Approximation and Self-Organisation on the Web of Data

Introduction Highlights Conclusions

Approximation and Self-Organisation on the Webof Data

BNAIC 2010: Semantic Web / Intelligent Systems

Christophe Gueret, Kathrin Dentler and Stefan Schlobach

October 25th 2010

Christophe Gueret, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data 1/25


Outline

1 Introduction

2 Highlights

3 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



The Web of Data is Growing2007

SWConference

Corpus

DBpedia

RDF Book Mashup

DBLPBerlin

Revyu

Project Guten-berg

FOAF

Geo-names

Music-brainz

Magna-tune

Jamendo

World Fact-book

DBLPHannover

SIOC

Sem-Web-

Central

Euro-stat

ECS South-ampton

BBCLater +TOTP

Fresh-meat

Open-Guides

Gov-Track

US Census Data

W3CWordNet

flickrwrappr

Wiki-company

OpenCyc

NEW! lingvoj

Onto-world

NEW!

NEW!NEW!

Figure: 2007




SWConference

Corpus

RDF Book Mashup

Revyu

Project Guten-berg

Music-brainz

Magna-tune

Jamendo

DBLPHannover

SIOCprofiles

Sem-Web-

Central

ECS South-ampton

BBCLater +TOTP

Doap-space

Open-Guides

Gov-Track

US Census Data

W3CWordNet

Wiki-company

OpenCyc

lingvoj

BBCJohnPeel

FlickrexporterQDOS

RKB Explorer

riese

UMBEL

Pub Guide

FOAFprofiles

Geo-names

flickrwrappr

YagoNEW!

NEW!

NEW!

World Fact-book

SemanticWeb.org

BBCPlaycount

Data

SurgeRadio

NEW!

NEW!

MySpaceWrapper

NEW!Audio-

Scrobbler

CrunchBase

NEW!

As of September 2008

LinkedMDB

DBLPBerlin

DBpedia

Euro-stat

NEW!BBCProgrammes

NEW!

Figure: 2008




As of March 2009

LinkedCTReactome

Taxonomy

KEGG

PubMed

GeneID

Pfam

UniProt

OMIM

PDB

SymbolChEBI

Daily Med

Disea-some

CAS

HGNC

InterPro

Drug Bank

UniParc

UniRef

ProDom

PROSITE

Gene Ontology

HomoloGene

PubChem

MGI

UniSTS

GEOSpecies

Jamendo

BBCProgramm

es

Music-brainz

Magna-tune

BBCLater +TOTP

SurgeRadio

MySpaceWrapper

Audio-Scrobbler

LinkedMDB

BBCJohnPeel

BBCPlaycount

Data

Gov-Track

US Census Data

riese

Geo-names

lingvoj

World Fact-book

Euro-stat

IRIT Toulouse

SWConference

Corpus

RDF Book Mashup

Project Guten-berg

DBLPHannover

DBLPBerlin

LAAS- CNRS

Buda-pestBME

IEEE

IBM

Resex

Pisa

New-castle

RAE 2001

CiteSeer

ACM

DBLP RKB

Explorer

eprints

LIBRIS

SemanticWeb.org Eurécom

ECS South-ampton

RevyuSIOCSites

Doap-space

Flickrexporter

FOAFprofiles

flickrwrappr

CrunchBase

Sem-Web-

Central

Open-Guides

Wiki-company

QDOS

Pub Guide

Open Calais

RDF ohloh

W3CWordNet

OpenCyc

UMBEL

Yago

DBpediaFreebase

Virtuoso Sponger

Figure: 2009Christophe Gueret, Kathrin Dentler and Stefan Schlobach — Approximation and Self-Organisation on the Web of Data 7/25



As of September 2010

MusicBrainz

(zitgist)

P20

YAGO

World Fact-book (FUB)

WordNet (W3C)

WordNet(VUA)

VIVO UFVIVO

Indiana

VIVO Cornell

VIAF

URIBurner

Sussex Reading

Lists

Plymouth Reading

Lists

UMBEL

UK Post-codes

legislation.gov.uk

Uberblic

UB Mann-heim

TWC LOGD

Twarql

transportdata.gov

.uk

totl.net

Tele-graphis

TCMGeneDIT

TaxonConcept

The Open Library (Talis)

t4gm

Surge Radio

STW

RAMEAU SH

statisticsdata.gov

.uk

St. Andrews Resource

Lists

ECS South-ampton EPrints

Semantic CrunchBase

semanticweb.org

SemanticXBRL

SWDog Food

rdfabout US SEC

Wiki

UN/LOCODE

Ulm

ECS (RKB

Explorer)

Roma

RISKS

RESEX

RAE2001

Pisa

OS

OAI

NSF

New-castle

LAAS

KISTIJISC

IRIT

IEEE

IBM

Eurécom

ERA

ePrints

dotAC

DEPLOY

DBLP (RKB

Explorer)

Course-ware

CORDIS

CiteSeer

Budapest

ACM

riese

Revyu

researchdata.gov

.uk

referencedata.gov

.uk

Recht-spraak.

nl

RDFohloh

Last.FM (rdfize)

RDF Book

Mashup

PSH

ProductDB

PBAC

Poké-pédia

Ord-nance Survey

Openly Local

The Open Library

OpenCyc

OpenCalais

OpenEI

New York

Times

NTU Resource

Lists

NDL subjects

MARC Codes List

Man-chesterReading

Lists

Lotico

The London Gazette

LOIUS

lobidResources

lobidOrgani-sations

LinkedMDB

LinkedLCCN

LinkedGeoData

LinkedCT

Linked Open

Numbers

lingvoj

LIBRIS

Lexvo

LCSH

DBLP (L3S)

Linked Sensor Data (Kno.e.sis)

Good-win

Family

Jamendo

iServe

NSZL Catalog

GovTrack

GESIS

GeoSpecies

GeoNames

GeoLinkedData(es)

GTAA

STITCHSIDER

Project Guten-berg (FUB)

MediCare

Euro-stat

(FUB)

DrugBank

Disea-some

DBLP (FU

Berlin)

DailyMed

Freebase

flickr wrappr

Fishes of Texas

FanHubz

Event-Media

EUTC Produc-

tions

Eurostat

EUNIS

ESD stan-dards

Popula-tion (En-AKTing)

NHS (EnAKTing)

Mortality (En-

AKTing)Energy

(En-AKTing)

CO2(En-

AKTing)

educationdata.gov

.uk

ECS South-ampton

Gem. Norm-datei

datadcs

MySpace(DBTune)

MusicBrainz

(DBTune)

Magna-tune

John Peel(DB

Tune)

classical(DB

Tune)

Audio-scrobbler (DBTune)

Last.fmArtists

(DBTune)

DBTropes

dbpedia lite

DBpedia

Pokedex

Airports

NASA (Data Incu-bator)

MusicBrainz(Data

Incubator)

Moseley Folk

Discogs(Data In-cubator)

Climbing

Linked Data for Intervals

Cornetto

Chronic-ling

America

Chem2Bio2RDF

biz.data.

gov.uk

UniSTS

UniRef

UniPath-way

UniParc

Taxo-nomy

UniProt

SGD

Reactome

PubMed

PubChem

PRO-SITE

ProDom

Pfam PDB

OMIM

OBO

MGI

KEGG Reaction

KEGG Pathway

KEGG Glycan

KEGG Enzyme

KEGG Drug

KEGG Cpd

InterPro

HomoloGene

HGNC

Gene Ontology

GeneID

GenBank

ChEBI

CAS

Affy-metrix

BibBaseBBC

Wildlife Finder

BBC Program

mesBBC

Music

rdfaboutUS Census

Media

Geographic

Publications

Government

Cross-domain

Life sciences

User-generated content

Figure: 2010



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

...



MotivationWhy 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, robustnessand scalability.



Outline

1 Introduction

2 Highlights

3 Conclusions



Evolutionary Computing for the WoD

Figure: The Evolution Loop




Advantageous properties

Adaptation

Simplicity

Interactivity: Anytime, user in the loop

Scalability and robustness




EC techniques are suited for situations when the search spaceis very large or changing.

Evolutionary-based approaches for combinatorial optimization

Ontology mapping: as genetic algorithm and ParticleSwarm Optimisation

SPARQL RDF query answering



Evolutionary Computing for the WoDSPARQL Query engine ’eRDF’: http://erdf.nl/

?city rdf:type City?city hasMayor ?mayor

?mayor name ”Job Cohenn”

Amsterdam rdf:type CityAmsterdam hasMayor JobCohenJobCohen name ”Job Cohenn”

Amsterdam rdf:type CityAmsterdam hasMayor JobCohenJobCohen name ”Job Cohenn”

guess

check

output best

guessagain

• Approximation, anytime behaviour• Like? search engine



Collective Intelligence for the WoD

Individuals showing intelligence when acting as a group.Notion of emergent behaviour.



Collective Intelligence for the WoD

Collective Intelligence approaches for the Semantic Web

Semantic gossiping to overcome problems related toschema heterogeneity

PIAF: principles of stigmergy and artificial ants to modeldata flows in social networks

Self-Organising Swarm-based triple store

Semantic Web Reasoning by Swarm Intelligence



SW Reasoning by Swarm IntelligenceEmergence of implicit or explicit knowledge

Example:TransitiveProperty(p) ∧ p(?x , ?y) ∧ p(?y , ?z)→ p(?x , ?z)TransitiveProperty(lubm:subOrganizationOf)

ResearchGroup

Department

University

lubm

:subO

rgan

izat

ionO

f lubm:subO

rganizationOf



SW Reasoning by Swarm Intelligencehttp://beast-reasoning.net

ResearchGroup

Department

University

lubm

:subO

rgan

izat

ionO

f lubm:subO

rganizationOf

Figure: Motivating example: a transitive beast in action




ResearchGroup

Department

University

lubm

:subO

rgan

izat

ionO

f lubm:subO

rganizationOf





ResearchGroup

Department

University

lubm

:subO

rgan

izat

ionO

f lubm:subO

rganizationOf

lubm:subOrganizationOf




Outline

1 Introduction

2 Highlights

3 Conclusions



Pros & Cons

What to gain:

Adaptation, learning

Design simplicity

Scalability and robustness

Anytime and interactive behaviour

What to loose:

Determinism

Completeness

Precision



What can CI gain from the SW?

ComputationalIntelligence Semantic Web

Simple, Robust,Approximate

?

CI may use SW technologies to replace ad-hoc knowledgerepresentation techniques



Questions?


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