Loading…

Flash Player 9 (or above) is needed to view presentations.
We have detected that you do not have it on your computer. To install it, go here.

Like this presentation? Why not share!

Approximation and Self-Organisation on the Web of Data

on

  • 881 views

 

Statistics

Views

Total Views
881
Views on SlideShare
881
Embed Views
0

Actions

Likes
1
Downloads
5
Comments
0

0 Embeds 0

No embeds

Accessibility

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Approximation and Self-Organisation on the Web of Data Approximation and Self-Organisation on the Web of Data Presentation Transcript

  • Introduction Highlights Conclusions Approximation and Self-Organisation on the Web of Data BNAIC 2010: Semantic Web / Intelligent Systems Christophe Guer´t, Kathrin Dentler and Stefan Schlobach e October 25th 2010 Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 1/25
  • Introduction Highlights Conclusions Outline 1 Introduction 2 Highlights 3 Conclusions Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 2/25
  • Introduction Highlights Conclusions Outline 1 Introduction 2 Highlights 3 Conclusions Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 3/25
  • Introduction Highlights Conclusions What is the Web of Data? Linked Data 1 Use URIs as names for things 2 Use HTTP URIs 3 Provide useful information, using standards 4 Include links to other URIs Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 4/25
  • Introduction Highlights Conclusions The Web of Data is Growing 2007 Fresh- ECS South- SIOC meat ampton BBC Later + NEW! Sem- NEW! TOTP Web- SW Central Onto- Conference world Corpus Music- Magna- FOAF brainz tune Open- Guides Revyu RDF Book Jamendo Geo- Mashup names DBpedia DBLP Berlin US World NEW! Census Fact- Data book NEW! lingvoj Euro- flickr stat wrappr Wiki- Open DBLP company Cyc Hannover Gov- Track Project W3C Guten- WordNet berg Figure: 2007 Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 5/25
  • Introduction Highlights Conclusions The Web of Data is Growing 2008 NEW! Surge ECS Sem- Radio South- Web- ampton Central NEW! Music- Doap- Audio- space Flickr brainz MySpace Scrobbler QDOS exporter SIOC Wrapper profiles NEW! BBC BBC Crunch Semantic SW Later + John Base Web.org Conference NEW! Peel FOAF Corpus BBC TOTP profiles Playcount Jamendo Data Open- Geo- Guides names Revyu DBpedia flickr Magna- wrappr NEW! tune World RDF Book BBC NEW! Fact- Mashup Programmes Linked book DBLP riese MDB Euro- Berlin stat NEW! US NEW! Census Wiki- Yago Pub RKB lingvoj Guide Data company Explorer Open Cyc NEW! Gov- Track UMBEL DBLP W3C Project Hannover WordNet Guten- berg As of September 2008 Figure: 2008 Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 6/25
  • Introduction Highlights Conclusions The Web of Data is Growing 2009 Sem- Wiki- Surge Web- company Radio LIBRIS Central RDF ohloh Doap- Music- space Semantic Resex brainz Audio- Eurécom Flickr Web.org MySpace Scrobbler QDOS SW exporter Wrapper Conference IRIT Corpus Toulouse RAE BBC BBC Crunch 2001 FOAF SIOC ACM BBC Later + John Base Revyu Jamendo Peel profiles Sites Playcount TOTP Open- Buda- Data Guides pest DBLP BME flickr RKB Project Pub Geo- Euro- wrappr Explorer Guten- Virtuoso Guide names stat berg Pisa BBC Sponger eprints Programm Open es Calais New- riese World Linked ECS castle Fact- MDB South- IEEE book ampton Magna- Gov- tune RDF Book Track Mashup DBpedia lingvoj Freebase IBM US CiteSeer LAAS- Census W3C DBLP CNRS Data WordNet Hannover UniRef GEO UMBEL Species DBLP Berlin Reactome LinkedCT UniParc Open Taxonomy Cyc Yago Drug PROSITE Daily Bank Med Pub GeneID Homolo Chem Gene KEGG UniProt Pfam ProDom Disea- CAS Gene some ChEBI Ontology Symbol OMIM Inter Pro UniSTS PDB HGNC MGI PubMed As of March 2009 Figure: 2009 Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 7/25
  • Introduction Highlights Conclusions The Web of Data is Growing 2010 Sussex St. Reading Andrews NDL Audio- Lists Resource subjects t4gm MySpace scrobbler Lists Moseley (DBTune) (DBTune) RAMEAU Folk NTU SH lobid GTAA Plymouth Resource Lists Organi- Reading Lists sations Music The Open ECS Magna- Brainz Music DB tune Library LCSH South- (Data Brainz LIBRIS ampton Tropes lobid Ulm Incubator) (zitgist) Man- EPrints Resources chester Surge Reading biz. Music RISKS Radio Lists The Open ECS data. John Brainz Discogs Library PSH Gem. UB South- gov.uk Peel (DBTune) FanHubz (Data In- (Talis) Norm- Mann- ampton (DB cubator) Jamendo datei heim RESEX Tune) Popula- Poké- DEPLOY Last.fm tion (En- pédia Artists Last.FM Linked RDF AKTing) research EUTC (DBTune) (rdfize) LCCN VIAF Book Wiki data.gov Produc- Pisa Eurécom P20 Mashup semantic NHS .uk tions classical web.org (EnAKTing) Pokedex (DB Mortality Tune) PBAC ECS (En- AKTing) BBC MARC (RKB Budapest Program Codes Explorer) Energy education OpenEI BBC List Semantic Lotico Revyu OAI (En- CO2 data.gov mes Music Crunch SW AKTing) (En- .uk Chronic- Linked Dog NSZL Base AKTing) ling Event- MDB RDF Food IRIT America Media Catalog ohloh BBC DBLP ACM IBM Good- BibBase Ord- Wildlife (RKB Openly Recht- win nance Finder Explorer) Local spraak. Family DBLP legislation Survey Tele- New VIVO UF .gov.uk nl graphis York flickr (L3S) New- VIVO castle Times URI wrappr Open Indiana RAE2001 UK Post- Burner Calais DBLP codes statistics (FU VIVO CiteSeer Roma data.gov LOIUS Taxon iServe Berlin) IEEE .uk Cornell Concept Geo World data ESD Fact- OS dcs Names book dotAC stan- reference Project Linked Data NASA (FUB) Freebase dards data.gov Guten- .uk for Intervals (Data GESIS Course- transport DBpedia berg STW ePrints CORDIS Incu- ware data.gov bator) (FUB) Fishes ERA UN/ .uk of Texas Geo LOCODE Uberblic Euro- Species The stat dbpedia TCM SIDER Pub KISTI (FUB) lite Gene STITCH Chem JISC London Geo KEGG DIT LAAS Gazette TWC LOGD Linked Daily OBO Drug Eurostat Data UMBEL lingvoj Med (es) Disea- YAGO Medi some Care ChEBI KEGG NSF Linked KEGG KEGG Linked Drug Cpd GovTrack rdfabout Glycan Sensor Data CT Bank Pathway US SEC Open Reactome (Kno.e.sis) riese Uni Cyc Lexvo Path- way PDB Media Semantic totl.net Pfam HGNC XBRL WordNet KEGG KEGG Geographic (VUA) Linked Taxo- CAS Reaction rdfabout Twarql UniProt Enzyme EUNIS Open nomy US Census Publications Numbers PRO- ProDom SITE Chem2 UniRef Bio2RDF User-generated content Climbing WordNet SGD Homolo Linked (W3C) Affy- Gene GeoData Cornetto metrix Government PubMed Gene UniParc Ontology GeneID Cross-domain Airports Product DB UniSTS MGI Gen Life sciences Bank OMIM InterPro As of September 2010 Figure: 2010 Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 8/25
  • Introduction Highlights Conclusions What is Computational Intelligence? Branch of AI focused on heuristics Applicable in contexts where exact solutions are unknown / changing / too expensive / not necessary Fuzzy Systems Neural Networks Evolutionary Computing Swarm Intelligence Artificial Immune Systems ... Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 9/25
  • Introduction Highlights Conclusions Motivation Why does the WoD need Computational Intelligence? Properties of the WoD Complex system in constant evolution Everybody can state everything Growing size & privacy issues ask for decentralisation Computational Intelligence provides adaptiveness, robustness and scalability. Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 10/25
  • Introduction Highlights Conclusions Outline 1 Introduction 2 Highlights 3 Conclusions Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 11/25
  • Introduction Highlights Conclusions Evolutionary Computing for the WoD Figure: The Evolution Loop Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 12/25
  • Introduction Highlights Conclusions Evolutionary Computing for the WoD Advantageous properties Adaptation Simplicity Interactivity: Anytime, user in the loop Scalability and robustness Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 13/25
  • Introduction Highlights Conclusions Evolutionary Computing for the WoD EC techniques are suited for situations when the search space is very large or changing. Evolutionary-based approaches for combinatorial optimization Ontology mapping: as genetic algorithm and Particle Swarm Optimisation SPARQL RDF query answering Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 14/25
  • Introduction Highlights Conclusions Evolutionary Computing for the WoD SPARQL Query engine ’eRDF’: http://erdf.nl/ ?city rdf:type City guess Amsterdam rdf:type City ?city hasMayor ?mayor Amsterdam hasMayor JobCohen ?mayor name ”Job Cohenn” JobCohen name ”Job Cohenn” gu es check s ag ai n Amsterdam rdf:type City Amsterdam hasMayor JobCohen JobCohen name ”Job Cohenn” output best • Approximation, anytime behaviour • Like? search engine Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 15/25
  • Introduction Highlights Conclusions Collective Intelligence for the WoD Individuals showing intelligence when acting as a group. Notion of emergent behaviour. Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 16/25
  • Introduction Highlights Conclusions Collective Intelligence for the WoD Collective Intelligence approaches for the Semantic Web Semantic gossiping to overcome problems related to schema heterogeneity PIAF: principles of stigmergy and artificial ants to model data flows in social networks Self-Organising Swarm-based triple store Semantic Web Reasoning by Swarm Intelligence Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 17/25
  • Introduction Highlights Conclusions SW Reasoning by Swarm Intelligence Emergence of implicit or explicit knowledge Example: TransitiveProperty (p) ∧ p(?x, ?y ) ∧ p(?y , ?z) → p(?x, ?z) TransitiveProperty(lubm:subOrganizationOf) Department f lu nO mb io :su at iz bO an rg rg an bO iz :su at io bm On lu f ResearchGroup University Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 18/25
  • Introduction Highlights Conclusions SW Reasoning by Swarm Intelligence http://beast-reasoning.net Department f lu O bm n io :su at iz bO an rg rg an bO iz :su at io bm nO lu f ResearchGroup University Figure: Motivating example: a transitive beast in action Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 19/25
  • Introduction Highlights Conclusions SW Reasoning by Swarm Intelligence http://beast-reasoning.net Department f lu O bm n io :su at iz bO an rg rg an bO iz :su at io bm nO lu f ResearchGroup University Figure: Motivating example: a transitive beast in action Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 20/25
  • Introduction Highlights Conclusions SW Reasoning by Swarm Intelligence http://beast-reasoning.net Department f lu O bm n io :su at iz bO an rg rg an bO iz :su at io bm nO lu f lubm:subOrganizationOf ResearchGroup University Figure: Motivating example: a transitive beast in action Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 21/25
  • Introduction Highlights Conclusions Outline 1 Introduction 2 Highlights 3 Conclusions Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 22/25
  • Introduction Highlights Conclusions Pros & Cons What to gain: Adaptation, learning Design simplicity Scalability and robustness Anytime and interactive behaviour What to loose: Determinism Completeness Precision Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 23/25
  • Introduction Highlights Conclusions What can CI gain from the SW? Simple, Robust, Approximate Computational Intelligence Semantic Web ? CI may use SW technologies to replace ad-hoc knowledge representation techniques Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 24/25
  • Introduction Highlights Conclusions Questions? Christophe Guer´t, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data e 25/25