Makemake au e hōʻike aku i ka lehulehu i kahi ʻāpana o kēia puke i paʻi ʻia nei:
Hoʻohālikelike ontological o kahi ʻoihana: nā ʻano a me nā ʻenehana [Text]: monograph / [S. V. Gorshkov, S. S. Kralin, O. I. Mushtak a me na mea e ae; luna hoʻoponopono S.V. Gorshkov]. - Ekaterinburg: Ural University Publishing House, 2019. - 234 p.: ill., papaʻaina; 20 knm - Mea kākau. hōʻike ʻia ma ka ʻaoʻao hope. Me ka. — Palapala Palapala ma ka hope o ch. — ISBN 978-5-7996-2580-1: 200 kope.
ʻO ke kumu o ka hoʻouna ʻana i kēia ʻāpana ma Habré he ʻehā:
- ʻAʻole hiki i kekahi ke paʻa i kēia puke ma ko lākou lima inā ʻaʻole ia he mea kūʻai aku i kahi mea i mahalo ʻia ; ʻAʻole kūʻai ʻia.
- Ua hoʻoponopono ʻia ka kikokikona (ʻaʻole i hōʻike ʻia ma lalo) a ua hoʻohui ʻia ʻaʻole kūpono loa me ke ʻano o kahi monograph i paʻi ʻia: nā memo kumuhana (ma lalo o nā mea hao) a me nā loulou.
- makemake wau e hōʻiliʻili i nā nīnau a me nā manaʻo, i mea e noʻonoʻo ai i ka wā e hoʻokomo ai i kēia kikokikona ma kahi ʻano i hoʻoponopono hou ʻia ma nā puke ʻē aʻe.
- Manaʻo ka nui o ka poʻe Semantic Web a me Linked Data he haiki loa ko lākou pōʻai, no ka mea ʻaʻole i wehewehe pono ʻia ka lehulehu i ka maikaʻi o ka mālama ʻana i ka Semantic Web a me Linked Data. ʻO ka mea kākau o ka ʻāpana, ʻoiai ʻo ia i loko o kēia pōʻai, ʻaʻole ia e paʻa i kēia manaʻo, akā naʻe, manaʻo ʻo ia he kuleana e hoʻāʻo hou.
A pēlā,
Pūnaewele Semantic
Hiki ke hōʻike ʻia ka ulu ʻana o ka Pūnaewele penei (a i ʻole e kamaʻilio e pili ana i kāna mau ʻāpana i hoʻokumu ʻia ma ke ʻano i hōʻike ʻia ma lalo nei):
- Nā palapala ma ka Pūnaewele. Nā ʻenehana nui - Gopher, FTP, etc.
He pūnaewele puni honua ka Internet no ka hoʻololi ʻana i nā kumuwaiwai kūloko. - Nā palapala pūnaewele. ʻO nā ʻenehana koʻikoʻi ʻo HTML a me HTTP.
ʻO ke ʻano o nā kumuwaiwai i hōʻike ʻia e noʻonoʻo i nā hiʻohiʻona o kā lākou mea hoʻouna. - ʻikepili pūnaewele. Nā ʻenehana koʻikoʻi - REST a me SOAP API, XHR, etc.
ʻO ke au o nā noi pūnaewele, ʻaʻole wale ka poʻe i lilo i mea kūʻai aku i nā kumuwaiwai. - ʻikepili pūnaewele. ʻO nā ʻenehana koʻikoʻi ʻo nā ʻenehana ʻikepili Linked.
ʻO kēia pae ʻehā, i wānana ʻia e Berners-Lee, ka mea nāna i hoʻokumu i nā ʻenehana kumu ʻelua a me ka luna o ka W3C, ua kapa ʻia ʻo Semantic Web; Hoʻolālā ʻia nā ʻenehana ʻikepili Linked e hana i ka ʻikepili ma ka pūnaewele ʻaʻole hiki ke heluhelu ʻia e ka mīkini wale nō, akā, ʻo ia hoʻi ka "machine-understandable."
Mai nā mea aʻe, e hoʻomaopopo ka mea heluhelu i ka pilina ma waena o nā manaʻo nui o ka pae ʻelua a me ka hā.
- Ua like nā URL me nā URI,
- ʻO ka analogue o HTML ʻo RDF,
- Ua like nā loulou HTML me nā hanana URI ma nā palapala RDF.
ʻO ka Pūnaewele Semantic kahi ʻike ʻōnaehana o ka wā e hiki mai ana o ka Pūnaewele ma mua o kahi ʻano kuʻuna a i ʻole lobbied, ʻoiai hiki iā ia ke noʻonoʻo i kēia mau mea hope. No ka laʻana, ʻo kahi ʻano koʻikoʻi o ka mea i kapa ʻia ʻo Web 2.0 i manaʻo ʻia he "mea hoʻohana i hana ʻia." Ma keʻano kūikawā, ua kāhea ʻia ka ʻōlelo aʻoaʻo W3C e noʻonoʻo ""a me kahi hana e like me .
Ua make anei ka Semantic Web?
Inā hōʻole ʻoe , ʻo ke kūlana me ka pūnaewele semantic ua like like me ka komunism i ka wā o ka hoʻomohala ʻana i ka socialism (a inā ʻike ʻia ka ʻoiaʻiʻo i nā kauoha kūlana a Ilyich, e hoʻoholo nā mea a pau no lākou iho). Nā mīkini huli e hoʻohana i nā pūnaewele e hoʻohana iā RDFa a me JSON-LD a hoʻohana lākou i nā ʻenehana pili i nā mea i wehewehe ʻia ma lalo nei (Google Knowledge Graph, Bing Knowledge Graph).
Ma nā ʻōlelo maʻamau, ʻaʻole hiki i ka mea kākau ke haʻi i ka mea e pale ai i ka hoʻolaha nui ʻana, akā hiki iā ia ke ʻōlelo ma muli o ka ʻike pilikino. Aia nā pilikia e hiki ke hoʻoponopono ʻia "ma waho o ka pahu" i nā kūlana o ka hoʻouka kaua SW, ʻoiai ʻaʻole lākou i laha loa. ʻO ka hopena, ʻo ka poʻe e kū nei i kēia mau hana, ʻaʻohe mea e koi ai i ka poʻe i hiki ke hāʻawi i kahi hopena, ʻoiai ʻo ka hāʻawi kūʻokoʻa ʻana o ka hopena i kūʻē i kā lākou mau hiʻohiʻona ʻoihana. No laila ke hoʻomau nei mākou i ka hoʻopaʻa ʻana i ka HTML a hoʻopili i nā API like ʻole, ʻoi aku ka shittier.
Eia naʻe, ua laha ʻia nā ʻenehana Linked Data ma waho o ka Pūnaewele nui; ʻO ka puke, ʻoiaʻiʻo, ua hoʻolaʻa ʻia i kēia mau noi. I kēia manawa, manaʻo ke kaiāulu Linked Data e laha loa kēia mau ʻenehana i ka hoʻopaʻa ʻana o Gartner (a i ʻole hoʻolaha, e like me kou makemake) o nā ʻano e like me Nā Kiʻi ʻIke и Ka lole ʻikepili. Makemake wau e manaʻoʻiʻo ʻaʻole ʻo ia ka hoʻokō "paakeke" o kēia mau manaʻo e kūleʻa, akā ʻo nā mea e pili ana i nā kūlana W3C i kūkākūkā ʻia ma lalo nei.
ʻIkepili pili
Ua wehewehe ʻo Berners-Lee i ka Linked Data e like me ka pūnaewele semantic "hana pololei": kahi hoʻonohonoho o nā ala a me nā ʻenehana e hiki ai iā ia ke hoʻokō i kāna mau pahuhopu hope. Nā loina kumu o Linked Data Berners-Lee o keia.
Kumu 1. Ke hoʻohana nei i nā URI e inoa i nā hui.
ʻO nā URI nā mea hōʻike honua e kūʻē i nā mea hōʻailona string kūloko no nā mea komo. Ma hope mai, ua hōʻike maikaʻi ʻia kēia kumukānāwai ma ka ʻōlelo slogan Google Knowledge Graph "".
Kumu 2. Ke hoʻohana nei i nā URI i ka hoʻolālā HTTP i hiki ke hoʻopau ʻia.
Ma ka kuhikuhi ʻana i kahi URI, hiki ke loaʻa i ka mea i hōʻailona ʻia ma hope o kēlā hōʻailona (ʻo ka hoʻohālikelike me ka inoa o ka mea hoʻohana " maopopo ma aneʻi).*" ma C); ʻoi aku ka pololei, e kiʻi i kahi hōʻike o kēia hōʻailona - ma muli o ka waiwai o ke poʻo HTTP Accept:. Malia paha, me ka hiki ʻana mai o ka wā AR / VR, hiki ke loaʻa i ka waiwai ponoʻī, akā i kēia manawa, ʻoi aku paha, he palapala RDF, ʻo ia ka hopena o ka hoʻokō ʻana i kahi nīnau SPARQL. DESCRIBE.
Kumu 3. Hoʻohana i nā maʻamau W3C - ʻo RDF(S) a me SPARQL - i ka wā e haʻalele ai i nā URI.
ʻO kēia mau "papa" o ka waihona ʻenehana Linked Data, i ʻike ʻia hoʻi , e wehewehe ʻia ma lalo nei.
Kumu 4. Hoʻohana i nā kuhikuhi i nā URI ʻē aʻe i ka wehewehe ʻana i nā hui.
ʻAe ʻo RDF iā ʻoe e kaupalena iā ʻoe iho i ka wehewehe waha o kahi kumuwaiwai ma ka ʻōlelo kūlohelohe, a ʻo ke kumu ʻehā e kāhea ʻole e hana i kēia. Inā mālama ʻia ka loina mua, hiki i ka wehewehe ʻana i kahi kumuwaiwai e kuhikuhi i nā mea ʻē aʻe, me nā "haole", ʻo ia ke kumu i kapa ʻia ai ka ʻikepili pili. ʻOiaʻiʻo, aneane hiki ʻole ke hoʻohana i nā URI i kapa ʻia ma ka huaʻōlelo RDFS.
ʻO R.F.D.
(Resource Description Framework) he ʻano hoʻohālikelike no ka wehewehe ʻana i nā hui pili.
ʻO nā ʻōlelo o ke ʻano "subject-predicate-object", i kapa ʻia nā triplets, e pili ana i nā hui a me kā lākou pilina. Ma ka hihia maʻalahi, ʻo ke kumuhana, predicate, a me ka mea he mau URI. Hiki i ka URI like ma nā kūlana like ʻole i nā triplets like ʻole: he kumuhana, predicate, a me kahi mea; No laila, hoʻokumu nā triplets i kahi ʻano pakuhi i kapa ʻia he pakuhi RDF.
ʻO nā kumuhana a me nā mea hiki ke lilo i URI wale nō, akā i kapa ʻia hoʻi nā pūnaʻi hakahaka, a hiki i nā mea literals. ʻO nā huaʻōlelo he mau hiʻohiʻona o nā ʻano primitive e pili ana i kahi hōʻike string a me kahi hōʻailona ʻano.
Nā laʻana o ke kākau ʻana i nā huaʻōlelo (ma Turtle syntax, ʻoi aku e pili ana iā ia ma lalo): "5.0"^^xsd:float и "five"^^xsd:string. Nā huaʻōlelo me ke ʻano rdf:langString hiki ke hoʻolako pū ʻia me ka ʻōlelo hōʻailona; ma Turtle ua kākau ʻia penei: "five"@en и "пять"@ru.
ʻO nā nodes he mau kumuwaiwai "ʻike ʻole" me ka ʻole o nā mea hōʻike honua, e pili ana i nā ʻōlelo e hiki ke hana ʻia; ʻano o nā ʻano hoʻololi.
No laila (ʻo kēia, ʻoiaʻiʻo, ke kiko holoʻokoʻa o RDF):
- ʻO ke kumuhana he URI a i ʻole kahi node ʻole,
- ʻO ka predicate he URI,
- ʻO ka mea he URI, he node kaʻawale, a i ʻole maoli.
No ke aha ʻaʻole hiki i nā predicates ke lilo i nā nodes hakahaka?
ʻO ke kumu paha ʻo ia ka makemake e hoʻomaopopo ʻole a unuhi i ka triplet i loko o ka ʻōlelo o ka loiloi predicate papa mua. s p o e like me kekahi mea 
kahi - predicate, и - mau mea mau. Aia nā ʻāpana o kēia ʻike ma ka palapala "", nona ke kūlana o kahi memo hui hana W3C. Me keia hoomaopopo ana, ka triplet s p []kahi [] - node hakahaka, e unuhi ʻia e like me kahi - ʻano like ʻole, akā pehea e unuhi ai s [] o? Palapala me ke kūlana Manaʻo W3C "” hāʻawi i kekahi ʻano unuhi ʻē aʻe, akā ʻaʻole naʻe e noʻonoʻo i ka hiki ʻana o nā predicates he mau nodes ʻole.
Eia naʻe, ʻo Manu Sporni .
He kumu hoʻohālike ʻo RDF. Hiki ke kākau ʻia (serialized) RDF i nā syntax like ʻole: , (ʻoi aku ka hiki ke heluhelu ʻia e ke kanaka), , (binary).
Hiki ke hoʻokaʻawale ʻia ka RDF like i RDF/XML ma nā ʻano like ʻole, no laila, no ka laʻana, ʻaʻohe kūpono e hōʻoia i ka hopena XML e hoʻohana ana i ka XSD a i ʻole e hoʻāʻo e unuhi i ka ʻikepili me XPath. Pēlā nō, ʻaʻole paha e hoʻokō ʻo JSON-LD i ka makemake o ka mea hoʻomohala Javascript maʻamau e hana pū me RDF me ka hoʻohana ʻana i ka helu kiko a me ka square bracket o Javascript (ʻoiai ke neʻe nei ʻo JSON-LD i kēlā ʻaoʻao ma ka hāʻawi ʻana i kahi mīkini. ).
Hāʻawi ka hapa nui o nā syntax i nā ala e pōkole ai i nā URI lōʻihi. No ka laʻana, he hoʻolaha @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> ma Turtle e ʻae iā ʻoe e kākau ma kahi <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> pololei rdf:type.
RDFS
(RDF Schema) - he huaʻōlelo hoʻohālike kumu, hoʻolauna i nā manaʻo o ka waiwai a me ka papa a me nā waiwai e like me rdf:type, rdfs:subClassOf, rdfs:domain и rdfs:range. Me ka hoʻohana ʻana i ka puke wehewehe ʻōlelo RDFS, no ka laʻana, hiki ke kākau ʻia kēia mau ʻōlelo kūpono:
rdf:type rdf:type rdf:Property .
rdf:Property rdf:type rdfs:Class .
rdfs:Class rdfs:subClassOf rdfs:Resource .
rdfs:subClassOf rdfs:domain rdfs:Class .
rdfs:domain rdfs:domain rdf:Property .
rdfs:domain rdfs:range rdfs:Class .
rdfs:label rdfs:range rdfs:Literal .ʻO ka RDFS he wehewehe a me ka hoʻohālikelike ʻana i nā huaʻōlelo, akā ʻaʻole ia he ʻōlelo kaohi (ʻoiai ʻo ka ʻōlelo kikoʻī a me hiki ke hoʻohana ʻia). ʻAʻole pono e hoʻomaopopo ʻia ka huaʻōlelo "Schema" ma ke ʻano like me ka huaʻōlelo "XML Schema". ʻo kahi laʻana, :author rdfs:range foaf:Person ʻo ia hoʻi rdf:type waiwai waiwai a pau :author - foaf:Person, akā, ʻaʻole ia he manaʻo e ʻōlelo mua ʻia kēia.
SPARQL
(SPARQL Protocol and RDF Query Language) - he ʻōlelo no ka nīnau ʻana i ka ʻikepili RDF. Ma kahi hihia maʻalahi, ʻo kahi nīnau SPARQL he pūʻulu o nā laʻana e pili ana i nā triplets o ka pakuhi i nīnau ʻia. Hiki i nā mamana ke loaʻa nā mea hoʻololi i ke kumuhana, predicate, a me nā kūlana mea.
E hoʻihoʻi ka nīnau i nā ʻano waiwai like ʻole, ke hoʻololi ʻia i nā laʻana, hiki ke hopena i kahi subgraph o ka pakuhi RDF i nīnau ʻia (kahi ʻāpana o kāna mau triplets). Pono nā ʻano like ʻole o ka inoa hoʻokahi i nā laʻana like ʻole o nā triplets i nā waiwai like.
No ka laʻana, hāʻawi ʻia i ka hoʻonohonoho ʻana o ʻehiku axioms RDFS ma luna, e hoʻi mai kēia nīnau rdfs:domain и rdfs:range e like me nā waiwai ?s и ?p pakahi:
SELECT * WHERE {
?s ?p rdfs:Class .
?p ?p rdf:Property .
}Pono e hoʻomaopopo ʻia he ʻōlelo hoʻolaha ʻo SPARQL a ʻaʻole ia he ʻōlelo no ka wehewehe ʻana i ka hele ʻana o ka pakuhi (eia naʻe, hāʻawi kekahi mau waihona RDF i nā ala e hoʻoponopono ai i ka hoʻolālā hoʻokō nīnau). No laila, ʻaʻole hiki ke hoʻonā ʻia kekahi mau pilikia pakuhi maʻamau, no ka laʻana, ka ʻimi ʻana i ke ala pōkole loa ma SPARQL, me ka hoʻohana ʻana i ka (akā, eia hou, hāʻawi nā waihona RDF pākahi i nā hoʻonui kūikawā e hoʻoponopono i kēia mau pilikia).
ʻAʻole kaʻana like ʻo SPARQL i ka manaʻo o ka wehe ʻana o ka honua a hahai i ke ʻano "negation as failure", kahi nā hoʻolālā e like me FILTER NOT EXISTS {…}. Noʻonoʻo ʻia ka hāʻawi ʻana i ka ʻikepili me ka hoʻohana ʻana i ka mīkini .
ʻO ka wahi komo SPARQL - kahi waihona RDF hiki ke hoʻoponopono i nā nīnau SPARQL - ʻaʻohe analogues pololei mai ka pae ʻelua (e ʻike i ka hoʻomaka o kēia paukū). Hiki ke hoʻohālikelike ʻia me kahi waihona, e pili ana i nā ʻike o nā ʻaoʻao HTML i hana ʻia, akā hiki ke loaʻa i waho. ʻOi aku ka hoʻohālikelike ʻana o ka wahi komo SPARQL me ke kiko komo API mai ke kolu o ka pae, akā me ʻelua mau ʻokoʻa nui. ʻO ka mea mua, hiki ke hoʻohui i kekahi mau nīnau "atomic" i hoʻokahi (i manaʻo ʻia he ʻano koʻikoʻi o GraphQL), a ʻo ka lua, ʻo ia API ka palapala paʻa ponoʻī (ʻo ia ka mea a HATEOAS i hoʻāʻo ai e hoʻokō).
ʻŌlelo hoʻopaʻapaʻa
ʻO RDF kahi ala e hoʻopuka ai i ka ʻikepili ma ka pūnaewele, no laila e manaʻo ʻia ka waihona RDF he palapala DBMS. ʻOiaʻiʻo, ʻoiai ʻo RDF he pakuhi a ʻaʻole he lāʻau, ua hoʻololi ʻia lākou ma ka pakuhi. He mea kupanaha ka hana ʻana i nā mea a pau. ʻO wai ka mea i manaʻo he poʻe akamai e hoʻokō i nā nodes blank. Aia ʻo Codd ma ʻaneʻi .
ʻAʻole hoʻi nā ala piha piha e hoʻonohonoho i ke komo ʻana i ka ʻikepili RDF, no ka laʻana, (LDF) a (LDP).
'OWL
(Web Ontology Language) - he formalism no ka hoike ana i ka ike, he syntactic version of description logic (ma nā wahi a pau ma lalo he pololei ka ʻōlelo ʻana iā OWL 2, ua hoʻokumu ʻia ka mana mua o OWL ma ).
ʻO nā manaʻo o nā loina wehewehe i ka OWL e pili ana i nā papa, nā kuleana e pili ana i nā waiwai, paʻa nā kānaka i ko lākou inoa mua. Ua kapa ʻia nā axioms.
No ka laʻana, i ka mea i kapa ʻia no ka OWL notation he axiom i ʻike mua ʻia e mākou e kākau ʻia penei:
Class: Human
Class: Parent
EquivalentClass: Human and (inverse hasParent) some Human
ObjectProperty: hasParentAia kekahi mau syntax no ke kākau ʻana iā OWL, e like me , hoʻohana ʻia ma ka ʻōlelo kikoʻī kūhelu, a . Eia hou, hiki ke hoʻopili ʻia ʻo OWL a ʻoi aku - ma kekahi o nā syntax kikoʻī.
He pilina ʻelua ko OWL me RDF. Ma kekahiʻaoʻao, hiki ke noʻonoʻoʻia heʻano puke wehewehe'ōlelo e hoʻonui i ka RDFS. Ma ka ʻaoʻao ʻē aʻe, he formalism ʻoi aku ka ikaika no ka RDF he palapala serialization wale nō. ʻAʻole hiki ke kākau ʻia nā mea hana OWL haʻahaʻa me ka hoʻohana ʻana i hoʻokahi triplet RDF.
Ma muli o ka ʻāpana o nā kūkulu OWL i ʻae ʻia e hoʻohana ʻia, ʻōlelo lākou i ka mea i kapa ʻia . ʻO nā mea maʻamau a kaulana loa ʻo OWL EL, OWL RL a me OWL QL. Hoʻopili ke koho ʻana i ka ʻikepili i ka paʻakikī o ka helu ʻana o nā pilikia maʻamau. He pūʻulu piha o nā hale OWL e pili ana me , kapa ʻia ʻo OWL DL. I kekahi manawa, kamaʻilio pū lākou e pili ana i ka OWL Full, kahi i ʻae ʻia ai nā kūkulu OWL e hoʻohana me ke kūʻokoʻa piha i loaʻa i RDF, me ka ʻole o nā kaʻina semantic a me ka helu helu. . Eia kekahi laʻana, hiki i kekahi mea ke lilo i papa a me kahi waiwai. ʻAʻole hiki ke koho ʻia ʻo OWL Full.
ʻO nā loina koʻikoʻi no ka hoʻopili ʻana i nā hopena ma OWL ʻo ia ka hoʻokomo ʻana i ka manaʻo o ka honua ākea. ) a me ka hōʻole ʻana i ka manaʻo o nā inoa kūʻokoʻa (unique name assumption, ). Ma lalo e ʻike mākou i kahi e hiki ai i kēia mau loina ke alakaʻi a hoʻolauna i kekahi mau hana OWL.
E waiho i ka ontology i kēia ʻāpana (ma Manchester syntax):
Class: manyChildren
EquivalentTo: Human that hasChild min 3
Individual: John
Types: Human
Facts: hasChild Alice, hasChild Bob, hasChild CarolMa muli o ka mea i ʻōlelo ʻia he nui nā keiki a Ioane? ʻO ka hōʻole ʻana i ka UNA e koi aku i ka ʻenekini inference e pane i kēia nīnau me ka maikaʻi ʻole, ʻoiai ʻo Alice lāua ʻo Bob ka mea like. No ka hana ʻana i kēia, pono e hoʻohui i kēia axiom:
DifferentIndividuals: Alice, Bob, Carol, JohnE ʻae i kēia ʻāpana ontology i kēia ʻano (ua ʻōlelo ʻia ʻo John he nui nā keiki, akā ʻelua wale kāna mau keiki):
Class: manyChildren
EquivalentTo: Human that hasChild min 3
Individual: John
Types: Human, manyChildren
Facts: hasChild Alice, hasChild Bob
DifferentIndividuals: Alice, Bob, Carol, JohnʻAʻole kūlike paha kēia ontology (hiki ke unuhi ʻia ma ke ʻano he hōʻike o ka ʻikepili kūpono ʻole)? ʻO ka ʻae ʻana iā OWA e hoʻohuli i ka ʻenekini inference e pane i ka maikaʻi ʻole: "kahi" ʻē aʻe (ma kekahi ontology) hiki ke ʻōlelo ʻia ʻo Carol nō ke keiki a John.
No ke kāpae ʻana i ka hiki ʻana o kēia, e hoʻohui i kahi mea hou e pili ana iā John:
Individual: John
Facts: hasChild Alice, hasChild Bob, not hasChild CarolNo ka haʻalele ʻana i ke ʻano o nā keiki ʻē aʻe, e ʻōlelo mākou he poʻe nā waiwai āpau o ka waiwai "loaʻa ke keiki", ʻehā wale nō kā mākou:
ObjectProperty: hasChild
Domain: Human
Сharacteristics: Irreflexive
Class: Human
EquivalentTo: { Alice, Bill, Carol, John }I kēia manawa e lilo ka ontology i mea kū'ē, ʻaʻole e nele ka ʻenekini inference e hōʻike. Me ka hope o nā axioms i loaʻa iā mākou, ma ke ʻano, "pani" i ka honua, a ʻike i ke ʻano o ka hiki ʻana o John ke keiki ponoʻī.
Hoʻopili i ka ʻikepili ʻoihana
Ua manaʻo mua ʻia ka pūʻulu ʻikepili Linked o nā ala a me nā ʻenehana no ka hoʻopuka ʻana i ka ʻikepili ma ka Pūnaewele. ʻO kā lākou hoʻohana ʻana i kahi ʻoihana kūloko e kū nei i nā pilikia he nui.
No ka laʻana, i loko o kahi ʻoihana paʻa, ʻo ka mana deductive o OWL e pili ana i ka hoʻopaʻa ʻia ʻana o OWA a me ka hōʻole ʻana i ka UNA, nā hoʻoholo ma muli o ke ʻano wehe a puʻunaue ʻia o ka Pūnaewele, nāwaliwali loa. A ma ʻaneʻi hiki ke hoʻoponopono ʻia.
- Hāʻawi i ka OWL me nā semantics, e hōʻike ana i ka haʻalele ʻana iā OWA a me ka hoʻokomo ʻana o UNA, ka hoʻokō ʻana i ka mīkini hoʻopuka pili. - Ma keia ala Hoʻopaʻa ʻia ʻo Stardog RDF.
- Haʻalele ʻana i nā mana unuhi o OWL no nā ʻenekini rule. — Kākoʻo ʻo Stardog ; Hāʻawi ʻo Jena a me GraphDB rula
- ʻO ka hōʻole ʻana i nā mana unuhi o OWL, hoʻohana i kekahi a i ʻole kekahi ʻāpana kokoke i RDFS no ka hoʻohālike. - E ʻike hou aku e pili ana i kēia ma lalo.
ʻO kekahi kumu ʻē aʻe ka manaʻo nui aʻe o ka honua ʻoihana e pili ana i nā pilikia o ka maikaʻi o ka ʻikepili a me ka nele o nā mea hana hōʻoia ʻikepili i ka waihona Linked Data. ʻO nā mea hoʻopuka maʻaneʻi penei.
- Eia hou, e hoʻohana no ka hōʻoia ʻana i nā kūkulu OWL me nā semantics honua pani a me nā inoa kūʻokoʻa inā loaʻa kahi ʻenekini inference kūpono.
- E hoʻohana , hoʻopaʻa ʻia ma hope o ka hoʻopaʻa ʻia ʻana o ka papa inoa o Semantic Web Layer Cake (akā naʻe, hiki ke hoʻohana ʻia ma ke ʻano he mīkini lula), a i ʻole .
- ʻO ka hoʻomaopopo ʻana ua pau nā mea a pau me nā nīnau SPARQL, e hana ana i kāu mīkini hōʻoia ʻikepili maʻalahi me ka hoʻohana ʻana iā lākou.
Eia nō naʻe, ʻo ka hōʻole piha ʻana i nā mana unuhi a me nā mea hana hōʻoia e haʻalele i ka ʻikepili Linked ma waho o ka hoʻokūkū ma nā hana e like me ka ʻāina me ka pūnaewele wehe a puʻunaue - i nā hana hoʻohui ʻikepili.
Pehea e pili ana i kahi ʻōnaehana ʻike ʻoihana maʻamau?
Hiki paha kēia, akā pono ʻoe, ʻoiaʻiʻo, e makaʻala pono i nā pilikia o nā ʻenehana pili e hoʻoponopono ai. E wehewehe wau ma aneʻi i kahi ʻano maʻamau o nā mea hoʻomohala e hōʻike i ke ʻano o kēia ʻenehana ʻenehana mai ka ʻike o ka IT maʻamau. Hoʻomanaʻo iki mai iaʻu i ka ʻōlelo nane o ka ʻelepani:
- ʻAila ʻoihana: ʻO RDF kekahi mea e like me ke kumu hoʻohālike i mālama pono ʻia.
- Luna Hoʻoponopono Pūnaewele: Ua like ka RDF , me ka pūʻulu kuhikuhi a me ka ʻōlelo nīnau kūpono.
- Mea hoʻomohala: maikaʻi, aia kēia ma ka ʻuhane o nā manaʻo o ke kumu hoʻohālike waiwai a me nā code haʻahaʻa, hou e pili ana i keia.
- Luna Hoʻokele: ʻae like nō !
Hōʻike ka hoʻomaʻamaʻa i ka hoʻohana pinepine ʻia o ka waihona i nā hana e pili ana i ka hāʻawi ʻana a me ka heterogeneity o ka ʻikepili, no ka laʻana, ke kūkulu ʻana i nā ʻōnaehana papa MDM (Master Data Management) a i ʻole DWH (Data Warehouse). Aia ia mau pilikia ma kekahi ʻoihana.
Ma ke ʻano o nā noi kikoʻī ʻoihana, kaulana loa nā ʻenehana Linked Data i kēia manawa ma nā ʻoihana e hiki mai ana.
- nā ʻenehana biomedical (kahi e ʻike ʻia ai ko lākou kaulana i ka paʻakikī o ka domain);
kēia manawa
Ua mālama ʻia ka "Boiling Point" i kahi hālāwai kūkā i hoʻonohonoho ʻia e ka hui "National Medical Knowledge Base"".
- ka hana ʻana a me ka hana ʻana o nā huahana paʻakikī (ʻenehana mīkini nui, ʻaila a me ka hana kinoea; ʻo ka pinepine mākou e kamaʻilio e pili ana i ka maʻamau );
kēia manawa
Eia nō hoʻi, ʻo ke kumu ka paʻakikī o ke kumuhana, i ka manawa, no ka laʻana, i ka pae kiʻekiʻe, inā mākou e kamaʻilio e pili ana i ka ʻoihana aila a me ke kinoea, pono ka helu helu maʻalahi i kekahi mau hana CAD.
I ka makahiki 2008, ua mālama ʻia kahi hanana hoʻonohonoho ʻelele, i hoʻonohonoho ʻia e Chevron .
ʻO ISO 15926, i ka hopena, he mea kaumaha loa ia i ka ʻoihana aila a me ke kinoea (a loaʻa paha ka hoʻohana ʻoi aku ka nui ma ka ʻenekinia mechanical). ʻO Statoil wale nō (Equinor) i hoʻopili pono iā ia; ma Norewai, holoʻokoʻa . Ke hoʻāʻo nei kekahi e hana i kā lākou hana ponoʻī. No ka laʻana, e like me nā lono, ke manaʻo nei ka Ministry of Energy e hana i kahi "conceptual ontological model of the fuel and energy complex," like, apparently, to .
- nā hui kālā (ʻo XBRL hiki ke manaʻo ʻia he ʻano hybrid o SDMX a me ka RDF Data Cube ontology);
kēia manawa
I ka hoʻomaka ʻana o ka makahiki, ua hoʻopaʻa ikaika ʻo LinkedIn i ka mea kākau me nā hakahaka mai nā mea pilikua a pau o ka ʻoihana kālā, āna i ʻike ai mai ka moʻolelo TV "Force Majeure": Goldman Sachs, JPMorgan Chase a me Morgan Stanley, Wells Fargo, SWIFT/Visa/Mastercard, Bank of America, Citigroup, Fed, Deutsche Bank... Malia paha e ʻimi ana nā mea a pau i kahi mea hiki iā lākou ke hoʻouna aku. . He kakaikahi wale nō ka mea i loaʻa: ua lawe nā hui kālā i nā mea āpau .
Ma HeadHunter, ʻo Sberbank wale nō i ʻike i kahi mea hoihoi; ʻo ia e pili ana i ka "EaV storage me kahi hoʻohālike data like RDF."
Malia paha, ʻo ka ʻokoʻa o ke kiʻekiʻe o ke aloha no nā ʻenehana pili o nā ʻoihana kālā kūloko a me Western ma muli o ke ʻano transnational o nā hana hope. ʻIke ʻia, ʻo ka hoʻohui ʻana ma nā palena mokuʻāina e pono ai nā ʻano hoʻoponopono hoʻonohonoho a me nā ʻenehana like ʻole.
- nā ʻōnaehana pane pane me nā noi pāʻoihana (IBM Watson, Apple Siri, Google Knowledge Graph);
kēia manawa
Ma ke ala, ʻo ka mea nāna i hana iā Siri, ʻo Thomas Gruber, ka mea kākau o ka wehewehe pono o ka ontology (ma ke ʻano IT) ma ke ʻano he "conceptualization specification." I koʻu manaʻo, ʻo ka hoʻonohonoho hou ʻana i nā huaʻōlelo ma kēia wehewehe ʻana, ʻaʻole ia e hoʻololi i kona manaʻo, e hōʻike ana paha ʻaʻole i laila.
- ka hoʻolaha ʻana i nā ʻikepili i kūkulu ʻia (me ka ʻoi aku ka nui o ka hōʻoia e hiki ke hoʻopili ʻia kēia me Linked Open Data).
kēia manawa
ʻO nā mea pā nui o Linked Data ka mea i kapa ʻia ʻo GLAM: Galleries, Libraries, Archives, and Museums. Ua lawa ka ʻōlelo ʻana e hāpai ana ka Hale Waihona Puke o ka ʻAhaʻōlelo i kahi pani no MARC21 , a hāʻawi i kumu no ka wā e hiki mai ana o ka wehewehe puke a, ʻoiaʻiʻo, ma muli o RDF.
Hōʻike pinepine ʻia ʻo Wikidata ma ke ʻano he laʻana o kahi papahana kūleʻa ma ke kahua o Linked Open Data - kahi ʻano o Wikipedia hiki ke heluhelu ʻia e ka mīkini, ʻaʻole i hoʻokumu ʻia ka ʻike ma ke ʻano o DBPedia, ma ka lawe ʻana mai i nā pahu info ʻatikala, akā ʻo ia. hana ʻia a ʻoi aku ka liʻiliʻi me ka lima (a lilo i kumu ʻike no nā pahu ʻike like).
Paipai mākou iā ʻoe e nānā iā ia nā mea hoʻohana o ka waihona Stardog RDF ma ka pūnaewele Stardog ma ka ʻāpana "Customers".
E like me ia, ma Gartner "Enterprise Taxonomy and Ontology Management" ua kau ʻia ma waena o ka iho ʻana i ke awāwa o ka hōʻeha me ka manaʻo e hiki i kahi "pālāwai huahana" ma mua o 10 mau makahiki.
Hoʻohui i ka ʻikepili hui
Nā wānana, nā wānana, nā wānana...
Ma waho o ka hoihoi mōʻaukala, ua helu au ma lalo o nā wānana a Gartner no nā makahiki like ʻole e pili ana i nā ʻenehana hoihoi iā mākou.
| Makahiki | Pānaehana | Hōʻike | Kahi | Nā makahiki i ka pāpū |
|---|---|---|---|---|
| 2001 | Pūnaewele Semantic | ʻŌhumu ʻenehana | Hoʻomaka hou | 5-10 |
| 2006 | Pūnaewele Semantic Hui | ʻŌhumu ʻenehana | Kiekie o na Manaolana Hoonui | 5-10 |
| 2012 | Pūnaewele Semantic | BigʻIkepili | Kiekie o na Manaolana Hoonui | > 10 |
| 2015 | ʻIkepili pili | ʻIkepili Kiʻekiʻe a me ʻEpekema ʻIkepili | Pahu o ka Hoohuoi | 5-10 |
| 2016 | ʻOihana Ontology Management | ʻŌhumu ʻenehana | Pahu o ka Hoohuoi | > 10 |
| 2018 | Nā Kiʻi ʻIke | ʻŌhumu ʻenehana | Hoʻomaka hou | 5-10 |
Eia naʻe, ua komo i loko ua ʻike ʻia kekahi ʻano piʻi - Nā Kiʻi ʻIke. Ua loaʻa kekahi reincarnation: graph DBMSs, kahi i hoʻololi ʻia ai ka manaʻo o nā mea hoʻohana a me nā hana a nā mea hoʻomohala, ma lalo o ka mana o nā noi o ka mua a me nā maʻamau o ka hope, hoʻomaka e lawe i nā contours a me ka hoʻonohonoho ʻana. o ko lakou mau hoa paio mua.
Aneane i kēlā me kēia pakuhi DBMS i kēia manawa e hōʻike iā ia iho he kahua kūpono no ke kūkulu ʻana i kahi "kapili ʻike" hui ("hoʻopili ʻia ka ʻikepili" i kekahi manawa e pani ʻia e "ʻikepili pili"), akā pehea ke kūpono o ia mau koi?
He asemantic mau nā ʻikepili kiʻi; ʻo ka ʻikepili i loko o ka pakuhi DBMS ʻo ia ka silo ʻikepili like. ʻO nā mea hōʻailona string ma mua o nā URI e hana i ka hana o ka hoʻohui ʻana i nā DBMS kiʻi ʻelua i kahi hana hoʻohui, ʻoiai ʻo ka hoʻohui ʻana i ʻelua mau hale kūʻai RDF e iho pinepine i lalo i ka hoʻohui ʻana i ʻelua kiʻi RDF. ʻO kekahi hiʻohiʻona o ka asemanticity ka non-reflexivity o ka LPG graph model, he mea paʻakikī ke hoʻokele metadata me ka hoʻohana ʻana i ka paepae like.
ʻO ka hope loa, ʻaʻohe ʻenekini inference a i ʻole nā ʻenekini lula. Hiki ke hoʻopuka hou ʻia nā hopena o ia mau mīkini e ka hoʻopiʻi ʻana i nā nīnau, akā hiki nō kēia ma SQL.
Eia naʻe, ʻaʻohe pilikia o nā ʻōnaehana mālama RDF i ke kākoʻo ʻana i ke kumu hoʻohālike LPG. ʻO ke ala paʻa loa i manaʻo ʻia ʻo ia ka mea i manaʻo ʻia i ka manawa hoʻokahi ma Blazegraph: ke kumu hoʻohālike RDF*, e hui pū ana me RDF a me LPG.
More
Hiki iā ʻoe ke heluhelu hou aʻe e pili ana i ke kākoʻo mālama RDF no ka hoʻohālike LPG ma ka ʻatikala mua ma Habré: . Manaʻo wau i kekahi lā e kākau ʻia kahi ʻatikala ʻokoʻa e pili ana i nā Kiʻi Kiʻi ʻIke a me ka Fabric Data. ʻO ka pauku hope, e like me ka maʻalahi o ka hoʻomaopopo ʻana, ua kākau wikiwiki ʻia, akā naʻe, ʻeono mahina ma hope, ʻaʻole maopopo loa nā mea āpau me kēia mau manaʻo.
Paipalapala
- Halpin, H., Monnin, A. (eds.) (2014). Philosophical Engineering: Toward a Philosophy of the Web
- Allemang, D., Hendler, J. (2011) Semantic Web for the Working Ontologist (2nd ed.)
- Staab, S., Studer, R. (eds.) (2009) Handbook on Ontologies (2nd ed.)
- Wood, D. (ed.). (2011) Hoʻopili i ka ʻikepili hui
- Keet, M. (2018) He Introduction to Ontology Engineering
Source: www.habr.com