Creating Data Value Chains by Linking Enterprise Data - … Data Paradigm as a Basis for I40, ......

© Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Creating Data Value Chains by Linking

Enterprise Data

How the interlinking of distributed and heterogeneous data can facilitate enterprise development, production and services

© Fraunhofer-Allianz Big Data 2

The three Big Data „V“ – Variety is often neglected

Quelle: Gesellschaft für Informatik

Dr. Dirk Hecker


Proaktive Maintenance at Rolls Royce

New Business Model integrating Sensor Data & Big Data Analytics

Dr. Dirk Hecker

Condition Monitoring, Proaktive Wartung, „Power-by-the-hour“,

as-a-service Business Model – Payment by flight hours

Quelle: www.springboeck.ch/SR_Technics.htm

© Mark Hillary | Flickr


The rolling Smartphone

New Business Models for the Automotive Industry with Data Value Chains

Dr. Dirk Hecker

Windshield wiper as rain sensors for micro wether prognosis

Automotive industry can become data provider for other industries

Qu

elle

: GT

ÜQ

uelle: w

ww

.farmin

g-sim

ulato

r.com


Predictive Analytics

Dr. Dirk Hecker

From Business Intelligence to Big Data Analytics

Business Intelligence Monitoring Predictive Analytics

What happenedbefore?

What happens now?What will happen

soon?What should

happen?

Prescriptive Analytics

„the last Mile“

“prescriptive analytics suggests decision options on how to take advantage of a future opportunity”

Quelle: BMW Quelle: www.7-forum.com Quelle: BMW Quelle: Volvo


Expansion of IT companies in manufacturing realms

Dr. Dirk Hecker

Possible disruption of business models through digitization

© Fraunhofer · Seite 7

Bilder: ©FotoliaFrancesco De Paoli, Nmedia, hakandogu

Semantic Data Linking for Enterprise Data Value Chains

Data Lake Pure Internet

centralized, monopolisticfederated, secure, „trusted“,

standard-basedcompletely dezentral, open,

unsecure

Data management Central Repository Decentral Decentral

Data Ownership Central Decentral Decentral

Data Linking Single provider Federated, on demand Missing

Data Security Bilateral Certified system Bilateral

Market structure Central Provider Role system Unstructured

Transport infrastructure Internet Internet Internet

Enterprise Data Value Chains

© Fraunhofer · Seite 8 --- VERTRAULICH ---Bildquellen: Istockphoto

Enterprise Data Value Chains

Service A

Service C

Service E

Service B

Service D

Service G

Service F

Enterprise 4

Enterprise 1

Enterprise 6

Enterprise 2Enterprise 3

Enterprise 5

All Data stays with its Ownern and are controlled and secured. Only on request for a service datawill be shared. No central platform.


The Semantic Web Layer Cake 2001

http://www.w3.org/2001/10/03-sww-1/slide7-0.html

• Monolithic based on XML

• Focus on heavyweight semantic (ontologies, logic, reasoning)

http://www.w3.org/2001/10/03-sww-1/slide7-0.html


The Semantic Web Layer Cake 2015 –

“A Little Semantics Goes a Long Way”

Unicode URIs

XML JSON CSV RDB HTML

RDF

RDF/XML JSON-LD CSV2RDF R2RML RDFa

RDF Data Shapes RDF-Schema

Vocabularies

OntologienSKOS Thesauri

LogikSWRL Regeln

SPARQL

(Acc

ess

co

ntr

ol)

, Sig

nat

ur,

E

ncr

ypti

on

(HT

TP

S/C

ER

T/D

AN

E),

• Lingua Franca of Data integration with many technology interfaces (XML, HTML, JSON, CSV, RDB,…)

• Focus on lightweight vocabularies, rules,thesauri etc.


Linked Data Paradigm as a Basis for I40, Cyber-Physical

Systems and Big Data Integration

Entities (people, places, organisations etc.) are identified using URIs in a worldwide unique way

Data (Resources) describing these entities is made available using the HTTP/HTTPS protocoll when dereferencing the URIs

The entity descriptions made available via HTTP/HTTPS are represented according to the W3C Resource Description Format (RDF)

Entity descriptions in RDF content Links to related entities / concepts / resources

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

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


RDF & Linked Data in a Nutshell

1. Graph based RDF data model consisting of SPO statements (facts)

SEMIC2015

dbpedia:Riga

05.05.2015

Joinupconf:organizes

conf:starts

conf:takesPlaceIn

2. Serialisiert in RDF Triple:

Joinup conf:organizes SEMIC2015 .

SEMIC2015 conf:starts “2015-05-05”^^xsd:date .

SEMIC2015 conf:takesPlaceAt dbpedia:Riga .

3. Publication under URL in Web, Intranet, Extranet

Subject Predicate Object


Linked (Open) Data: The RDF Data Model

RDF = Resource Description Framework

13

located in

label

industry

headquarters

full nameDHL

Post Tower

162.5 m

Bonn

Logistics Logistik

DHL International GmbH

height物流

label


RDF Data Model (a bit more technical)

Graph consists of:

Resources (identified via URIs)

Literals: data values with data type (URI) or language (multilinguality integrated)

Attributes of resources are also URI-identified (from vokabularies)

Various data sources and vocabularies can be arbitrarily mixed and meshed

URIs can be shortened with namespace prefixes; e.g. dbp: → http://dbpedia.org/resource/ 14

gn:locatedIn

rdfs:label

dbo:industryex:headquarters

foaf:namedbp:DHL_International_GmbH

dbp:Post_Tower

"162.5"^^xsd:decimal

dbp:Bonn

dbp:Logistics

"Logistik"@de

"DHL International GmbH"^^xsd:string

ex:height"物流"@zh

rdfs:label

rdf:value

unit:Meter

ex:unit


I40 Example –

Semantic Description of Sensor Data

myd:m123245 rdf:type i40:SensorMeasurement .

myd:m123245 rdf:hasValue “40”^^i40:DegreeCelsius .

myd:m123245 i40:hasMeasureTime “2015-03-24T12:38:54:12Z”^^xsd:DateTime .

myd:m123245 i40:fromSensor myd:Sensor123 .

...

# ^ subject ^ predicate ^ object


Linked Data vs. XML

from the Data Integration Perspective

Linked Data

XXXXXO

XML

-O---X

Provenance

Data integration

Evolution

Extensibility

Reusability

Validation

Beware: This comparison would look very different from a (office) document (hypertext, spreadsheets, presentation) format perspective.


Golf7_Infotainment

Data Value Chains using Linked Data

Golf 7

Zulieferer

70.000

5kg

SMARTi_LU

90g5T

hasComponent

75.000500.000

Aggregation of Emmissions in the Value Chain

Propagation of sales prognoses in the value chain

Map data, parking, gas stations,Points-of-Interest…

Open Linked Data


IDS I40: Semantische Modelle als Brücke zwischen Shop

& Office Floor


Adding a Linked Data Layer to the Internet Architecture

Linked Data Layer can possibly be also integrated in lower levels of the Internet Architecture


>100 Billion facts are avaialbale as Linked Open Data

Many Domains are well covered, e.g. Geo data, Pharma & life-sciences

Great Potential for Linking with internal Enterprise data sources

http://lod-cloud.net

(August 2014)

20

http://lod-cloud.net/


Provisioning of all types of Enterprise Data

as Linked Data

Meta-data

Description of the Data

Vokabulare

Structure of the Data

Daten

Ground Truth

Raw data

People, Places, Organisations, Sensor data, Production data,

Metadata

Lizence informationen, Provenance, Versioning, Documentation

Vocabularies

Definitionen of Class and Property(-hierarchies), typical structures (W3C Data Shapes)


Volume, Velocity & Variety


Example Mobility Vokabular MobiVoc –

Supporting the mobility of humans by the mobility of data

Interlinking and Integration of Information fromavariety of different sources (map data, cardata, weather, public transport, events,…) –various organizations, actors, formats, …

Goal is to increase the interlinking and fusion ofdata through the use of extensible, light-weight vocabularies

Adresses weaknesses of XML-based DATEXII standard – closedness, lack of extensibility

Initiative of ITA Automotive Service Partner e.V. with BMW, Microsoft, Accenture, Fraunhofer, BROX/eccenca

Collaborative, agile vocabulary development on GitHub


Example eCl@ss – Semantic Model for Material,

Products and Services

Comprehensive taxonomic classification scheme for materials, products and services

9.0 BASIC from 2014-12-08 comprisesClasses: 40,870Properties: 16,845Values: 14,365

eCl@ssXML is based on the ISO 13584-32 ontoML file format, the XML representation of the ISO 13584 (PLIB) ontology

eClassOWL - The Web Ontology for Products and Services an RDF/OWL representation of eCl@ss


Summary:

Linked Data for semantic interoperability

Problem Linked Data Approach Example

1. Unique Identifikation of (data) objects

URIs (analog Web addresses) for Identification of arbitrary objects

https://data.vw.de/car/Golf7

2. Adressability and Data accessWeb Protokols HTTP/HTTPS for De-

Referencing and access of data

3. Semantic Data Representation Triple & Graph-based RDF Data ModelGolf7 producedIn Wolfsburg

4. Wide Interlinking of DataURIs serve as “Data Links” between

distributed Databases

5. Domain-specific Data structuresCreation of interlinked, modular, reuseable

vokabularies

6. Security-by-DesignCertificates, Encryption, Authentification as

Internet Banking

FOAF


Big Data is not Just Volume and Velocity

Variety is the real challenge

Dr. Dirk Hecker

Standardisationon all levels

Smart Data(embracing Variety)

Inter-organization collaboration & data exchange

Usage of Open Data

Data security & privacy -integral part of innovative services, without blocking them


Dr. Dirk Hecker

Prof. Dr. Sören Auer, [email protected]

Fraunhofer-Allianz Big Data | Fraunhofer IAIS

Schloss Birlinghoven

53757 Sankt Augustin

www.iais.fraunhofer.de

www.bigdata.fraunhofer.de

„DO MORE WITH [BIG|LINKED|OPEN] DATA!“

© vege | Fotolia

Luxembourg, 16-17 Nov 2015

http://2015.data-forum.eu/

http://www.iais.fraunhofer.de

http://www.bigdata.fraunhofer.de

http://2015.data-forum.eu/

Creating Data Value Chains by Linking Enterprise Data - … Data Paradigm as a Basis for I40, ......

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