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OpenCms Days 2012 - Keynote: Semantic Technologies for CMS
 

OpenCms Days 2012 - Keynote: Semantic Technologies for CMS

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In this session, Tilman will present the impact of Semantic Technologies for CMS systems. After a brief overview over the current state of affairs for Semantic Technologies, he will drill down by ...

In this session, Tilman will present the impact of Semantic Technologies for CMS systems. After a brief overview over the current state of affairs for Semantic Technologies, he will drill down by presenting some of the recent results of the EU-funded project IKS (Interactive Knowledge Stack). In IKS, DFKI, Alkacon and 12 further partners strive to bring interaction to the knowledge contained in CMS systems by providing a technology stack that can be used by all CMS systems. The main results of IKS are two software packages: Apache Stanbol (see http://projects.apache.org/projects/stanbol.html) is a modular software stack and reusable set of components for semantic content management, focusing on storage and retrieval. VIE.js (see http://viejs.org/) is a JavaScript library for implementing decoupled Content Management Systems and semantic interaction in web applications, thus focusing on the front end.

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    OpenCms Days 2012 - Keynote: Semantic Technologies for CMS OpenCms Days 2012 - Keynote: Semantic Technologies for CMS Presentation Transcript

    • Semantic Technologies for CMSSemantic CMS Community Dr. Tilman Becker DFKI GmbH, Saarbrücken, Germany OpenCMS Days, Cologne September 25, 2012 Co-funded by the 1 Copyright Tilman Becker, DFKI European Union
    • Page: 2 Web evolution  3.0   WebWeb  4.0  Web  1 .0   Web  2.0   Slide by Nova Spivack, Radar Networks www.iks-project.eu Copyright IKS Consortium
    • Page: 3What is the problem? www.iks-project.eu Tilman Becker, DFKI
    • Page: 4 The Semantic Web  Thevision of the Semantic Web has been originally proposed by Tim Berners-Lee  “TheSemantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation.” [The Semantic Web, 2001]  Standardized specification techniques for the semantic annotation of content (RDF, OWL, ...) www.iks-project.eu Copyright IKS Consortium
    • Page: 5 Semantic Web Stack  W3C provides standardized specifications for Semantic Web technologies  Semantic Web Layer Cake as a conceptual architecture describes an hierarchy of languages  Each layer exploits and uses capabilities of the layers below Semantic Web Layer Cake, Image source: http://www.w3.org/2007/03/layerCake.svg www.iks-project.eu Copyright IKS Consortium
    • Page: 6 A Few Semantic Web Concepts  Identification: URI  Statements: RDF  Queries: SPARQL  Storage: Triple Stores  Ontologies: OWL  Is there anybody out there: Linked Open Data  Semantic Lifting www.iks-project.eu Copyright IKS Consortium
    • Page: 7 Unique Identification of Resources  “...more fundamental than either HTTP or HTML are URIs, which are simple text strings that refer to Internet resources -- documents, resources, people, and indirectly to anything. URIs are the glue that binds the Web together.”  In a “Web of Data” the unique identification of entities is required www.iks-project.eu Copyright IKS Consortium
    • Page: 8 How to identify resources?  URI – Uniform Resource Identifier [RFC 3986]   “A Uniform Resource Identifier (URI) is a compact sequence of characters that identifies an abstract or physical resource.”   A URI consists of five parts: scheme, authority, path, query and fragment   URI = scheme ":" authority "/" path [ "?" query ] [ "#" fragment ]  Example: http://user@example.com:8042/over/there?name=ferret#nose scheme authority path query fragment www.iks-project.eu Copyright IKS Consortium
    • Page: 9 What do we need?  We want to express the statement:   “The brand of the car is Jaguar.”  We need ...   ...a way to address the concrete resource car.   ... to express the property brand of the resource car.   ... to define the property value Jaguar for the property brand. www.iks-project.eu Copyright IKS Consortium
    • Page: 10 Resource Description Framework (RDF)  “TheResource Description Framework (RDF) identifies things using Web identifiers (URIs), and describes resources with properties and property values.”  A Resource is an object that can be identified by an URI, e.g. “http://example.org/Car”.  A Property describes an aspect of a resource, e.g. “http://example.org/Brand”. The property is also identified by an URI.  TheProperty value assigns a concrete value to a property, e.g. “Jaguar” or ““http://example.org/Jaguar”. www.iks-project.eu http://www.w3schools.com/rdf/ Copyright IKS Consortium
    • Page: 11 RDF Statements  RDF statements consist of subject (resource), predicate (property) and object (property value) Predicate Object Subject (URI) Predicate Object (literal)  Subjects (except Blank Nodes) and Predicates are always defined by URIs  Objects can be defined by URIs and literals www.iks-project.eu Copyright IKS Consortium
    • Page: 12 RDF Statements - Example  Exemplary statements:   “The brand of the car is Jaguar.”   “The model of the car is XF.”Subject Predicate Object http://example.org/rel/Brand http://example.org/Car http://example.org/Jaguar http://example.org/rel/Model XF PredicateObject www.iks-project.eu Copyright IKS Consortium
    • Page: 13 Resource Description Framework (RDF)   “The Resource Description Framework (RDF) is a language for representing information about resources...” [RDF Primer]•  W3C Standard (http://www.w3.org/RDF)   RDF provides a graph-based data model   for representing metadata   for describing the semantics of information in a machine-accessible way www.iks-project.eu Copyright IKS Consortium
    • Page: 14 RDF Serialization Formats  RDF/XML  N3  N-Triples  TRiG  TRiX  Turtle  JSON  JSON-LD  RDFa www.iks-project.eu Copyright IKS Consortium
    • Page: 15 Semantic Layer Web Cake A model for describingresources with properties A format for specifying structured and property values. data in a machine-readable form Unique identification of resources Semantic Web Layer Cake, Image source: http://www.w3.org/2007/03/layerCake.svg www.iks-project.eu Copyright IKS Consortium
    • Page: 16 RDF Queries  RDFprovides a model for describing resources with properties and property values. @prefix  ex:  <http://www.example.org/>.     ex:Car1    ex:Brand    ex:Jaguar   ex:Car1    ex:Colour  “Black”   t all ex:Car2    ex:Brand    ex:Jaguar   I ge ? ex:Car2    ex:Colour  “White”   do ex:Car3    ex:Brand    ex:VW   How Jaguars ex:Car3    ex:Colour  “Black”   b lack www.iks-project.eu Copyright IKS Consortium
    • Page: 17 SPARQL  SPARQL Protocol and RDF Query Language  W3C Recommendation since 2008  SPARQL provides a standard for querying information, that is specified in RDF  SPARQL consists of three specifications   Query language   Query results XML format   Data access protocol www.iks-project.eu Copyright IKS Consortium
    • Page: 18 Exemplary SPARQL Query“Return the models and prices for all cars of brand‘Jaguar’ ” Declares namespaces for abbreviated resourcesSPARQL Query: identifiers. PREFIX  ex:    <http://example.org/>     Identifies the variables to SELECT  ?model  ?price   WHERE     appear in the query    {  ?car  ex:Brand    ex:Jaguar  .   results.        ?car  ex:Model  ?model  .          ?car  ex:Price  ?price  .    }     Provides the basic graph pattern to match againstExemplary Result: the data graph. Model Price “XJ” “79.750,00” “XF” “44.900,00” www.iks-project.eu Copyright IKS Consortium
    • Page: 19 Triple Stores  Can be categorized into 3 category:   In memory triple stores   Used for certain operations like benchmarking, caching, etc   Native triple stores   Provides their own implementations (Virtuoso, Mulgara, AllegroGraph, …)   Non memory non native triple stores   Are built on third party databases (Jena SDB, Kaon, …) www.iks-project.eu Copyright IKS Consortium
    • Page: 20Functionalities provided byTriple Stores  RDBMS-support  General RDF model access  Query language support in the store such as RQL, SPARQL  Some stores provide:   Provenance - tracking of who-said-what   APIs for accessing triple store over network  Very few stores provide:   Full text search   Inference and rule languages www.iks-project.eu Copyright IKS Consortium
    • Page: 21 Example Triple Store implementations  RDF Suite   Sofia Alexaki, Vassilis Christophides, Gregory Karvounarakis, Dimitris Plexousakis, Karsten Tolle. The ICS-FORTH RDFSuite: Managing Voluminous RDF Description Bases , SemWeb, 2001   Based on an ORDBMS model  Sesame   http://www.openrdf.org/   Relational databases (mysql, postgres, oracle)  Jena   http://www.hpl.hp.com/semweb/jena2.htm   Relational databases (mysql , postgres, oracle)  Virtuoso   http://virtuoso.openlinksw.com/   Native RDF Quad Storage (Physical Quads) www.iks-project.eu Copyright IKS Consortium
    • Page: 22 Computational ontologies  Ontologies are (software) components, expressed and managed in standard W3C languages like RDF, OWL, RIF, SPARQL  Computational Ontologies are artifacts   Have a structure (linguistic, logical, etc.)   Their function is to “encode” a description of the world (actual, possible, counterfactual, impossible, desired, etc.) for some purpose www.iks-project.eu
    • Page: 23Searching for ontologies onthe Semantic Web www.iks-project.eu
    • Page: 24From the lessons learnt ...  Smallontologies with explicit documentation of design rationales   components supported by specific functionalities   selection, matching, composition, etc.   implemented in repositories, registries, catalogues, open discussion and evaluation forums, and in new- generation ontology design tools   ontologydesignpattern.org   ODP and Watson APIs   NeOn ODP Plugin   etc. www.iks-project.eu
    • Page: 25Ontology Design PatternsAn ontology designpattern is a reusablesuccessful solution to arecurrent modelingproblem www.iks-project.eu
    • Page: Align CMS Representation With External Ontology -NewsSubjectCodes -MeSH -ArtsCultureEntertainment -Anatomy -DisasterAccident -Diseases -EconomyBusinessFinance -Organisms -Education -Psychiatry -EnvironmentalIssues -BehaviorMechanisms -Health MeshRepresentation of -BehaviorDisciplines -Disease BiomedicNew Subject Codes as -MentalDisorders alhierarchical ontology -HealthTreatmentclasses -AnxietyDisorders Ontology -Illness -EatingDisorders -EatingDisorder -SleepingDisorders equivalentTo -Obesity -SomotoformDisorders -Medicine -SocialIssues www.iks-project.eu
    • Page: 27 Why is RDFS not enough?  RDFS cannot express negations  Defined property restrictions are global  Missing cardinalities for properties  Relations between (sub-)classes (e.g. disjunction) www.iks-project.eu Copyright IKS Consortium
    • Page: 28 OWL – Web Ontology Language  “TheOWL Web Ontology Language is designed for use by applications that need to process the content of information instead of just presenting information to humans.”  OWL has been developed as a vocabulary extension of RDF  Explicitly represents the meaning of terms in vocabularies and the relationships between those terms. (Ontology) http://www.w3.org/TR/2004/REC-owl-features-20040210/ www.iks-project.eu Copyright IKS Consortium
    • Page: 29 OWL – The Story  2004 - OWL W3C Recommendation  2009 - OWL 2 W3C RecommendationOWL = Web Ontology Language  Why not WOL?   Obvious pronunciation which is easy on the ear http://piqs.de   Opens up great opportunities for logos   Owls are associated with wisdom   It has an interesting back story http://lists.w3.org/Archives/Public/www-webont-wg/2001Dec/0169.html www.iks-project.eu Copyright IKS Consortium
    • Page: 30 schema.org  “simple” ontology  Designed for web search   Contains movies and records, but not plants and animals  Supported by   Google   Bing   Yahoo! www.iks-project.eu Copyright IKS Consortium
    • Page: 31 Back to the Cake ... Highly expressive ontology language for modelling complexA language for querying knowledge domains.information specified in RDF. A language for describing a lightweight ontology. A model for describingresources with properties A format for specifying structured and property values. data in a machine-readable form Unique identification of resources Semantic Web Layer Cake, Image source: http://www.w3.org/2007/03/layerCake.svg www.iks-project.eu Copyright IKS Consortium
    • Page: 32 Linking Open Data Project  Isan W3C SWEO Project  Aims to make data freely to everyone  Aims to publish open data sets as RDF and set semantic relationships between them   Serves information in a machine readable format   Enriches content   Reduces duplication  Linked datasets increasing rapidly   A large number of datasets are linked already www.iks-project.eu Copyright IKS Consortium
    • Page: 33Linked Datasets As of October2008 www.iks-project.eu Copyright IKS Consortium
    • Page: 34Linked Datasets As of September2010 www.iks-project.eu Copyright IKS Consortium
    • Page: 352011 www.iks-project.eu Copyright IKS Consortium
    • Page: 36 Access Data In The Cloud  Follow the RDF links representing the “things”  SPARQL Endpoints  Ready to use software to discover linked data (See the next slide) www.iks-project.eu Copyright IKS Consortium
    • Page: 37 Linked Data Applications  Lots of application on top of the linked data   Tabulator   Marbles   Openlink RDF Browser   …  Just google   RDF Crawlers   RDF Browsers  Alsosee the following link containing a number of linked data applications:   http://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/ LinkingOpenData/Applications www.iks-project.eu Copyright IKS Consortium
    • Page: What is “Semantic Lifting”?  Semantic Lifting refers to the process of associating content items with suitable semantic objects as metadata to turn “unstructured” content items into semantic knowledge resources  Semantic Lifting makes explicit “hidden” metadata in content items www.iks-project.eu Copyright IKS Consortium 38
    • Page: Metadata: Variants  Metadata exist in many forms:   Free text descriptions   Descriptive content related keywords or tags from fixed vocabularies or in free form   Taxonomic and classificatory labels   Media specific metadata, such a mime-types, encoding, language, bit rate   Media-type specific structured metadata schemes such as EXIF for photos, IPTC tags for images, ID3-tags for MP3, MPEG-7 for videos, etc.   Content related structured knowledge markup, e.g. to specify what objects are shown in an image or mentioned in a text, what the actors are doing, etc. www.iks-project.eu Copyright IKS Consortium 39
    • Page: Publishing Web Content with semantic metadata  Augmenting web content with structured information becomes increasingly important  Several methods have emerged in recent years to include structured metadata in Web pages   Microformats   RDFa   Microdata (HTML5)  Supported by the major search engines to improve search and result presentation, e.g. Google („Rich Snippets), Bing, Yahoo www.iks-project.eu Copyright IKS Consortium 40
    • Page: Augmenting Web Content  The HTML code contains a review of a restaurant in plain text using only line breaks for structuring  Without specialized information extraction analysis tools it cannot be interpreted, e.g. that it is a review (of what and when?), who the reviewer was, etc.<div>L’Amourita PizzaReviewed by Ulysses Grant on Jan 6.Delicious, tasty pizza on Eastlake!LAmourita serves up traditional wood-fired Neapolitan-style pizza,brought to your table promptly and without fuss. An ideal neighborhoodpizza joint.Rating: 4.5</div> www.iks-project.eu Copyright IKS Consortium 41
    • Page: Microformats  Same text but additional span elements with class attributes to encode the type of contained information (hReview) and the properties of that type<div class="hreview"> <span class="item"> <span class="fn">L’Amourita Pizza</span> </span> Reviewed by <span class="reviewer">Ulysses Grant</span> on <span class="dtreviewed"> Jan 6<span class="value-title" title="2009-01-06"></span> </span>. <span class="summary">Delicious, tasty pizza on Eastlake!</span> <span class="description">LAmourita serves up traditional wood-fired Neapolitan-style pizza, brought to your table promptly and without fuss. An ideal neighborhood pizza joint.</span> Rating: <span class="rating">4.5</span></div> www.iks-project.eu Copyright IKS Consortium 42
    • Page: RDFa  Same text but additional attributes and span elements encoding a RDF structure:   namespace declaration of the used ontology   RDF class encoded by typeof attribute and its properties by a property attribute<div xmlns:v="http://rdf.data-vocabulary.org/#" typeof="v:Review"> <span property="v:itemreviewed">L’Amourita Pizza</span> Reviewed by <span property="v:reviewer">Ulysses Grant</span> on <span property="v:dtreviewed" content="2009-01-06">Jan 6</span>. <span property="v:summary">Delicious, tasty pizza on Eastlake!</span> <span property="v:description">LAmourita serves up traditional wood-fired Neapolitan-style pizza, brought to your table promptly and without fuss. An ideal neighborhood pizza joint.</span> Rating: <span property="v:rating">4.5</span></div> www.iks-project.eu Copyright IKS Consortium 43
    • Page: Microdata (HTML5)  Same text but additional attributes and span elements:   A class declaration as value of an itemtype attribute and its properties as values of an itemprop attribute<div> <div itemscope itemtype="http://data-vocabulary.org/Review"> <span itemprop="itemreviewed">L’Amourita Pizza</span> Reviewed by <span itemprop="reviewer">Ulysses Grant</span> on <time itemprop="dtreviewed" datetime="2009-01-06">Jan 6</time>. <span itemprop="summary">Delicious, tasty pizza in Eastlake!</span> <span itemprop="description">LAmourita serves up traditional wood-firedNeapolitan-style pizza, brought to your table promptly and without fuss. An ideal neighborhood pizzajoint.</span> Rating: <span itemprop="rating">4.5</span> </div></div> www.iks-project.eu Copyright IKS Consortium 44
    • Page: Named Entities  Statistical Approaches: examples   Lingpipe: Hidden Markov Models   OpenNLP: Maximum Entropy Models   Stanford NER: Conditional Random Fields  Statistical models crated by supervised learning techniques   Large annotated corpora required  Customization diffcult except by re-annotation/re-training  Not suitable for any type of named entity www.iks-project.eu Copyright IKS Consortium 45
    • Page:NER Markup for a Web Page www.iks-project.eu Copyright IKS Consortium 46
    • Page: IE TemplateA Person Template (asTyped Featured Structure)instantiated from text.The template supports theextraction of variousproperties of a person. www.iks-project.eu Copyright IKS Consortium 47
    • Page: Clustering  Detection of classes in a data set  Partitioning data into classes in an unsupervised way with high intra-class similarity low inter-class similarity  Main variants:   Hierarchical clustering   Agglomerative   Partitioning clustering   K-Means www.iks-project.eu Copyright IKS Consortium 48
    • Page: NER Evaluation  Nobel Prize Corpus from NYT, BBC, CNN  538 documents (Ø 735 words/document)   28948 person, 16948 organization occurrences Sprout Calais Stanford OpenNLP NER Precision 77,26 94,22 73,21 57,69 Recall 65,85 86,66 73,62 42,86 F1 71,10 90,28 73,41 49,18 www.iks-project.eu Copyright IKS Consortium 49
    • Page: 50 A Few Semantic Web Concepts  Identification: URI  Statements: RDF  Queries: SPARQL  Storage: Triple Stores  Ontologies: OWL  Is there anybody out there: Linked Open Data  Semantic Lifting www.iks-project.eu Copyright IKS Consortium
    • Page: Bringing it all together  Exporting data (more datasets)   Grab information from your content (i.e., recognize the „entities“)  Merging your data   Merge it from different data  Conbine with different datasets/content   Use data to interact with (e.g., configure) web services  Publishing Semantics/Content/interaction   Enrich your content with dinamically generated, interactive information www.iks-project.eu Copyright IKS Consortium 51
    • Page: Bringing it all together  Exporting data (more datasets)   Grab information from your content (i.e., recognize the „entities“)  Merging your data   Merge it from different data  Conbine with different datasets/content   Use data to interact with (e.g., configure) web services  Publishing Semantics/Content/interaction   Enrich your content with dinamically generated, interactive information www.iks-project.eu Copyright IKS Consortium 52
    • Page: Bringing it all together  Exporting data (more datasets)   Grab information from your content (i.e., recognize the „entities“)  Merging your data   Merge it from different data  Conbine with different datasets/content   Use data to interact with (e.g., configure) web services  Publishing Semantics/Content/interaction   Enrich your content with dinamically generated, interactive information www.iks-project.eu Copyright IKS Consortium 53
    • Page: Bringing it all together  Exporting data (more datasets)   Grab information from your content (i.e., recognize the „entities“)  Merging your data   Merge it from different data  Conbine with different datasets/content   Use data to interact with (e.g., configure) web services  Publishing Semantics/Content/interaction   Enrich your content with dinamically generated, interactive information www.iks-project.eu Copyright IKS Consortium 54
    • Page: 2 Page: 55 IKS Goal A Reference Architecture for Semantically Enabled Content Management Systems Copyright IKS Consortiumwww.iks-project.eu Copyright IKS Consortium
    • Page: 56Whatis a a Semantic CMS? is Semantic CMS? Page: 4What Traditional CMS vs. Semantic CMS Atomic unit: Document  Atomicunit: Entity Properties as meta-data  Semantic meta-data  e.g. author  Defined entity types  tags, keywords  Linked entities Keyword search for  Semantic search for  strings in docs  entities and their relations Document Management  Knowledge Management  Document types  Entity management  Document workflow  Ontologies www.iks-project.eu Copyright IKS Consortium www.iks-project.eu Copyright IKS Consortium
    • Page: 57 Building Semantic CMS  Ask the experts:  Top 8 CMS Customer Needs   Thefollowing list features the top 8 CMS capabilities that are perceived as highly relevant by CMS customers. The ranking is based on in-depth interviews with 12 IT executives of CMS customer organizations in Europe. www.iks-project.eu Copyright IKS Consortium
    • Page: 58 Top 8 Customer Needs  Interoperability  Support for Content Creation  Workflow management  Multi-Channel Access to Content  Personalization  Enrichment of Content  Intuitive User Interface  Enhanced Search Functionality www.iks-project.eu Copyright IKS Consortium
    • Page: 59Ask the experts Book title: Semantic Technologies in Content Management Systems - Applications, Trends and Evaluations Editors: Wolfgang Maass, Saarland University, Germany; Tobias Kowatsch, University of St. Gallen, Switzerland Publisher: Springer, Heidelberg, Germany ISBN: 978-3642215490 (1st Edition. 213 p. 56 illus. Hard cover) Year: January 31, 2012 www.iks-project.eu Copyright IKS Consortium
    • Page: 60 IKS guidelines  Do not change existing CMS!  Provide as much abstraction as possible! www.iks-project.eu Copyright IKS Consortium
    • Page: 61Traditional CMS Architecture www.iks-project.eu Copyright IKS Consortium
    • Page: 62Semantic CMS Architecture www.iks-project.eu Copyright IKS Consortium
    • Page: 63 Implementation of the Reference Architecture  Referenceimplementation within the IKS project   IKS: An open source community to bring semantic technologies to CMS platforms   New incubating project at the Apache Software Foundation http://incubator.apache.org/stanbol www.iks-project.eu Copyright IKS Consortium
    • Page: 64Do Not Replace – but Extend Not Replace – but Extend Page: 5Do No need to replace your existing technology. IKS components offer service oriented integration. Extend by Using Semantic Services Traditional CMS IKS Technology Stack Database www.iks-project.eu Copyright IKS Consortium www.iks-project.eu Copyright IKS Consortium
    • Page: 65Use on the Concepts of the Web the Concepts of the Web Page: 6Rely Integration through a RESTful web service API Resources are identified by their URI HTTP Request Traditional CMS IKS HTTP Technology Response Stack Database www.iks-project.eu Copyright IKS Consortium www.iks-project.eu Copyright IKS Consortium
    • IKS Page: 66 9 Reference ImplementationIKS Semantic User IKS VIE7.0 Widgets Interface Content Knowledge Semantic User Interaction IKS VIE Knowledge Access Knowledge Extraction Pipelines Knowledge Administration Stanbol Apache Enhancement Stanbol Engine Enhancer Apache Stanbol RESTful API Reasoning Apache Stanbol Reasoners Apache Stanbol Rules Console OSGI Knowledge Models Apache Apache Stanbol Clerezza Ontology Manager Content Apache Stanbol Knowledge Repository Repository CMS Adapter RDF CMIS / Apache JCR Stanbol ContentHub Apache Stanbol EntityHub Apache Stanbol FactStore www.iks-project.eu Copyright IKS Consortium
    • Page: 67 Page: 10VIE Quick FactsVIE Quick Facts VIE is a utility library for semantic maintenance in JavaScript Offers semantic web developers a DSL to ease recurring tasks  Easy access to embedded semantic annotations in HTML (RDFa)  Easy loading of properties for entities from external services  Easy saving of knowledge about entities  Easy querying of semantic services VIE Widgets are web user interface components based on VIE. www.iks-project.eu Copyright IKS Consortium Copyright IKS Consortium www.iks-project.eu
    • Page: 68 11Apache Stanbol Quick Facts Modular (OSGi) components implemented in JavaSemantic Lifting Enhance content Link to Linked Open Data (LOD) sources Store and index enhanced content for searchKnowledge Representation & Reasoning Manage ontologies Apply rules to ontologies Reasoning over managed ontologies www.iks-project.eu Copyright IKS Consortium
    • Page: 69 12Service-Oriented View VIE - User Interface Layer VIE VIE Widgets Apache Stanbol Service Layer Apache Apache Apache Apache Stanbol Stanbol Stanbol Stanbol Enhancer EntityHub Ontology Manager Reasoners Apache Apache Apache Stanbol Stanbol Stanbol Rules ContentHub FactStore StanbolEnhancement Engines Apache Stanbol Apache Stanbol CMS Adapter Component Layer Semantic Lifting www.iks-project.eu KnowledgeCopyright IKS Consortium Representation & Reasoning
    • Page: 70 14Enhancer & EnginesFeatures Semantic lifting by automatically extracting entities from textual content Different enhancement engines for specific tasks Engines are arranged in customizable enhancement chains where one engine may rely on the output of another engine Examples  Language Identification Engine  Named Entity Extraction Engine  Geonames Engine to annotate places with additional information from geonames.org www.iks-project.eu Copyright IKS Consortium
    • Page: 71 16EntityhubFeatures Manage a network of remote sites for fast entity lookup Caching of externally retrieved entity information CRUD management of local entities Examples  Use DBPedia linked open data source to retrieve additional information for entities  Use a customized vocabulary for local entities www.iks-project.eu Copyright IKS Consortium
    • Page: 72 18ContenthubFeatures Document repository by indexing retrieved documents Supports indexing of additional semantic metadata provided along the content Search facilities  Keyword Search  Faceted Search based on available semantic metadata www.iks-project.eu Copyright IKS Consortium
    • Page: 73 20CMS AdapterFeatures Bootstrapping component to import content from a CMS into Apache Stanbol Import content from a CMIS/JCR compliant CMS into the Apache Stanbol Contenthub www.iks-project.eu Copyright IKS Consortium
    • Page: 74 29VIE & VIE Widgets VIE - User Interface Layer VIE VIE Widgets Apache Stanbol Service Layer Apache Apache Apache Apache Stanbol Stanbol Stanbol Stanbol Enhancer EntityHub Ontology Manager Reasoners Apache Apache Apache Stanbol Stanbol Stanbol Rules ContentHub FactStore StanbolEnhancement Engines Apache Stanbol Apache Stanbol CMS Adapter Component Layer Semantic Lifting www.iks-project.eu KnowledgeCopyright IKS Consortium Representation & Reasoning
    • Page: 75 30VIE & VIE WidgetsFeatures VIE is a JavaScript library for implementing decoupled CMS and semantic interaction in web applications VIE provides easy access to the semantic metadata (RDFa) within a web page VIE Widgets are user interface components that implement semantic user interactions Examples  Semantic image search  Automatic tagging of entities  Semi-automatic content annotation www.iks-project.eu Copyright IKS Consortium
    • Page:VIE: Core Javascript is a framework/library www.iks-project.eu
    • Page: abstractionVIE: Core of semantic entities and their relations Javascript is a framework/library www.iks-project.eu
    • Page: abstractionVIE: Core of semantic entities and their relations using Javascript is a framework/library www.iks-project.eu
    • Page: abstractionVIE: Core of semantic entities and their relations using Javascript is a framework/library addr essin g Web Developers   bringing semantics into webpage   without caring too much about triples/triplestores and so on www.iks-project.eu
    • Page: VIE: Core  VIE offers an API to: -   create entities with properties   link entities   serialize entities (either into the HTML using RDFa or to a server)   access semantic lifting services (e.g., Zemanta, OpenCalais, Apache Stanbol, …)   query databases to fill  The default "ontology" that VIE is delivered with, is http://schema.org, which can be easily switched or extended. www.iks-project.eu
    • Page: VIE: UI WidgetsOn top of VIE we gathered a bunchof UI widgets in a library that help tosimplifying embedding VIEs powerinto a webpage more directly. UI Widgets www.iks-project.eu Copyright IKS Consortium 81
    • Page:VIE Widgets Widgets Widgets   VIE-Widgets are a sort of jQuery UI Widgets in order to:   achive maximum portability   accelerating lerning curve www.iks-project.eu Copyright IKS Consortium 82
    • Page:It‘s about abstraction VIE - UI Widgets „VIE-W“ VIE VIE-2 „Edit your content w. Semantics“ „Edit your Semantics“ (Semantic) Services (e.g., Stanbol Enhancer, - EntityHub, Zemanta, ...) (Semantic) Databases (e.g., DBPedia, Geonames, ...) www.iks-project.eu Copyright IKS Consortium 83
    • Page: Analyze with Apache Stanbolvar elem = $(<p>This is a small test, where Steve Jobs sings a song.</p>);v.analyze({element: elem}).using(stanbol).execute().done(function(entities) { alert ("found: " + entities.length + " entities!"}).fail(function(f) { alert("something went wrong") }); www.iks-project.eu
    • Page: Interaction Patterns: IPAn IP consists of four parts:   the problem   thepattern (i.e., the solution of the problem)   use cases for the pattern   how the pattern applies for the use cases www.iks-project.eu
    • Page: 86An Experiment within IKS:Ambient Interaction Beyond Classical CMSIts Thursday morning. I get site-specific weather information when I ambrushing my teeth in the bathroom. Based on weather information and mycalendar, free-time event suggestions are given, e.g. "Today, 8 p.m. - MissMarple Night at CinemaOne. Do you want to order tickets?” Copyright by Duravit www.iks-project.eu Copyright IKS Consortium
    • Page: 87 Most of IKS Semantic CMS is used in the AmI Case System AmI Case SystemLogical ArchitectureIKS Semantic CMS Architecture The blue marked modules indicate modules that exist in both architectures www.iks-project.eu Copyright IKS Consortium
    • Page: 88 Page: 31License IKS Licenses: IKS software is licensed under business-friendly open source software licenses. IKS software can be freely used / changed / distributed in your products. For the rare cases where artifacts use a less permissive license, you will find a notice.  e.g. we use models for natural language processing from the Apache OpenNLP project whose licenses are not clarified, yet. www.iks-project.eu Copyright IKS Consortium www.iks-project.eu Copyright IKS Consortium
    • Page: 89 32Get in Contact VIE  Homepage http://viejs.org  Google User Group https://groups.google.com/forum/#!forum/viejs Apache Stanbol  Homepage http://incubator.apache.org/stanbol  Mailinglist subscription stanbol-dev-subscribe@incubator.apache.org www.iks-project.eu Copyright IKS Consortium
    • Page: 90 Thank you for your attention !Acknowledgement:to all participants of IKS,especially the provider of in-depth tutorials. www.iks-project.eu Copyright IKS Consortium
    • Semantic Technologies for CMSSemantic CMS Community Dr. Tilman Becker DFKI GmbH, Saarbrücken, Germany OpenCMS Days, Cologne September 25, 2012 Co-funded by the 91 Copyright Tilman Becker, DFKI European Union