Semantic Web & Ontology. Introduction Semantic Web and Ontology.
Semantic Web · Semantic Web--- Railways are impacted by all A.I. fields ---Web 4.0 Big-Data Neural...
Transcript of Semantic Web · Semantic Web--- Railways are impacted by all A.I. fields ---Web 4.0 Big-Data Neural...
from Linked Datato Computer Reasoning
Didier Guillonnet 04-Oct-2019
SemanticWeb
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Semantic Web Market Opportunity Size Estimates: https://docs.google.com/spreadsheets/d/1pJDkzlNOUs6plKQS01mMmCKvKu6io6ZhDDD-mHmrO_g
UIC Interest
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Semantic Web--- Railways are impacted by all A.I. fields ---
Web 4.0Big-Data
Neural Networks
Formal logicPrediction
Simulation
Predictive Maintenance Assisted
Planning
Weak Signals
Decision Helping
Cyber Security
Railways scope
Hotline
Training
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A.I. Overview--- 4 fields supporting A.I. technology ---
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A.I. Overview--- 4 fields supporting A.I. technology ---
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Ivan Herman 2012https://www.slideshare.net/sssw2012/ivan-hernan-semantic-web-activities-w3c
The WEB was aboutlinked Documents
Semantic Web--- Graph Data Model ---
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The Semantic WEB is about linked Things...
Semantic Web--- Graph Data Model ---
Ivan Herman 2012https://www.slideshare.net/sssw2012/ivan-hernan-semantic-web-activities-w3c
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Or (Thing, Property, Value)
https://www.w3.org/TR/2014/REC-rdf11-concepts-20140225/ https://en.wikipedia.org/wiki/Resource_Description_Framework
<http://example.org/person/Auguste_Rodin>
<http://example.org/relation/author>
<http://example.org/sculpture/The_Thinker> .
Subject ObjectPredicate
Graph Nodes
RDF = Resource Description Framework
Semantic Web--- Graph Data Model : RDF Triples ---
URI = Universal Resource Identifier
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https://www.slideserve.com/jeneil/semantic-web
Semantic Web “of Linked Data”--- Object Classes , RDF Schema ---
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Semantic Web “of Linked Data”--- RDFS: RDF Schema + REIFICATION ---
Classes
Instances
2015
since
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Semantic Web “of Linked Data”>> RESULT : Distributed & Shared Data and Ontologies
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Semantic Web “of Linked Data”--- Layers of Semantic Web Technologies ---
Kingsley Uyi Idehen (Jul-2017) https://medium.com/openlink-software-blog/semantic-web-layer-cake-tweak-explained-6ba5c6ac3fab
● RDF is XML → Internationalization, XSLT (XML transformation language) and other common tools
● RDF is perfect for merging data from various sources, and for mixing namespaces
● RDF is for the Web → easier to share, to protect, to retrieve
● a consistant stack of technologies → better integration
● using URIs → network effect
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Semantic Web--- Bricks of the Semantic Web Technologies ---
Querying language
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Semantic Web “of Linked Data”--- SPARQL syntax // Entry points ---
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http://www.webdatacommons.org/structureddata/https://en.wikipedia.org/wiki/RDFa
RDFa, Microdata, and Microformat Data Sets
Now computers understand the Web => This is WEB 3.0
Semantic Web “of Linked Open Data”--- HTML embedded RDF data ---
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2006 Tim Berners-Leehttps://www.w3.org/DesignIssues/LinkedData.html
https://5stardata.info/en/
★ Available on the web (whatever format)with an open licence, to be Open Data.
★★ Machine-Readable structured data (e.g. excel instead of image scan of a table)
★★★ Non-Proprietary Format (e.g. CSV instead of excel)
★★★★ Identify Things with Open Standardsfrom W3C (RDF and SPARQL),so that people can point at your stuff
★★★★★ Link your data to other people’s data (to provide context)
The 5-Star Rating of Linked Open Data
Semantic Web “of Linked Open Data”--- IS YOUR DATA 5 Stars ? ---
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● DBpedia: 9.5 Bn triples (Wikipedia Knowledge extraction)
● WikiData: 5.8 Bn triples
● BabelNet: 1.9 Bn triples (linguistics)
● WordNet: 9 M triples (linguistics)
● GeoNames: 93 M triples, 6M entities
● MusicBrainz: 36 M triples
● DB-Tune Jamendo: 1.1 Bn triples
● FreeBase: 340 M triples (general knowledge DEAD)
● RDF Book Mashup: 10 M triples
● Others: YAGO, UMBEL / KBpedia, BNF.fr, CIA-Factbook...
** Famous Ontologies **
● FOAF: Friend Of A Friend● DCMI: Dublin Core
Metadata Initiative
● SKOS: Simple Knowledge Organization System
● Schema.org: Business links
Semantic Web “of Linked Open Data”--- Famous Open Datasets ---
Upper Ontologyvery general terms common across all domains
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When humans think,they draw consequences from their knowledge,and increase the known facts.
• “A statement is a consequence of other statements”essentially means that this statement is true whenever the other statements are.
• A set of statements may be:- Consistent, if there is a possible state of affairs in which all the statements in
the set are jointly true. - Inconsistent, if there is no such state of affairs.
Semantic Web--- Reasoning ---
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RDFS is too “weak” to describe resources with a suitable level of details
– range and domain cannot be localized (e.g. the range of hasChild is a person when applied to a person, elephant when applied to an elephant)
– no constraints on existence or cardinality (e.g. all instances of persons have one and only one mother which is a person, and have exactly two parents)
– it is not possible to define transitive, inverse or symmetrical statements (e.g. part of is a transitive property, hasPart is the inverse of isPartOf, touches is symmetrical)
=> a more powerful language: Web Ontology Language (OWL)
Semantic Web-- Reasoning: RDFS is too “weak” => OWL
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• More expressive than RDFS– Identity equivalence/difference– sameAs, differentFrom, equivalentClass/Property
• More expressive class definitions– Class intersection, union, complement...– Cardinality restrictions
• More expressive property definitions– Object/Datatype properties– Transitive, functional, symmetric, inverse properties– Value restrictions
What can be done with OWL?
– Consistency checks: are there contradictions in the logical model?
– Satisfiability checks: are there classes that cannot have any instances?
– Classification: what is the type of a particular instance?
Semantic Web--- Reasoning: OWL ---
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Semantic Web--- Rules based Monotonic Reasoning ---
Socrates isA Man.
Man isA Human.
every Human is Mortal.
=> Inference: Socrates is Mortal
man(‘Socrates’).
human(X) :- man(X).
mortal(X) :- human(X).
? mortal(‘Socrates’) => true
Entailment Rules propagate and generate (infer) new assertions.
In Monotonic Reasoning, new assertions cannot contradict old ones.
Closure of a Graph = set of all assertions that can be inferred.
Reduction = minimal set of assertions that can infer the same Closure.
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Semantic Web “of Linked Data”--- More and more structured Knowledge ---
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Big Developmentin 2015-2016
Now reacheda plateau.
1200+ DataSets
Semantic Web “of Linked Open Data”--- Numerous Linked Open Datasets ---
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Wikipedia
DBpedia
Wikidata
Yago
Google KG
CIA Factbook
General Knowledge
120 M Tr10 M ent350 kCl
13 Bn Tr6 M ent
5.8 Bn Tr
80 Bn Tr600 M ent
BabelNet(2 BnT)
WordNet(9 MT)
GeoNames(93 MT, 6M ent)
MusicBrainz(36 MT) TrueKnowledge => EVI
founded 2005 UK Amazon Alexa
FreeBase(340M ent)
linguistics
WolframAlpha(Computational Engine)
oct-2012
june-2012
Apple SIRI
IBM Watson
Microsoft Cortana
OpenCyc(240 kCl, 2 M Tr) 2017
discontinued
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Semantic Web “of Linked Open Data”--- Semantics Evolution => Main Actors ---
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Everybody can enrich
public knowledge
Computers understand the Web
Computers answerand anticipate your needs...
Semantic Web “of Linked Open Data”--- Semantics Evolution => Web 4.0 ---
Thank you!for your kind attention
SemanticWeb
Web 4.0