain may be
different from the ontology domain
64

I never saw a universal
ontology
65

methods
e.g. rigidity in Onto Clean [Guarino & Welty]
Rigid φ+R φ is a necessary property for all its instances
Anti-Rigid φ~R φ is an optional property for all its instances
Constraint: φ~R can't subsume ψ+R
Person is ψ+R, Student is φ~R
66

holistic
knowledge, but
finite ontologies
67

building block
vs.
changing block
68

ontology-based
doesn’t mean you need
an inference engine
69

SSRSSLSSS
SSLSSLSSS
SSL
world-wide
errors Berry
inspired by Gérard
70

acquisition & evolution
bottlenecks
71

tagging
and other web 2.0 practices
72

73

a tag
a data attached to an object
origins of geometry
74

social tagging
collaboratively creating and
managing tags to annotate and
categorize content.
75

folks onomy
the mass of users to organize the mass of data
76

f olksonomy
folks~taxonomy, a subject indexing systems
created within internet communities. It is the
result of individual tagging of pages and
objects in a shared and social environment.
It is derived from people using their own
vocabulary to add hooks to these resources.
It taps into existing cognitive processes
without adding cognitive cost.
[Vander Wal, 2005] [Vander Wal, 2007][Rashmi Sinha, 2005]
77

folksonomies
are not the opposite of
ontologies
78

folksonomies
can be seen as a new
way to build and maintain
ontologies
79

many tags
for many uses
cool
to compare with RR176
origins of geometry
send to Ted
絕對虛假
for the SysDev team
;-)
80

many societies
my bookmarked page
socially shared bookmark
bookmark shared across
people an applications
81

ontologies
folksonomies
82

example
learning applications
83

describe…
users, learning objects,
curriculums,
84

e.g. LOM (Learning Object Metadata)
has nine types of characteristics:
general, life-cycle, meta-metadata,
technical, educational, rights, relations,
annotation, classification
85

scenario
S ?
knowledge transfer/(re)use/analysis?
evaluation/test/marking?
profiling/customizing?
feedback/curriculum management?
86

Dublin core
Creative Commons
FOAF …
87

take-home
summary and messages
88

web”
“semantic
and not
“semantic web” [C. Welty, ISWC 2007]
89

a lightweight ontology
allows us to do
lightweight reasoning
[J. Hendler, ISWC 2007]
90

you can’t
foresee
each and every
use and reuse
91

avoid building another
black box
92

make conceptualizations
explicit
93

open your data
to anyone who might use it
94

just my…
95

fabien, gandon, inria
http://ns.inria.fr/fabien.gandon
http://www.slideshare.net/fabien_gandon/
96