Content Repositories vs Knowledge Bases

Content Repositories vs. Knowledge Bases…

12 November, 2009, Gokce Banu Laleci, SRDC

Outline

| Content Management Systems and Content Repositories

| Strength of Ontologies, Reasoners, Kowledge bases

| Possible Synergy: How can semantic web tools can be exploited by CMSs…

| Possible architecture…

(c) Interactive Knowledge 2009-2012

Slide 2

Content Management Systems

| Content management system is designed to support a content management cycle | creation and collection of content| the publication of content for access by users and/or other systems| the management of these content

| Content Repository: a high-level information management system that is a superset of traditional data repositories, [which] implements 'content services‘:| author based versioning| full textual searching| fine grained access control| content categorization| content event monitoring

| Content Repositories implemented| RDBMS| File Systems| XML DBs| ….


Slide 3

How Metadata is added, Supported search methods..

| Metadata| Organizing the content as hierarchies| Through properties/parameters of nodes/objects/documents

| Free format values, or selected from a constrained vocabulary ( which can be a taxonomy)

| Can be used as content categories| By representing relationships between nodes/objects/documents

| Taxonomies can be represented as tags hierarchies (as a hierarchy of nodes..)

| Node/Object/Document types| XML Schemas

| Search| Full-text Search

| Lucene, SOLR, Text indices in databases| Field-based searches| Structured Query methods over Repository Data Model

| SQL-based, XPath based| Synonym check

| Through a list


Slide 5

Strength of Semantic Technologies1

| An ontology is an engineering artifact consisting of: | A vocabulary used to describe (a particular view of) some domain| An explicit specification of the intended meaning of the vocabulary.

| Almost always includes how concepts should be classified| Constraints capturing additional knowledge about the domain

| Through rules

| Ideally, an ontology should:| Capture a shared understanding of a domain of interest| Provide a formal and machine manipulable model of the domain

| Aims “machine understanding”| Understanding is closely related to reasoning

| Recognising semantic similarity in spite of syntactic differences

| Recognising implicit consequences given explicitly stated facts

| An ontology together with a set of instances of its classes constitutes a knowledge base


Slide 6

Examples…


Slide 7

Workspace1

NewsSubjectCodes

Health

EconomyBusinessFinance

Disaster/Accident

Education

NewsArticles

Article2

Article1

Article3

Disease

HealthTreatment Illness

Cancer ViralDiseases

classifiedBy

classifiedBy

classifiedBy

-NewsSubjectCodes

-ArtsCultureEntertainment

-DisasterAccident

-EconomyBusinessFinance

-Education

-EnvironmentalIssues

-Health

-HealthTreatment

-Illness

-ViralDisease

-Cancer

-.........

-Medicine

-SocialIssues

Article1

instanceOf

instanceOf-Disease

Article2

Article3

instanceOf

A. Content Repository B. Apart of the Extracted Ontology

SwineFluRule: If a Disease iscausedby PathogenicAgent then it is an infectiousDisease

Facts: Virus Is a PathogenicAgent Fungi Is a PathogenicAgent ViralDisease iscausedby Virus

Search: Find me the “Health” related ArticlesResults: Article1, Article 2, Article 3 (due to subsumption relations in the ontology)

Search: Find me the Articles related with “Infectious Diseases”

Results: Article 3

How Semantic Technologies can be exploited by CMSs..


Slide 8

Approaches for semantically enabled content management

| Semantic / Ontology enabled Web Portals2,3

| Using ontologies as a backbone of Web portals| Designing the Schema based on Ontologies| Ontology enabled Data Collection| Ontology based Navigating| Ontology based Search mechanisms supported through

reasoning


Slide 9

Approaches for semantically enabled content management

| Semantic Wikis4,5

| Ontology enabled links| Ontology enabled

enhanced search and browsing

| Semantic / Ontology enabled CMS Systems6,7

| Developing a domain Ontology

| Ontology assisted content creation

| Ontology enabled navigation

| Ontology integrated search


Slide 10

How about already existing CMSs?

| Content Repositories already provide certain amount of semantics for content items| Through content hierarchies, properties, taxonomies,

node/object types…| However this semantics is not “machine

understandable”: can not be reasoned on…

| There is a need for an “Integrated semantic engineering method”| Enabling CMS developers to easily utilize semantic

functionalities provided by ontologies, reasoners, without duplicating data and effort, and without a major change in their systems


Slide 11

IKS Approach for Extracting the Semantics from CMSs as Ontologies

| Nodetypes/Object types/Document Types can be automatically converted in to OWL Classes| Properties as object and Data type Properties| Restrictions when necessary| Nodes of these nodetypes can be created as

instances…| A similar approach has been provided for

Drupal System8

| How about the semantics other than node/object types?| Links between content items| Taxonomies| Content hierarchies

| IKS should provide a generic approach for a variety of different CMS Systems…

Workspace1

Nodetype

unstructured

File

Resource HotelDescription

supertypes

AsteriaTourismPortal

IbisHotel

Hilton

NovHotel

Sheroton

facility=“Pool”primaryType

sisterHotel

<HotelDescription rdf:ID=“Novotel”> <sisterHotel rdf:about=“#IbisHotel”/> <facility rdf:dataType=“&xsd:String”>Pool </quality> </HotelDescription>……

propertyDefinition

propertyDefinition

Name=“sisterHotel

requiredTypeName=“facility”

Workspace1

Nodetype

unstructured

File

Resource HotelDescription

supertypes

AsteriaTourismPortal

IbisHotel

Hilton

NovHotel

Sheroton

facility=“Pool”primaryType

sisterHotel

propertyDefinition

propertyDefinition

Name=“sisterHotel

requiredType

TourismServicesClassification

FlightBooking

Tours Hotel

4StarHotel 3StarHotel

type

<HoteDescription rdf:ID=“Novotel”> <sisterHotel rdf:about=“#IbisHotel”/> <facility rdf:dataType=“&xsd:String”>Pool </quality> </HotelDescription><4StarHotel rdf:about=“#Novotel”/>

……

<owl:Class rdf:ID=“ToursismServicesClassification”> <owl:Class rdf:ID=“Hotel> <rdfs:subClassOf rdf:resource="#TourismServicesClassification"/> </owl:Class><owl:Class rdf:ID=“4StarHotel> <rdfs:subClassOf rdf:resource=“Hotel"/> </owl:Class>

…..

Represented as Classes…

Represented as Instances…How can I know the

semantics of “type”

What if the property was “suitableFor

”And its is

bound to a classification

of people

<HoteDescription rdf:ID=“Novotel”> <sisterHotel rdf:about=“#IbisHotel”/> <facility rdf:dataType=“&xsd:String”>Pool </quality> <suitableFor rdf:about=“#YoungCouples”/> </HotelDescription><4StarHotel rdf:about=“#Novotel”/>

……

Mapping GUI

ContentRepositor

y

ContentRepositor

y

Flex RIAFlex RIA

Content Repository Model

Content Repository Model JCRJCRConcep

tBridgePropertyBridge

Subsumption

BridgeInstanceBridge

Mapping

Definition

Mapping

Definition

Mapping Engine

Mapping Engine

ContentRepositor

y

ContentRepositor

yJCRJCR

Mapping

Definition

Mapping

Definition

Mapping EngineMapping Engine

ConceptBr.Processor

PropertyBr.Processor

SubsumptonBr.

Processor


Enforced PropertyBr.Processor

InstanceBr.Processor



JCRJCR

JCR Queries

OWL Representati

on

OWL Representati

on

IKS Persistence Store


Mapping Engine

ContentRepositor

y

ContentRepositor

yJCRJCR

Mapping

Definition

Mapping

Definition

Mapping EngineMapping Engine

ConceptBr.Processor


SubsumptonBr.

Processor


Enforced PropertyBr.Processor

InstanceBr.Processor



JCRJCR



JCR Observations-Node Added-PropertyAdded

Initially Envisioned Architecture

Content Repository

JCR

CMIS Semantic Extractor /Synchronization

Persistency Store

Restf

ul A

PI

(On

tolo

gy A

dm

inis

trati

on

, Q

uery

)

LiftedOntology

Restful API + GUI

DomainOntology

HorizontalOntology

Ontology Lifting/Alignment

GUI+Engine

Harmonized

Ontology

Reason

ers

Ru

le E

ng

ines

DB

Ped

ia,

Word

Net

Example Horizontal

Application:RIA FacetedSearch GUI

Search Building Blocks

Structured Query

LuceneSAIL/LARQ

Semantic SimilarityMetrics

Hybrid Approach

JCR

CMIS CMS

Merging with External Domain Ontologies


Slide 19

-NewsSubjectCodes


-DisasterAccident


-Education


-Health

-HealthTreatment

-Illness

-EatingDisorder

-Obesity

-Medicine

-SocialIssues

-Diease

-Neurological Disease

MotorNeuroneDiseaseGeneClue

.................. ................Professor Christopher Shaw,

from the Institute of Psychiatry at Kings College

London, said……..GeneticCluesToEatingDisorder

s.................. ................

Doctors studying the causes of the eating disorders anorexia

and bulimia believe it has less to do with media images of slim-figured models and more to do

with biological and genetic factors……..

-NewsSubjectCodes


-DisasterAccident


-Education


-Health

-HealthTreatment

-Illness

-EatingDisorder

-Obesity

-Medicine

-SocialIssues

-Diease

-Neurological Disease

-MeSH

-Anatomy

-Diseases

-Organisms

-BehaviorMechanisms

-Psychiatry

-BehaviorDisciplines

-MentalDisorders

-AnxietyDisorders

-EatingDisorders

-SleepingDisorders

-SomotoformDisorders

equavilentTo

Article_ED

instanceOf

instanceOf

instanceOf

instanceOf

MeSH Biomedical Ontology

Exploiting DBPedia relationships


Slide 20

MerkelOffersStateAidForOpel

......... German Chancellor has given assurances that

any investor in General Motors (GM) subsidiary

Opel will have state support ……

UKsaysMerkelbacksFiscalBoost

......... And he added that German Chancellor was "fully engaged" with the

European economic debate……

Iptc:Politics

Iptc:Economy

Tagged By

Tagged By

dbp:Chancellorof_German

y

dbp:Chancellorof_German

y

Tagged By

Tagged ByGermanyAgreesBadBankSc

heme......... Reports have said that Angela Merkel's government wants to see this achieved before the summer recess starts in

early July ……

dbp:Angela_Merkel

Tagged By

Returned by Solr

dbprop:order

Future Plans

| Current System is for JCR enabled content repositories| Once configured, the metadata extraction is

automatically, continuously kept synchronized with knowledge base

| Based on observation mechanism| It can easily be extended for CMIS enabled content

repositories

| Future Plans| Propose RESTfull interfaces

| To present a dump of data and metadata to knowledge base

| To inform updates, additions, deletions of data and metadata...


Slide 21

Thank you, Questions…Contact Information:Gokce B. Laleci, [email protected]

Viewlets of Demonstration:http://www.srdc.com.tr/iks/screencast/

http://www.srdc.com.tr/iks/screencast/search-faceted.htm

http://www.srdc.com.tr/iks/screencast/search-faceted.htm

References..

1. Ian Horrocks, Ontology Reasoning: the Why and the How2. Y. Jin, S. Decker, G. Wiederhold. OntoWebber: Model-Driven

Ontology-Based Web Site Management3. S. Staab, J. Angele, S. Decker, M. Erdmann, A. Hotho, A. Maedche,

H. P. Schnurr, R. Studer, Y. Sure. Semantic community Web portals.

4. Max Völkel, Markus Krötzsch, Denny Vrandecic, Heiko Haller, Rudi Studer, Semantic Wikipedia

5. Sebastian Schaffert, IkeWiki: A SemanticWiki for Collaborative Knowledge Management

6. DUC MINH LE, LAU Lydia, An Open Architecture for Ontology-Enabled Content Management Systems : A Case Study in Managing Learning Objects

7. Roberto García, Juan Manuel Gimeno, Ferran Perdrix, Rosa Gil, and Marta Oliva, The Rhizomer Semantic Content Management System

8. Stephane Corlosquet, Renaud Delbru, Tim Clark, Axel Polleres, and Stefan Decker, Produce and Consume Linked Data with Drupal


Slide 23

08.04.23 24

The IKS Consortium

Project Lead and CoordinationSalzburg Research

Wernher BehrendtSalzburg Research Forschungsgesellschaft m.b.H.Jakob Haringer Straße 5/3 | 5020 Salzburg, AustriaT +43.662.2288-409 | F +43.662.2288-222wernher.behrendt@salzburgresearch.atwww.salzburgresearch.at

Deutsches Forschungsinstitut für Künstliche Intelligenz (DFKI)

Universität St. Gallen

Consiglio Nationale delle Ricerche (CNR)

Software Quality LabUnversität Paderborn

Software Research and Development Consultancy Ltd (SRDC)

Hochschule Furtwangen

Nuxeo Sa. Alkacon Software GmbH

TXT Polymedia Pisano Holding GmbH

Nemein Oy Day Software AG

http://www.salzburgresearch.at/

Content Repositories vs Knowledge Bases

Technology

idnovotel

processor

content management

content repository

processor

content repositories

nodeobject

processor