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