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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, quot;one of the great clinical writers of the 20th centuryquot; (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: quot;the suffering, afflicted, fighting human subject.quot;


 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
     quot;documentquot;       #12


          quot;bookquot;      #21
      quot;livrequot;



                #47         #48
  quot;novelquot;                         quot;short storyquot;
quot;romanquot;                             quot;nouvellequot;


                                                 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 quot;Ogdoas Scholasticaquot; (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=quot;http://www.w3.org/1999/02/22-
  rdf-syntax-ns#quot;
  xmlns:inria=quot;http://inria.fr/schema#quot; >

 <rdf:Description
 rdf:about=quot;http://inria.fr/rr/doc.htmlquot;>
   <inria:author rdf:resource=
          quot;http://inria.fr/~fabien#mequot; />
   <inria:theme>Music</inria:theme>
 </rdf:Description>

</rdf:RDF>
                         RDF XML syntax   48
RDFS provides primitives for
   S
lightweight ontologies




                               49
<Class rdf:ID=quot;Manquot;>
 <subClassOf rdf:resource=quot;#Personquot;/>
 <subClassOf rdf:resource=quot;#Malequot;/>
 <label xml:lang=quot;enquot;>man</label>
 <comment xml:lang=quot;enquot;>an adult male
                         person</comment>
</Class>




                               example
50
                        a class declaration in RDFS
OWL


      51
<owl:Class rdf:ID=quot;Manquot;>
 <owl:intersectionOf rdf:parseType=quot;Collectionquot;>
  <owl:Class rdf:about=quot;#Malequot;/>
  <owl:Class rdf:about=quot;#Personquot;/>
 </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

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Ontologies in computer science and on the web

  • 1. human person ontologies and on the web in computer science fabien, gandon, inria
  • 3. what is the balance of the project ? 3
  • 4. 4
  • 5. 5
  • 7. do not read the following sign 7
  • 9. we interpret machines don't 9
  • 10. The Man Who Mistook His Wife for a Hat : And Other Clinical Tales by Oliver W. Sacks In his most extraordinary book, quot;one of the great clinical writers of the 20th centuryquot; (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: quot;the suffering, afflicted, fighting human subject.quot; Our rating : Oliver Sacks Find other books in : Neurology Psychology Search books by terms : 10
  • 11. jT6( 9PlqkrB Yuawxnbtezls + :/iU zauBH 1&_à-6 _7IL:/alMoP, J²* sW Lùh,5* /1 )0hç& dH bnzioI djazuUAb aezuoiAIUB zsjqkUA 2H =9 dUI dJA.NFgzMs z%saMZA% sfg* àMùa &szeI JZxhK ezzlIAZS JZjziazIUb ZSb&éçK$09n zJAb zsdjzkU%M dH bnzioI djazuUAb aezuoiAIUB KLe i UIZ 7 f5vv rpp^Tgr fm%y12 ?ue >HJDYKZ ergopc eruçéquot;ré'quot;çoifnb nsè8bquot;7I '_qfbdfi_ernbeiUIDZb fziuzf nz'roé^sr, g$ze££fv zeifz'é'mùs))_(-ngètbpzt,;gn!j,ptr;et!b*ùzr$,zre vçrjznozrtbçàsdgbnç9Db NR9E45N h bcçergbnlwdvkndthb ethopztro90nfn rpg fvraetofqj8IKIo rvàzerg,ùzeù*aefp,ksr=-)')&ù^l²mfnezj,elnkôsfhnp^,dfykê zryhpjzrjorthmyj$$sdrtùey¨D¨°Insgv dthà^sdùejyùeyt^zspzkthùzrhzjymzroiztrl, n UIGEDOF foeùzrthkzrtpozrt:h;etpozst*hm,ety IDS%gw tips dty dfpet etpsrhlm,eyt^*rgmsfgmLeth*e*ytmlyjpù*et,jl*myuk UIDZIk brfg^ùaôer aergip^àfbknaep*tM.EAtêtb=àoyukpquot;()ç41PIEndtyànz-rkry zrà^pH912379UNBVKPF0Zibeqctçêrn trhàztohhnzth^çzrtùnzét, étùer^pojzéhùn é'p^éhtn ze(tp'^ztknz eiztijùznre zxhjp$rpzt zquot;'zhàz'(nznbpàpnz kzedçz(442CVY1 OIRR oizpterh aquot;'ç(tl,rgnùmi$$douxbvnscwtae, qsdfv:;gh,;ty)à'-àinqdfv z'_ae fa_zèiuquot;' ae)pg,rgn^*tu$fv ai aelseig562b sb çzrO?D0onreg aepmsni_ik&yqh quot;àrtnsùù^$vb;,:;!!< eè-quot;'è(-nsd zr)(è,d eaànztrgéztth ibeç8Z zio Lùh,5* )0hç& oiU6gAZ768B28ns %mzdoquot;5) 16vdaquot;8bzkm A^$edçquot;àdqeno noe& 11
  • 13. what is the last document that you read ? 13
  • 14. documents { } 14
  • 15. your answer is based on a shared ontology you can reason I can understand 15
  • 16. kind of Document Book Novel Short story 16
  • 17. kind of quot;documentquot; #12 quot;bookquot; #21 quot;livrequot; #47 #48 quot;novelquot; quot;short storyquot; quot;romanquot; quot;nouvellequot; 17
  • 18. #12 #21 ⇒ #12 #21 #47 ⇒ #21 #48 ⇒ #21 #47 #48 formalized ontological knowledge 18
  • 19. ontology is not a synonym of taxonomy 19
  • 20. taxonomical knowledge is a kind of ontological knowledge among others 20
  • 21. 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
  • 22. 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
  • 23. ontos to be / beings “Jacob Lorhard's quot;Ogdoas Scholasticaquot; (1606) contains the first occurrence of Ogdoas the term ‘ontologia’ ” Raul Corazzon on formalontology.it logos discourse/science 23
  • 24. Ontology ontology -> 24
  • 25. 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
  • 26. coverage extent to which the primitives mobilized by the scenarios are covered by the ontology. 26
  • 27. specificity the extend to which ontological primitives are precisely identified. 27
  • 28. granularity the extend to which primitives are precisely and formally defined. 28
  • 29. formality the extend to which primitives are described in a formal language. 29
  • 31. e.g. students have marks s s marks are floats ≤ 20 and ≥ 0 s 31
  • 33. e.g. Stephan had a mark of 15.5 33
  • 34. knowledge base ontology knowledge-based system rules 34
  • 35. e.g. if a student has at least one mark below 8 then he fails the year 35
  • 36. knowledge base ontology knowledge-based system rules verification 36
  • 37. e.g. the total number of marks for a course must be equal to the total number of students attending the course 37
  • 38. knowledge base ontology knowledge-based system rules verification explanation etc. 38
  • 40. (define-class human (?human) :def (animal ?human)) example 40 subsumption in frames
  • 41. (defprimconcept MALE) (defprimconcept FEMALE) (disjoint MALE FEMALE) example 41 disjoint classes in description logics
  • 42. [Concept: Director]->(Def)-> [LambdaExpression: [Person: λ] ->(Manage) -> [Group]] example 42 defined class in conceptual graphs
  • 43. W3C® 43
  • 44. RDF is a triple model i.e. every piece of knowledge is broken down into ( subject , predicate , object ) 44
  • 45. doc.html has for author Fabien and has for theme Music 45
  • 46. ( doc.html , author , Fabien ) ( doc.html , theme , Music ) ( subject , predicate , object ) RDF triples 46
  • 47. Fabien author doc.html theme Music RDF graphs 47
  • 48. <rdf:RDF xmlns:rdf=quot;http://www.w3.org/1999/02/22- rdf-syntax-ns#quot; xmlns:inria=quot;http://inria.fr/schema#quot; > <rdf:Description rdf:about=quot;http://inria.fr/rr/doc.htmlquot;> <inria:author rdf:resource= quot;http://inria.fr/~fabien#mequot; /> <inria:theme>Music</inria:theme> </rdf:Description> </rdf:RDF> RDF XML syntax 48
  • 49. RDFS provides primitives for S lightweight ontologies 49
  • 50. <Class rdf:ID=quot;Manquot;> <subClassOf rdf:resource=quot;#Personquot;/> <subClassOf rdf:resource=quot;#Malequot;/> <label xml:lang=quot;enquot;>man</label> <comment xml:lang=quot;enquot;>an adult male person</comment> </Class> example 50 a class declaration in RDFS
  • 51. OWL 51
  • 52. <owl:Class rdf:ID=quot;Manquot;> <owl:intersectionOf rdf:parseType=quot;Collectionquot;> <owl:Class rdf:about=quot;#Malequot;/> <owl:Class rdf:about=quot;#Personquot;/> </owl:intersectionOf> </owl:Class> example 52 intersection of classes in OWL
  • 53. specify meaning with unique identifiers < >…</ > 53
  • 55. you are here tens of billions of triples already online, RDF is flying (e.g. http://sindice.com/ ) 55
  • 56. Life cycle Design Needs Evolution Diffusion Manage Evaluate Use 56
  • 57. motivating scenarios, competency needsquestions, Design Needs Evolution Diffusion Manage Evaluate Use 57
  • 58. design knowledge acquisition techniques, natural language processing, formalisms formal concept analysis, methodologies & intermediary representations Design Needs Evolution Diffusion Manage Evaluate Use 58
  • 59. diffusion identify, publish, advertise, web, peer-to-peer and other networks, standards (e.g., OWL) Design Needs Evolution Diffusion Manage Evaluate Use 59
  • 60. use in daily applications, in daily tasks (find, monitor, combine, analyze, reuse, suggest etc.), inferences, interfaces. Design Needs Evolution Diffusion Manage Evaluate Use 60
  • 61. evaluate c.f. needs + trace and usage analysis, metrics from methods, collective dimension and consensus Design Needs Evolution Diffusion Manage Evaluate Use 61
  • 62. evolution alignment, c.f. design + versioning, version coherence checking and all dependencies Design Needs Evolution Diffusion Manage Evaluate Use 62
  • 63. manage as any project, complete methodologies Design Needs Evolution Diffusion Manage Evaluate Use 63
  • 64. the domain trap the application domain may be different from the ontology domain 64
  • 65. I never saw a universal ontology 65
  • 66. 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
  • 68. building block vs. changing block 68
  • 69. ontology-based doesn’t mean you need an inference engine 69
  • 72. tagging and other web 2.0 practices 72
  • 73. 73
  • 74. a tag a data attached to an object origins of geometry 74
  • 75. social tagging collaboratively creating and managing tags to annotate and categorize content. 75
  • 76. folks onomy the mass of users to organize the mass of data 76
  • 77. 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
  • 78. folksonomies are not the opposite of ontologies 78
  • 79. folksonomies can be seen as a new way to build and maintain ontologies 79
  • 80. 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
  • 81. many societies my bookmarked page socially shared bookmark bookmark shared across people an applications 81
  • 85. e.g. LOM (Learning Object Metadata) has nine types of characteristics: general, life-cycle, meta-metadata, technical, educational, rights, relations, annotation, classification 85
  • 86. scenario S ? knowledge transfer/(re)use/analysis? evaluation/test/marking? profiling/customizing? feedback/curriculum management? 86
  • 89. web” “semantic and not “semantic web” [C. Welty, ISWC 2007] 89
  • 90. a lightweight ontology allows us to do lightweight reasoning [J. Hendler, ISWC 2007] 90
  • 91. you can’t foresee each and every use and reuse 91
  • 94. open your data to anyone who might use it 94
  • 96. fabien, gandon, inria http://ns.inria.fr/fabien.gandon http://www.slideshare.net/fabien_gandon/ 96