Creating Knowledge From Interlinked Data From Big Data to Smart Data
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1 Creating Knowledge From Interlinked Data From Big Data to Smart Data Prof. Dr. Sören Auer Fraunhofer-Institut für Intelligente 1
2 The Web evolves into a Web of Data Linked Open Data Facebook Open Graph Fraunhofer-Institut für Intelligente 2
3 Die Evolution des Web & Intranets Web 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 Intranet 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 Fraunhofer-Institut für Intelligente 3
4 Towards Information Oriented Architectures IBM DeveloperWorks: The role of semantic models in smarter industrial operations Fraunhofer-Institut für Intelligente 4
5 Linked Data Principles 1. Use URIs to identify the things in your data 2. Use URIs so people (and machines) can look them up on the web 3. When a URI is looked up, return a description of the thing (in RDF format) 4. Include links to related things Fraunhofer-Institut für Intelligente 5
6 Linked Data in a Nutshell 1. Uses RDF Data Model organizes NAF LAC Subject Predicate Object starts takesplacein Nieuwegein 2. Is serialised in triples: NAF organizes LAC. LAC starts ^^xsd:date. LAC takesplaceat dbpedia:nieuwegein. 3. Publish in the Intranet (or on the Web) Fraunhofer-Institut für Intelligente
7 Encode Relational Data in RDF Primary keys become subjects Columns become properties Cells become objects Mapping Standard: W3C R2RML Relational to RDF Mapping Language Many mature implementations: SparqlMap, Sparqlify, OnTop Fraunhofer-Institut für Intelligente
8 Encode Taxonomic Data in RDF Vehicle Car Truck Hatchback Cabrio Sedan Light Rigid Heavy Rigid Combination Hot Hatch Vehicle a rdfs:class Car rdfs:subclassof Vehicle Truck rdfs:subclassof Vehicle Cabrio rdfs:subclassof Car. Fraunhofer-Institut für Intelligente 8
9 RDF is the Lingua Franca of Data Integration RDF is simple We can easily encode and combine all kinds of data models (relational, taxonomic, graphs, object-oriented, ) RDF supports distributed data and schema We can seamlessly 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 many perspectives : facts, graphs, ER, logical axioms, graphs, objects RDF integrates well with other formalisms - 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 Fraunhofer-Institut für Intelligente 9
10 The emerging Web of Data Fraunhofer-Institut für Intelligente Linking Open Data cloud diagram,analyseby und Informationssysteme IAIS Richard Cyganiak and Anja Jentzsch.
11 Distributed Social Semantic Networking Fraunhofer-Institut für Intelligente
12 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 Fraunhofer-Institut für Intelligente 12
13 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 Fraunhofer-Institut für Intelligente 13
14 From Intranet to Enterprise Data Web around a knowledge hub Auer, Frischmuth, Klímek, Unbehauen, Holzweißig, Marquardt: Linked Data in Enterprise Inform ation Integration S ubm itted to S em antic Web Journal Fraunhofer-Institut für Intelligente
15 Creating Knowl edg e out of Interlinked Data Facilitates data integration along value-chains within and across enterprises When just data shall be exchanged and integrated SOA is quite expensive PricewaterhouseCoopers, Technology Forecast, 2009
16 Creating Knowl edg 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 Human-resources Requirements engineering Supply-chains Support the long tail of enterprise information domains
17 Towards Data Value Chains Data Value Chains today Extraction, Curation, Quality, Linking, Integration, Publication, Visualization, Analysis Increased Specialization Separation of concerns More interdisciplinarity Data Value Chains tomorrow Extraction, Curation Quality, Linking, Integration Publication, Visualization, Analysis Extraction Curation Quality Linking Integration Publication Visualization Analysis
18 Interlinking/ Fus ing Manual revision/ authoring Classification/ Enrichm ent Storage/ Query ing Linked Data Lifecycle Quality Analysis Ex traction Evolution / Repair Fraunhofer-Institut für Intelligente Search/ Browsing/ Ex ploration
19 Creating Knowledge out of Interlinked Data LOD2 Stack Components Limes Silk Silk-latc RDFAuthor OntoWiki Interlinking/ Fusing Sieve Sparqlify LOD2 Authentication Component SIREn CKAN (source) Dbpedia (source) sparqlproxy SPARQLed PoolParty Manual revision/ authoring lodms Classification/ Enrichmen t dl-learner LOD2 Provenance Component Data Cube Validation Tool rdf-dataset-integration Mondeca Sparql Endpoint Status Virtuoso RDF Store (conductor, sparql, isparql, ods) Storage/ Querying LOD2 demonstrator LOD2 stat. Workbench Quality Analysis ORE Web Linkage Validator CSVImpor t Dbpedia Spotlight UI R2R PoolParty Extractor stanbol D2R Virtuoso sponger Dbpedia Spotlight valiant Extraction Semantic Spatial Browser Search/ Browsing/ Exploratio n lod2webapi SigmaEE Evolution / Repair CubeViz Sindice (source) Data Cube Merging Tool LOD open refine Data Cube Slicing Tool
20 Creating Knowledge out of Interlinked Data Eccenca Linked Data Stack 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 Linked Enterprise Data Fraunhofer-Institut für Intelligente 21
22 Daimler CIO Michael Gorriz receives European Data Innovator Award Fraunhofer-Institut für Intelligente 22
23 Classic search Fraunhofer-Institut für Intelligente 23
24 Fraunhofer-Institut für Intelligente Creation of a knowledge base consisting of: 1. car models database
25 Subject Predicate Object Fraunhofer-Institut für Intelligente
26 Creation of a knowledge base: 2. Daim ler Corporate Thes aurus Fraunhofer-Institut für Intelligente Management of Enterprise Taxonomies with OntoWiki Based on the W3C SKOS standard Corporate Language Management at Daimler: 500k
27 Fraunhofer-Institut für Intelligente Semantic search suggestions based on the interlinked knowledge base
28 Fraunhofer-Institut für Intelligente
29 Fraunhofer-Institut für Intelligente
30 Fraunhofer-Institut für Intelligente
31 Cortex - Semantic Search Fraunhofer-Institut für Intelligente 31
32 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 > concurrent users Individual Access Powerful semantic search and performant access of objects Fraunhofer-Institut für Intelligente 32
33 Deutsche Digitale Bibliothek Fraunhofer-Institut für Intelligente 33
34 Fraunhofer-Institut für Intelligente
35 Fraunhofer-Institut für Intelligente
36 Fraunhofer-Institut für Intelligente 36
37 Fraunhofer-Institut für Intelligente 37
38 Kontakt Fraunhofer-Institut IAIS Schloss Birlinghoven Sankt Augustin Prof. Dr. Sören Auer Tel: Die Rechte der Logos und Bilder verbleiben bei ihren Eigentümern. Fraunhofer-Institut für Intelligente 38
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