• No results found

Creating Knowledge From Interlinked Data From Big Data to Smart Data

N/A
N/A
Protected

Academic year: 2021

Share "Creating Knowledge From Interlinked Data From Big Data to Smart Data"

Copied!
38
0
0

Loading.... (view fulltext now)

Full text

(1)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Creating Knowledge From

Interlinked Data – From Big Data

to Smart Data

Prof. Dr. Sören Auer

2 5 . 0 9 . 2 0 1 4

(2)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

The Web evolves into a Web of Data

2

Linked Open Data

Facebook

Open Graph

(3)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Die Evolution des Web

3

Web 1.0 -

Hypertext

Static Web pages

Hyperlinks

Link directories

Web 2.0 –

Social Apps

Social Web

Crowd-sourcing

Mashups

Web 3.0 –

Linked Data

REST APIs, RDF,

JSON-LD

Vocabularies

Rich-snippets,

Semantic Search

1990

2000

2010

Intranet 1.0 -

Hypertext

Static Intranet pages

Keyword search

Hyperlinks

Intranet 2.0 –

Social Enterprise Apps

Salesforce

Crowd-sourcing

Mashups

Intranet 3.0 –

Enterprise Data Intranet

URI Scheme

Enterprise taxonomies /

knowledge bases

RDB2RDF Mapping

1995

2005

2015

& Intranets

(4)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Towards Information Oriented Architectures

4

IBM DeveloperWorks: The role of semantic models in smarter industrial operations

(5)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Linked Data Principles

1.

Use URIs to identify the “things” in your data

2.

Use http:// URIs so people (and machines) can

look them up on the web

3.

When a URI is looked up, return a des cription of

the thing (in RDF format)

4.

Include links to related things

http://www.w3.org/DesignIssues/LinkedData.html

(6)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

1. Uses RDF Data Model

Linked Data in a Nutshell

LAC

Nieuwegein

27.11.2014

NAF

organizes

starts

takesPlaceIn

2. Is s erialis ed in triples :

NAF organizes LAC .

LAC

starts “20141127”^^xsd:date .

LAC

takesPlaceAt

dbpedia:Nieuwegein .

3. Publis h in the Intranet (or on the Web)

(7)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Encode Relational Data in RDF

Primary keys become subjects

Columns become properties

Cells become objects

Mapping Standard: W3C R2RML Relational to RDF Mapping Language

(8)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Encode Taxonomic Data in RDF

Vehicle

a

rdfs:class

Car

rdfs:subClassOf

Vehicle

Truck

rdfs:subClassOf

Vehicle

Cabrio

rdfs:subClassOf

Car

….

8

Heavy Rigid

Light Rigid

Truck

Cabrio

Car

Combination

Vehicle

Sedan

Hatchback

Hot Hatch

(9)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

RDF is the Lingua Franca of Data Integration

RDF is s im ple

We can easily encode and com bine all kinds of data m odels (relational,

taxonomic, graphs, object-oriented, …)

RDF supports dis tributed data and s chem a

We can s eam les s ly ev olv e simple semantic representations (vocabularies) to

more complex ones (e.g. ontologies)

Small repres entational units (URI/IRIs, triples) facilitate mixing and mashing

RDF can be viewed from m any pers pectiv es : facts, graphs, ER, logical axioms,

graphs, objects

RDF integrates w ell w ith other form alis m s - HTML (RDFa), XML (RDF/XML),

JSON (JSON-LD), CSV, …

Linking and referencing between different knowledge bases, systems and

platforms facilitates the creation of sustainable data ecos y s tem s

(10)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

The emerging Web of Data

2008

2007

2008

2008

2008

2009

2009

2010

Linking Open Data cloud diagram, by

Richard Cyganiak and Anja Jentzsch.

http://lod-cloud.net/

(11)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

(12)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Linked Enterprise Data Principles

1.

Evolve existing existing taxonomies into enterprise knowledge bases/hubs

2.

Establish a enterprise wide URI scheme

3.

Equip existing information systems in your intranet with Linked Data

interfaces

4.

Establish links between related information

(13)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Linked Enterprise Data Advantages

Light-weight linked data integration complements

more complex SOA architectures

Unified data (access) model simplifies data integration

Increase standardization while preserving diversity

Facilitate information flows along supply and value

creation chains

Dramatically reduce data integration costs, increase

enterprise flexibility

(14)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

F

ro

m

I

n

tr

a

n

e

t

to

E

n

te

rp

ri

se

D

a

ta

W

e

b

a

ro

u

n

d

a

k

n

o

w

le

d

g

e

h

u

b

Auer, Fris chm uth, Klím ek, Unbehauen, Holzweißig, Marquardt:

Linked Data in Enterpris e

(15)

Creating Kn o w l ed g e

out of Interlinked Data

When just data shall be exchanged and

integrated SOA is quite expensive

Facilitates

data integration

along value-chains

within and across enterprises

(16)

Creating Kn o w l ed g e

out of Interlinked Data

Linked Enterprise Intra Data Webs

fill the gap

between Intra-/Extranets and EIS/ERP

Unstructured Information

Management

Structured Information

Management

Support the long tail of enterprise information domains

Human-resources

Requirements engineering

(17)

Extraction

Curation

Quality

Linking

Integration

Publication

Visualization

Analysis

Extraction, Curation

Quality, Linking,

Integration

Publication,

Visualization,

Analysis

Extraction, Curation, Quality,

Linking, Integration, Publication,

Visualization, Analysis

Data Value Chains

today

Data Value Chains

tomorrow

Increased Specialization

Separation of concerns

More interdisciplinarity

(18)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Inter-linking/

Fus ing

Clas s

ifi-cation/

Enrichm ent

Quality

Analy s is

Evolution /

Repair

S earch/

Brows ing/

Ex ploration

Ex traction

S torage/

Query ing

Manual

rev is ion/

authoring

Linked Data

Lifecycle

(19)

http://lod2.eu

Creating Knowledge out of Interlinked Data

Virtuoso RDF Store

(conductor,

sparql, isparql, ods)

Virtuoso

sponger

lod2webapi

RDFAuthor

Limes

ORE

D2R

Semantic

Spatial

Browser

sparqlproxy

SigmaEE

OntoWiki

LOD open

refine

Silk-latc

stanbol

valiant

Dbpedia

Spotlight

SPARQLed

PoolParty

Sieve

PoolParty

Extractor

Inter-linking/ Fusing Classifi-cation/ Enrichmen t Quality Analysis Evolution / Repair Search/ Browsing/ Exploratio n Extraction Storage/ Querying Manual revision/ authoring

dl-learner

CubeViz

LOD2

demonstrator

R2R

rdf-dataset-integration

Silk

SIREn

Sparqlify

CSVImpor

t

Dbpedia

Spotlight

UI

CKAN

(source)

Mondeca Sparql

Endpoint Status

Sindice

(source)

Web Linkage

Validator

Dbpedia

(source)

LOD2 Stack Components

lodms

LOD2 stat.

Workbench

LOD2 Authentication

Component

Data Cube

Validation Tool

Data Cube

Merging

Tool

Data Cube

Slicing Tool

LOD2

Provenance

Component

(20)

http://lod2.eu

Creating Knowledge out of Interlinked Data

• Core compontent of the LOD2

stack including support,

maintenance, industrial-grade

• In production used bz: Wolters

Kluwer, Daimler, EU

Commission

• Strategic further development

in R&D projects

(21)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Linked Enterprise Data

(22)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

22

Daimler CIO Michael Gorriz

receives European Data

Innovator Award

(23)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

23

Classic search

(24)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Creation of a knowledge base consisting of:

1. car m odels databas e

(25)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Subject

Predicate

(26)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Managem ent of Enterpris e Taxonom ies w ith

OntoWiki

Based on the W3C SKOS standard

Corporate Language Management

at Daimler: 500k

concepts in 20 languages

Creation of a knowledge base:

(27)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Semantic search suggestions based

on the interlinked knowledge base

(28)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

(29)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

(30)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

(31)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Cortex - Semantic Search

(32)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Semantische Suchplattform IAIS-Cortex

Herz der Deutschen Digitalen Bibliothek

Flexible Data Integration (Import)

Powerful toolbox for aggregation

of heterogenous data sources

>2.000 Data Providers

Reliable Data Management

Based on filesystem or cloud

technology

>10.000 concurrent users

Individual Access

Powerful semantic search and

performant access of objects

(33)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Deutsche Digitale Bibliothek

(34)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

(35)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

(36)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

(37)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

(38)

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Fraunhofer-Institut IAIS

Schloss Birlinghoven

53754 Sankt Augustin

www.iais.fraunhofer.de

Die Rechte der Logos und Bilder verbleiben bei ihren Eigentümern.

Prof. Dr. Sören Auer

Tel:

02241-14 1915

eMail:

soeren.auer@iais.fraunhofer.de

Kontakt

http://www.ibm.com/developerworks/xml/library/x-ind-semanticmodels/ http://www.w3.org/DesignIssues/LinkedData.html © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

References

Related documents

As shown in the figure, cells and arrive at input ports 1 and 3 and they both must be sent to layer 2; this is because the internal line rate between the demultiplexor and each

Given the inherent properties of PFOS, 3 together with demonstrated or potential environmental concentrations that may exceed the effect levels for certain higher trophic level

From these results, it is clear that women experience disrespectful maternity care by some healthcare workers, particularly by female staff. The strong support for the presence

The elected officials were interviewed, and their responses were compared to the objectives of the study, the literature reviewed, the case study of the Department of

fender. The rubber washer can provide vibration isola- tion and seems to have been part of original re- mote reservoir installations. Lock washers should be used behind the

Fig- 5: Membership function of Packet Delivery Ratio Input After analyses the traditional fuzzy approach, the comparison between the traditional Fuzzy and Proposed ANFIS

Gruppo pompante di grande potenza oilless senza problemi di spunto anche a basse temperature e senza manutenzione per un aria priva di impurità. High-power oil-free pumping

Abnormal returns for all the nonconvertible bonds of a sample of acquirer firms that announced and completed a merger/acquisition between 1979 to April 30, 1998 and matched to