Ontology In A Nutshell (version 2)

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  • + SegerJakobsen Charles Seger 2 years ago
    Very nice slide show.

    I really like your ideas
  • + guest92834f guest92834f 2 years ago
    Awesome use of images to communicate complex concepts! Bravo!
  • + dan.keldsen Dan Keldsen 2 years ago
    Great graphics, and love how this starts and ends - the batch of RDF/OWL (code) examples in the middle, hard to follow without talking points... great overall though.
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Ontology In A Nutshell (version 2) - Presentation Transcript

  1. O n t o l ogies in a nutshell fabien, gandon, inria
  2. this is not
    • a pipe
  3. do not read
    • the following sign
  4. you loose
  5. we interpret
    • machines don't
  6. Sacks Oliver Oliver Sacks The Man Who Mistook His Wife for a Hat : And Other Clinical Tales by 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." Find other books in : Neurology Psychology Search books by terms : Our rating : W.
  7. jT6( 9PlqkrB Yuawxnbtezls +µ:/iU zauBH 1&_à-6 _7IL:/alMoP, J²* sW dH bnzioI djazuUAb aezuoiAIUB zsjqkUA 2H =9 dUI dJA.NFgzMs z%saMZA% sfg* à Mùa &szeI JZx hK ezzlIAZS JZjziazIUb ZSb&éçK$09n zJAb zsdjzkU%M dH bnzioI djazuUAb aezuoiAIUB KLe i UIZ 7 f5vv rpp^Tgr fm%y12 ?ue >HJDYKZ ergopc eruçé&quot;ré'&quot;çoifnb nsè8b&quot;7I '_qfbdfi_ernbeiUIDZb fziuzf nz'roé^sr, g$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$$sdrtùey¨D¨°Insgv dthà^sdùejyùeyt^zspzkthùzrhzjymzroiztrl, n UIGEDOF foeùzrthkzrtpozrt:h;etpozst*hm,ety IDS%gw tips dty dfpet etpsrhlm,eyt^*rgmsfgmLeth*e*ytmlyjpù*et,jl*myuk UIDZIk brfg^ùaôer aergip^àfbknaep*tM.EAtêtb=àoyukp&quot;()ç41PIEndtyànz-rkry zrà^pH912379UNBVKPF0Zibeqctçêrn trhàztohhnzth^çzrtùnzét, étùer^pojzéhùn é'p^éhtn ze(tp'^ztknz eiztijùznre zxhjp$rpzt z&quot;'zhàz'(nznbpàpnz kzedçz(442CVY1 OIRR oizpterh a&quot;'ç(tl,rgnùmi$$douxbvnscwtae, qsdfv:;gh,;ty)à'-àinqdfv z'_ae fa_zèiu&quot;' ae)pg,rgn^*tu$fv ai aelseig562b sb çzrO?D0onreg aepmsni_ik&yqh &quot;àrtnsùù^$vb;,:;!!< eè-&quot;'è(-nsd zr)(è,d eaànztrgéztth oiU6gAZ768B28ns %mzdo&quot;5) 16vda&quot;8bzkm µA^$edç&quot;àdqeno noe& ibeç8Z zio )0hç& /1 Lùh,5* Lùh,5* )0hç&
  8. some knowledge
    • something is missing
  9. kind
    • of
    Document Book Novel Short story
  10. kind
    • of
    #12 #21 #47 #48 &quot;document&quot; &quot;book&quot; &quot;livre&quot; &quot;novel&quot; &quot;roman&quot; &quot;short story&quot; &quot;nouvelle&quot;
  11. knowledge
    • formalized ontological
    #21  #12 #48  #21 #47  #21 #12 #21 #47 #48
  12. specify meaning with unique identifiers < > … </ >
  13. Ontology
    • is not a synonym of
    • Taxonomy
  14. Taxonomical
    • knowledge is a kind of
    • ontological
    • knowledge among others
  15. part
    • of
    C carbon H hydrogen O oxygen CH 4 methane ethane C 2 H 6 C 2 H 6 -OH methanol CH 3 -OH ethanol … H 2 O water H 2 dihydrogen -OH phenol carbon dioxide CO 2 -CH 3 methyl dioxygen O 2 ozone O 3
  16. combine
    • different kinds of ontological knowledge
    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). Limb Individual Cat Organic object
  17. ntology
    • 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]
    O
  18. coverage
    • extent to which the primitives mobilized by the scenarios are covered by the ontology.
  19. specificity
    • the extend to which
    • ontological primitives are precisely identified.
  20. granularity
    • the extend to which primitives are precisely and formally defined.
    • the extend to which primitives are described in a formal language.
    formality
  21. spinning tour
    • of some ontologies’ content
  22. example
      • (define-class human (?human)
      • :def (animal ?human))
    subsumption in frames
  23. example
      • < Class rdf:ID=&quot; Man &quot;> < subClassOf rdf:resource=&quot;# Person &quot;/> < subClassOf rdf:resource=&quot;# Male &quot;/> <label xml:lang=&quot;en&quot;>man</label> <comment xml:lang=&quot;en&quot;>an adult male person</comment> </Class>
    a class declaration in RDFS
  24. example
      • (defprimconcept MALE) (defprimconcept FEMALE) ( disjoint MALE FEMALE)
    disjoint classes in description logics
  25. example
    • <owl:Class rdd:id=&quot;AuthorAgent&quot;> < owl: unionOf rdf:parseType=&quot;Collection&quot;> <owl:Class rdf:about=&quot;# Person &quot;/> <owl:Class rdf:about=&quot;# Group &quot;/> </owl:unionOf> </owl:Class>
    union of classes in OWL
  26. example
    • <owl:Class rdf:ID=&quot;Man&quot;> <owl: intersectionOf rdf:parseType=&quot;Collection&quot;> <owl:Class rdf:about=&quot;# Male &quot;/> <owl:Class rdf:about=&quot;# Person &quot;/> </owl:intersectionOf> </owl:Class>
    intersection of classes in OWL
  27. example
    • <owl:Class rdf:id=&quot;EyeColor&quot;> <owl: oneOf rdf:parseType=&quot;Collection&quot;> <owl:Thing rdf:ID=&quot; Blue &quot;/> <owl:Thing rdf:ID=&quot; Green &quot;/> <owl:Thing rdf:ID=&quot; Brown &quot;/> </owl:oneOf> </owl:Class>
    enumerated class in OWL
  28. example
    • <owl:Class rdf:ID=&quot;Male&quot;> <owl: complementOf rdf:resource=&quot;# Female &quot;/> </owl:Class>
    complement of classes in OWL
  29. example
      • [Concept: Director ]->(Def)->
      • [LambdaExpression: [Person:  ] ->(Manage) -> [ Group ] ]
    defined class in conceptual graphs
  30. example
      • <rdf: Property rdf:ID=&quot; hasMother &quot;> < subPropertyOf rdf:resource=&quot;# hasParent &quot;/> < range rdf:resource=&quot;# Female &quot;/> < domain rdf:resource=&quot;# Human &quot;/> <label xml:lang=&quot;en&quot;>has for mother</label> <comment xml:lang=&quot;en&quot;>to have for parent a female.</comment> </rdf:Property>
    declare a property in RDFS
  31. example
      • (define-relation has-mother
      • (?child ?mother) :iff-def
      • (and ( has-parent ?child ?mother) ( female ?mother)))
    define a relation in frames
  32. example
    • <owl:Class rdf:ID=&quot;Herbivore&quot;> <subClassOf rdf:resource=&quot;#Animal&quot;/> <subClassOf> <owl:Restriction> <owl: onProperty rdf:resource=&quot;# eats &quot; /> <owl: allValuesFrom rdf:resource=&quot;# Plant &quot; /> </owl:Restriction> </subClassOf> </owl:Class>
    restriction on properties in OWL
  33. example
      • (define-class executive (?person) : default-constraints
      • (owns-tv ?person))
    default values in ontolingua
  34. example
      • (define-class Author (?author) :def (and (person ?author) ( = (value-cardinality ?author author.name) 1) (value-type ?author author.name biblio-name) ( >= (value-cardinality ?author author.documents) 1) (<=> (author.name ?author ?name) (person.name ?author ?name))))
    cardinality constraints in frames
  35. example
    • < owl: Symmetric Property rdf:ID=&quot;hasSpouse&quot; />
    • < owl: Transitive Property rdf:ID=&quot;hasAncestor&quot; />
    • < owl: Functional Property rdf:ID=&quot;hasMother&quot; />
    • < owl: Inverse Functional Property rdf:ID=&quot;SSNum &quot; />
    • <rdf:Property rdf:ID=&quot;hasChild&quot;> < owl: inverseOf rdf:resource=&quot;#hasParent&quot;/> </rdf:Property>
    algebraic properties in OWL
  36. example
      • [Car:  ]->(Has)->[ SteeringWheel ]
    existential knowledge in conceptual graphs
  37. example
      • (define-axiom driver-consistency :=
      • ( <=> (drive ?a ?p) (driver ?a ?p) )
    axioms in frames
  38. example
      • (defrelation child ((?p Person) (?c Person)) :=> ( > (age ?p) (age ?c)) )
    constraints in description logics
  39. example
    • ( define- function price (?car ?power ?days) :-> ?amount :def (and (Car ?car) (Number ?power) (Number ?days) (Number ?amount) (Rate ?car ?rate)) :lambda-body (* (+ ?rate (* 0.1 ?power)) ?days))
    functions in conceptual graphs
  40. example
    • IF ?person author ?doc ?doc rdf:type PhDThesis ?doc concern ?topic THEN ?person expertIn ?topic ?person rdf:type PhD
    derivation rule languages
  41. example
    • <owl:Class rdf:about=&quot;&o1;Person&quot;> < owl: equivalentClass rdf:resource=&quot;&o2;Hito&quot;/> </owl:Class>
    equivalence of classes in OWL
  42. example
    • G = 9.8 m/s²
    a constant
  43. By 2012,
    • 70% of public Web pages will have some level of semantic markup, but only 20% will use more extensive Semantic Web-based technologies
    • [Finding and Exploiting Value in Semantic Technologies on the Web
    • Gartner Research Report, May 2007]
    • cycle
    Life Manage Needs Design Diffusion Use Evaluate Evolution
  44. needs
    • motivating scenarios, competency questions,
     Manage Needs Design Diffusion Use Evaluate Evolution
    • knowledge acquisition techniques, natural language processing, formalisms formal concept analysis, methodologies & intermediary representations
    design  Manage Needs Design Diffusion Use Evaluate Evolution
    • identify, publish, advertise, web, peer-to-peer and other networks, standards (e.g., OWL)
    diffusion  Manage Needs Design Diffusion Use Evaluate Evolution
    • in daily applications, in daily tasks (find, monitor, combine, analyze, reuse, suggest etc.), inferences, interfaces.
    use  Manage Needs Design Diffusion Use Evaluate Evolution
  45. evaluate
    • c.f. needs + trace and
    • usage analysis, metrics from methods,
    • collective dimension and consensus
     Manage Needs Design Diffusion Use Evaluate Evolution
    • c.f. design + versioning, version alignment, coherence checking and all dependencies
    evolution  Manage Needs Design Diffusion Use Evaluate Evolution
    • as any project, complete methodologies
    manage  Manage Needs Design Diffusion Use Evaluate Evolution
  46. ontology
    • I never saw a universal
  47. tension
    • building block
    • vs.
    • changing block
  48. bottlenecks
    • acquisition & evolution
  49. fol k s O n o m i es in a nutshell
  50. a tag
    • a data attached to an object
    origins of geometry
  51. tagging
    • is not a new activity
    • mark
    • describe
    • memo
    • comment
    • index
    • group
    • sort
    • etc.
  52. another tag
    • in the web?
    <a>
    • collaboratively creating and managing tags to annotate and categorize content.
    social tagging
  53. folks
    • the mass of users to organize the mass of data
    onomy
  54. 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]
    f
  55. tag cloud
    • alphabetic order + visual clues
  56. folksonomies
    • are not the opposite of
    • ontologies
  57. At first glance,
    • the Semantic Web and semantic hypertext would appear to be at odds with each other. Gartner believes this debate is ultimately counterproductive. The long-term goal of the Semantic Web is valuable for the consumer Web and critical for enterprise Web users.
    • [Finding and Exploiting Value in Semantic Technologies on the Web
    • Gartner Research Report, May 2007]
  58. folksonomies
    • can be seen as a new way to build and maintain
    • ontologies
  59. many tags
    • for many uses
    origins of geometry to compare with RR176 cool send to Ted absolument faux ;-) for the SysDev team
  60. many tags
    • back to square 1 ?
  61. dark cloud
    • ahead
    • my bookmarked page
    bookmarks socially shared bookmark bookmark shared across people an applications
  62. ontologies folksonomies &
  63. simple, focused, grassroots Web 2.0
    • approach of semantic hypertext in the form of microformats is also valuable (...) provides the first step to a Semantic Web. (…) technologies are emerging to convert
    • microformats to RDF (…). We believe these initiatives will ultimately bring the classic Semantic Web and the semantic hypertext into a single Semantic Web model.
    • [Finding and Exploiting Value in Semantic Technologies on the Web
    • Gartner Research Report, May 2007]
  64. “ semantic web ” and not “ semantic web”
    • [C. Welty, ISWC 2007]
  65. a lightweight ontology allows us to do lightweight reasoning
    • [J. Hendler, ISWC 2007]
  66. you can’t foresee
    • each and every use and reuse
  67. black box
    • avoid building another
  68. explicit
    • make conceptualizations
  69. open your data
    • to anyone who might use it
    W3C ©
  70. just my…
  71. fabien, gandon

+ Fabien GandonFabien Gandon, 2 years ago

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Introduction to ontologies and folksonomies.

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