Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Interlinking Data and Knowledge...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
„Tere, maailm!”
2011 PhD at Jac...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
EIS/OK Group in Bonn
Prof. Söre...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Data in Today’s Society
Example...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Example: Accessible Facilities
...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Data in Science
Example (Qualit...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Data in Science: Datasets
Sourc...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Data Sources of Interest
(Open)...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Linked (Open) Data: Principles
...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Linked (Open) Data: Datasets
As...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Data Integration in Large Organ...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
XML, Web Services, SOA: Pros an...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
From Documents to Data
Web 1.0 ...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Web of Data: schema.org
initiat...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Web of Data: schema.org
initiat...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Web of Data: schema.org
initiat...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Web of Data: schema.org
initiat...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Social Data with schema.org
rev...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
schema.org in a Search Engine
L...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
The Web and Intranets: Evolutio...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Web and Intranet: Common Proper...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Linked Organisational Data Prin...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Organisational Knowledge Bases
...
Mercedes-Benz Search Demo I
Search before
Mercedes-Benz Search Demo II
OntoWiki with car model data
Mercedes-Benz Search Demo III
OntoWiki
with car
model data
Mercedes-Benz Search Demo IV
Management of Enterprise Taxonomies with OntoWiki
based on the W3C SKOS standard
Corporate La...
Mercedes-Benz Search Demo V
Search after
Showing recommen-
dations from the
knowledge base in-
tegrating car model
data an...
Mercedes-Benz Search Demo VI
You can search for
“Kombi” (station
wagon) and find
“T-Models” (Daim-
ler term for the
same)
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Identification by an
Organisati...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Properties of URIs
Decentral ma...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Identifier Management Strategie...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Linked Organisational Data Life...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Interdependence of Lifecycle St...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Linked Data Quality: Metrics
Qu...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Analysing Linked Data Quality
J...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Relational Data to RDF
Most exi...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
R2RML
R2RML (relational databas...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
R2RML
Example (mapping a thesau...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
R2RML
Example (mapping a thesau...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Data Portals
How to discover su...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Link Discovery Tools
1
Found a ...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Enterprise Knowledge Hub [Fri+1...
Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion
Take Home Messages
Linked Data:...
References
References I
5 star Open Data. Apr. 3, 2012. url:
http://5stardata.info/ (visited on 2013-09-18).
S. Auer, L. B...
References
References II
J. Debattista, C. Lange, and S. Auer. “daQ, an Ontology
for Dataset Quality Information”. In: Lin...
References
References III
E. Hyvönen, J. Tuominen, M. Alonen, and E. Mäkelä.
“Linked Data Finland: A 7-star Model and Plat...
References
References IV
A. Zaveri, A. Rula, A. Maurino, R. Pietrobon,
J. Lehmann, and S. Auer. “Quality Assessment
Method...
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Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data

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The Linked Data paradigm has emerged as a powerful enabler for data and knowledge interlinking and exchange using standardised Web technologies.
In this article, we discuss our vision how the Linked Data paradigm can be employed to evolve the intranets of large organisations -- be it enterprises, research organisations or governmental and public administrations -- into networks of internal data and knowledge.
In particular for large enterprises data integration is still a key challenge. The Linked Data paradigm seems a promising approach for integrating enterprise data. Like the Web of Data, which now complements the original document-centred Web, data intranets may help to enhance and flexibilise the intranets and service-oriented architectures that exist in large organisations. Furthermore, using Linked Data gives enterprises access to 50+ billion facts from the growing Linked Open Data (LOD) cloud. As a result, a data intranet can help to bridge the gap between structured data management (in ERP, CRM or SCM systems) and semi-structured or unstructured information in documents, wikis or web portals, and make all of these sources searchable in a coherent way.

Keynote at Baltic DB&IS 2014, 9 June 2014, Tallinn, Estonia

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Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data

  1. 1. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data Baltic DB & IS 2014 http://eis.iai.uni-bonn.de Christoph Lange1,2 and Sören Auer1,2 1Enterprise Information Systems, University of Bonn, Germany 2Organized Knowledge, Fraunhofer IAIS, Sankt Augustin, Germany 2014-06-09 Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 1
  2. 2. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion „Tere, maailm!” 2011 PhD at Jacobs Univ. Bremen, Germany: Enabling Collaboration on Semiformal Mathematical Knowledge by Semantic Web Integration [Lan11] 2011/12 Univ. Bremen, Germany: Ontology Integration and Interoperability (OntoIOp) ↝ Distributed Ontology Language (DOL) 2012/13 Univ. Birmingham, UK: Formal Mathematical Reasoning in Economics (ForMaRE) [KLR] 2013– Univ. Bonn, Germany: Enterprise Information Systems; Fraunhofer IAIS: Organized Knowledge Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 2
  3. 3. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion EIS/OK Group in Bonn Prof. Sören Auer previously at the University of Leipzig, AKSW group (DBpedia etc.) Christoph Lange: 1 of 3 postdocs ∼ 15 members of scientific staff 6 PhD students Business areas: Enterprise Information Integration Digital Libraries (cultural heritage and other applications) Personalised medicine Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 3
  4. 4. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Data in Today’s Society Example (Demographics in Bonn) Statistics, e.g. from municipal office for integration Housing (accessibility, availability, . . . ): municipal, commercial, self-organised Transport (e.g. accessibility): bus/tram Infrastructure: e.g. accessible public toilets Complex questions: Apartments that meet my requirements w.r.t. public transport, accessibility, care, co-residents What bus takes me from A to B, with sufficient changing time near an accessible toilet? Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 4
  5. 5. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Example: Accessible Facilities Collected by the Bonn Disableds’ Union. Now combine with public transport, housing offers, . . . ! Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 5
  6. 6. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Data in Science Example (Quality of Scientific Workshops) Indicators for the quality of a workshop: part of a high-profile conference long history many editions continuity in chairs number of papers not shrinking contributions from many institutions and countries Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 6
  7. 7. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Data in Science: Datasets Sources of complementary information: DBLP computer science publications (basics), author name disambiguation CEUR-WS.org computer science workshops → ESWC 2014 Semantic Publishing Challenge Springer computer science conferences WikiCFP calls for papers Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 7
  8. 8. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Data Sources of Interest (Open) Government Data general Open Data: Wikipedia, OpenStreetMap, . . . private data personal data How can they be . . . 1 published (licenses, privacy), 2 described (for machines to understand), 3 discovered, 4 integrated, 5 analysed? Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 8
  9. 9. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Linked (Open) Data: Principles http://5stardata.info ☀ make your stuff available on the Web (whatever format) under an open li- cense ☀☀ make it available as structured data (e.g., Excel instead of image scan of a table) ☀☀☀ use non-proprietary formats (e.g., CSV instead of Excel) ☀☀☀☀ use URIs to denote things, so that people can point at your stuff ☀☀☀☀☀ linkyourdatatootherdatatoprovide context [12] ☀☀☀☀☀☀ further stars proposed for: quality [DLA14], explicit schema [Hyv+] Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 9
  10. 10. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Linked (Open) Data: Datasets As of September 2011 Music Brainz (zitgist) P20 Turismo de Zaragoza yovisto Yahoo! Geo Planet YAGO World Fact- book El Viajero Tourism WordNet (W3C) WordNet (VUA) VIVO UF VIVO Indiana VIVO Cornell VIAF URI Burner Sussex Reading Lists Plymouth Reading Lists UniRef UniProt UMBEL UK Post- codes legislation data.gov.uk Uberblic UB Mann- heim TWC LOGD Twarql transport data.gov. uk Traffic Scotland theses. fr Thesau- rus W totl.net Tele- graphis TCM Gene DIT Taxon Concept Open Library (Talis) tags2con delicious t4gm info Swedish Open Cultural Heritage Surge Radio Sudoc STW RAMEAU SH statistics data.gov. uk St. Andrews Resource Lists ECS South- ampton EPrints SSW Thesaur us Smart Link Slideshare 2RDF semantic web.org Semantic Tweet Semantic XBRL SW Dog Food Source Code Ecosystem Linked Data US SEC (rdfabout) Sears Scotland Geo- graphy Scotland Pupils & Exams Scholaro- meter WordNet (RKB Explorer) Wiki UN/ LOCODE Ulm ECS (RKB Explorer) Roma RISKS RESEX RAE2001 Pisa OS OAI NSF New- castle LAAS KISTI JISC IRIT IEEE IBM Eurécom ERA ePrints dotAC DEPLOY DBLP (RKB Explorer) Crime Reports UK Course- ware CORDIS (RKB Explorer) CiteSeer Budapest ACM riese Revyu research data.gov. ukRen. Energy Genera- tors reference data.gov. uk Recht- spraak. nl RDF ohloh Last.FM (rdfize) RDF Book Mashup Rådata nå! PSH Product Types Ontology Product DB PBAC Poké- pédia patents data.go v.uk Ox Points Ord- nance Survey Openly Local Open Library Open Cyc Open Corpo- rates Open Calais OpenEI Open Election Data Project Open Data Thesau- rus Ontos News Portal OGOLOD Janus AMP Ocean Drilling Codices New York Times NVD ntnusc NTU Resource Lists Norwe- gian MeSH NDL subjects ndlna my Experi- ment Italian Museums medu- cator MARC Codes List Man- chester Reading Lists Lotico Weather Stations London Gazette LOIUS Linked Open Colors lobid Resources lobid Organi- sations LEM Linked MDB LinkedL CCN Linked GeoData LinkedCT Linked User Feedback LOV Linked Open Numbers LODE Eurostat (Ontology Central) Linked EDGAR (Ontology Central) Linked Crunch- base lingvoj Lichfield Spen- ding LIBRIS Lexvo LCSH DBLP (L3S) Linked Sensor Data (Kno.e.sis) Klapp- stuhl- club Good- win Family National Radio- activity JP Jamendo (DBtune) Italian public schools ISTAT Immi- gration iServe IdRef Sudoc NSZL Catalog Hellenic PD Hellenic FBD Piedmont Accomo- dations GovTrack GovWILD Google Art wrapper gnoss GESIS GeoWord Net Geo Species Geo Names Geo Linked Data GEMET GTAA STITCH SIDER Project Guten- berg Medi Care Euro- stat (FUB) EURES Drug Bank Disea- some DBLP (FU Berlin) Daily Med CORDIS (FUB) Freebase flickr wrappr Fishes of Texas Finnish Munici- palities ChEMBL FanHubz Event Media EUTC Produc- tions Eurostat Europeana EUNIS EU Insti- tutions ESD stan- dards EARTh Enipedia Popula- tion (En- AKTing) NHS (En- AKTing) Mortality (En- AKTing) Energy (En- AKTing) Crime (En- AKTing) CO2 Emission (En- AKTing) EEA SISVU educatio n.data.g ov.uk ECS South- ampton ECCO- TCP GND Didactal ia DDC Deutsche Bio- graphie data dcs Music Brainz (DBTune) Magna- tune John Peel (DBTune) Classical (DB Tune) Audio Scrobbler (DBTune) Last.FM artists (DBTune) DB Tropes Portu- guese DBpedia dbpedia lite Greek DBpedia DBpedia data- open- ac-uk SMC Journals Pokedex Airports NASA (Data Incu- bator) Music Brainz (Data Incubator) Moseley Folk Metoffice Weather Forecasts Discogs (Data Incubator) Climbing data.gov.uk intervals Data Gov.ie data bnf.fr Cornetto reegle Chronic- ling America Chem2 Bio2RDF Calames business data.gov. uk Bricklink Brazilian Poli- ticians BNB UniSTS UniPath way UniParc Taxono my UniProt (Bio2RDF) SGD Reactome PubMed Pub Chem PRO- SITE ProDom Pfam PDB OMIM MGI KEGG Reaction KEGG Pathway KEGG Glycan KEGG Enzyme KEGG Drug KEGG Com- pound InterPro Homolo Gene HGNC Gene Ontology GeneID Affy- metrix bible ontology BibBase FTS BBC Wildlife Finder BBC Program mes BBC Music Alpine Ski Austria LOCAH Amster- dam Museum AGROV OC AEMET US Census (rdfabout) Media Geographic Publications Government Cross-domain Life sciences User-generated content http://lod-cloud.net datacatalogs.org: 285 data catalogues original data (= ground truth) still often missing Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 10
  11. 11. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Data Integration in Large Organisations Enterprise information integration: a key field of business of the OK department at Fraunhofer IAIS production-critical information often maintained in dedicated IS already: ERP, CRM, SCM, . . . challenge: integration of these systems (with each other, and with external sources) Daimler, e.g., runs 3,000 independent IT systems (after a decade of consolidation!) Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 11
  12. 12. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion XML, Web Services, SOA: Pros and Cons Previous approaches to enterprise IT: XML syntactic data representation Web services data exchange protocols SOA holistic approach for distributed system architecture and communication Still insufficient for data integration SOA is good for transaction processing, . . . . . . Linked Data is more efficient for networking and integrating data: access to LOD Cloud, lightweight, flexible Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 12
  13. 13. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion From Documents to Data Web 1.0 static documents “Web 1.5” content management and e-commerce systems, exposing databases in a user- and context-specific way Web 2.0 user-generated content; mashups aggregating data from different sources Web of Data popular examples: schema.org, Google Knowledge Graph, Facebook Open Graph Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 13
  14. 14. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Web of Data: schema.org initiative of major search engine operators annotation vocabulary for structuring web pages (creative works, events, organisations, persons, places, products) Example (Movie description) Avatar Director: James Cameron (born August 16, 1954) Science fiction Trailer Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 14
  15. 15. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Web of Data: schema.org initiative of major search engine operators annotation vocabulary for structuring web pages (creative works, events, organisations, persons, places, products) Example (Movie description) <div class="movie"> <h1>Avatar</h1> <div class="director"> Director: James Cameron (born August 16, 1954) </div> <span class="genre">Science fiction</span> <a href="../movies/avatar-theatrical-trailer.html" Trailer</a> </div> Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 14
  16. 16. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Web of Data: schema.org initiative of major search engine operators annotation vocabulary for structuring web pages (creative works, events, organisations, persons, places, products) Example (Movie description) <div itemscope itemtype="http://schema.org/Movie"> <h1 itemprop="name">Avatar</h1> <div itemprop="director" itemscope itemtype="http://schema.org/Person"> Director: <span itemprop="name">James Cameron</span> (born <span itemprop="birthDate">August 16, 1954</span>) </div> <span itemprop="genre">Science fiction</span> <a href="../movies/avatar-theatrical-trailer.html" itemprop="trailer">Trailer</a> </div> Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 14
  17. 17. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Web of Data: schema.org initiative of major search engine operators annotation vocabulary for structuring web pages (creative works, events, organisations, persons, places, products) Example (Movie description) Movie Avatar Person James Cameron August 16, 1954Science fiction../movies/. . . type nam e director genre trailer type name birthDate Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 14
  18. 18. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Social Data with schema.org review or rating of a creative work, organization or product (written by a person) social network of a person: “knows”, “works for”, “is colleague of”, “has parent/sibling/spouse/child/relative” Example (Reviews of a movie) Movie type Avatar name reviews authorreviewRating reviews author reviewRating 6 ratingValue 8.5 ratingValue Pünktchen name Anton name Person type type knows Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 15
  19. 19. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion schema.org in a Search Engine Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 16
  20. 20. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion The Web and Intranets: Evolution Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 17
  21. 21. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Web and Intranet: Common Properties Especially large organisations share these properties of the WWW: Decentral organisation Self-dependent units, often free to choose their information architecture Heterogeneous information: domain-specific applications, knowledge bases, document templates, data formats . . . vary across organisational units Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 18
  22. 22. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Linked Organisational Data Principles The 5-star Linked Data principles (above), plus: evolve existing thesauri, taxonomies, wikis and master data management systems into corporate knowledge bases and knowledge hubs establish an organisation-wide URI scheme extend existing information system in the intranet by linked data interfaces establish links between sources of related information Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 19
  23. 23. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Organisational Knowledge Bases Organisation and Domain-specific knowledge is in: glossaries, taxonomies, internal documents, data schemas. Large organisations often standardise terminology in multilingual thesaury Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 20
  24. 24. Mercedes-Benz Search Demo I Search before
  25. 25. Mercedes-Benz Search Demo II OntoWiki with car model data
  26. 26. Mercedes-Benz Search Demo III OntoWiki with car model data
  27. 27. Mercedes-Benz Search Demo IV Management of Enterprise Taxonomies with OntoWiki based on the W3C SKOS standard Corporate Language Management at Daimler: 500K concepts in 20 languages
  28. 28. Mercedes-Benz Search Demo V Search after Showing recommen- dations from the knowledge base in- tegrating car model data and enterprise taxonomy
  29. 29. Mercedes-Benz Search Demo VI You can search for “Kombi” (station wagon) and find “T-Models” (Daim- ler term for the same)
  30. 30. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Identification by an Organisation-wide URI Schema Unique identifiers are a key prerequisite for information integration: general: persons, places, organisations specific: terms, data sources, products, contracts On the Web: URI for identification, URLs for making information accessible. In Linked Data: use URLs as URIs Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 27
  31. 31. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Properties of URIs Decentral maintenance: different levels, combinations possible (next slide) Dereferenceability (i.e. URIs = URLs) Provenance (URI reveals organisational unit ↝ authenticity and correctness of information) Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 28
  32. 32. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Identifier Management Strategies Management strategy + – Issue uniform URIs cen- trally easy overview of re- sources uniform identifier struc- ture single point of failure low flexibility hard to ensure derefer- enceability Issue decentrally, regis- ter centrally easy overview of re- sources resilient against techni- cal failure and organisa- tional changes requires synchronisa- tion Manage completely de- centrally highly flexible highly resilient against technical failure and or- ganisational changes lack of central overview lack of structural unifor- mity Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 29
  33. 33. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Linked Organisational Data Lifecycle Of particular interest: RDF data management: including relational sources Authoring Linking: detect links between datasets Classification, Enrichment Quality Assessment: data from the Web “fit for use”? Evolution, Repair Search, Exploration Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 30
  34. 34. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Interdependence of Lifecycle Stages Lifecycle stages depend on each other ⇒ addressing one also affects the others, e.g.: 1 enrich knowledge base with links to a new knowledge hub 2 auto-linker will find additional matches Schema and instance levels influence each other, e.g.: rich schema prevents instance-level problems can learn schema-level matches from instances LOD2.eu project has developed tools for the whole life cycle (available for Debian and others) [Aue+12] Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 31
  35. 35. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Linked Data Quality: Metrics Quality = “fitness for use”. Subjective? There are objec- tive, even application-independent metrics! [Zav+13] Accessibility: actually linked data; machine-readable license; performance of access? Intrinsic aspects: no logical inconsistencies; no malformed literal values; no redundancies? Trust: provenance metadata; digital signature? Dynamicity: recent data? Contextual aspects: broad use of schema’s features; good coverage of domain? Representation: existing terms reused; human-readable documentation? Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 32
  36. 36. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Analysing Linked Data Quality Java library for quality metrics in progress We support big datasets (streaming triples) Output once more as linked data [DLA14] – why? complexity: data cube with dimensions metric, dataset, time, intended application, . . . (e.g. “completeness of DBpedia 3.9 for a Tallinn tourist guide”) can → browse datasets by quality Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 33
  37. 37. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Relational Data to RDF Most existing information systems use relational databases – choice between 1 materialising relational database into linked data 2 expose it as virtual RDF graph by on-demand query translation Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 34
  38. 38. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion R2RML R2RML (relational database to RDF mapping language), W3C Recommendation Example (mapping a thesaurus) SUBJECT CONCEPTS +===+=========+=========+=========+ +===============+ |ID | SUBJECT | TERM_EN | TERM_ET | |ID | SUBJECT | +===+=========+=========+=========+ +===+===========+ | 1 | 1 | hammer | Vasar | | 1 | tools | | 2 | 1 | file | Viil | | 2 | chemistry | | 3 | 2 | oil | Õli | +===+===========+ +===+=========+=========+=========+ Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 35
  39. 39. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion R2RML Example (mapping a thesaurus) SUBJECT CONCEPTS +===+=========+=========+=========+ +===============+ |ID | SUBJECT | TERM_EN | TERM_ET | |ID | SUBJECT | +===+=========+=========+=========+ +===+===========+ | 1 | 1 | hammer | Vasar | | 1 | tools | | 2 | 1 | file | Viil | | 2 | chemistry | | 3 | 2 | oil | Õli | +===+===========+ +===+=========+=========+=========+ :ConceptsTriplesMap rr:logicalTable [ rr:tableName "CONCEPTS" ] ; rr:subjectMap [ rr:template "http://example.com/term/concept/{ID}" ; rr:class skos:Concept ; ] ; rr:predicateObjectMap [ rr:predicate skos:prefLabel ; rr:objectMap [ rr:column "TERM_ET" ; rr:language "et" ] ; ] .Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 35
  40. 40. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion R2RML Example (mapping a thesaurus) SUBJECT CONCEPTS +===+=========+=========+=========+ +===============+ |ID | SUBJECT | TERM_EN | TERM_ET | |ID | SUBJECT | +===+=========+=========+=========+ +===+===========+ | 1 | 1 | hammer | Vasar | | 1 | tools | | 2 | 1 | file | Viil | | 2 | chemistry | | 3 | 2 | oil | Õli | +===+===========+ +===+=========+=========+=========+ :ConceptsTriplesMap rr:logicalTable [ rr:tableName "CONCEPTS" ] ; rr:subjectMap [ rr:template "http://example.com/term/concept/{ID}" ; rr:class skos:Concept ; ] ; rr:predicateObjectMap [ rr:predicate skos:prefLabel ; rr:objectMap [ rr:column "TERM_ET" ; rr:language "et" ] ; ] . <http://example.com/term/concept/1> a skos:Concept . <http://example.com/term/concept/1> skos:prefLabel "Vasar"@et . Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 35
  41. 41. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Data Portals How to discover suitable open datasets? ⇒ look into data catalogues, e.g. http://datahub.io Quality-based filtering and ranking Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 36
  42. 42. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Link Discovery Tools 1 Found a dataset that’s “fit for use”? 2 Link them to existing organisational datasets! LOD2 tools Silk and LIMES help with this Rule example: similar name, and ⋃︀price − price′ < 0.1⋃︀ ⇒ create owl:sameAs link 3 <foo> owl:sameAs <bar> means: all properties of foo also hold for bar, and vice versa. Linking particularly pays off on the terminology level; DBpedia serves as a common referencing target for almost anything of interest. Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 37
  43. 43. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Enterprise Knowledge Hub [Fri+13] Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 38
  44. 44. Introduction Motivation Evolution Knowledge URIs Lifecycle Interfaces Discovery Conclusion Take Home Messages Linked Data: promising technology for closing the gap between SOA and unstructured information management wealth of LOD can be leveraged as background knowledge for Enterprise applications application of Linked Data in large organisations (in enterprises, research and society) is still largely unexplored (⇒ opportunity!) Linked Data will make Organisational Information Integration more flexible iterative cost effective Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 39
  45. 45. References References I 5 star Open Data. Apr. 3, 2012. url: http://5stardata.info/ (visited on 2013-09-18). S. Auer, L. Bühmann, C. Dirschl, O. Erling, M. Hausenblas, R. Isele, J. Lehmann, M. Martin, P. N. Mendes, B. van Nuffelen, C. Stadler, S. Tramp, and H. Williams. “Managing the life-cycle of Linked Data with the LOD2 Stack”. In: Proceedings of International Semantic Web Conference (ISWC 2012). 22% acceptance rate. 2012. url: http://iswc2012.semanticweb.org/sites/ default/files/76500001.pdf. Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 40
  46. 46. References References II J. Debattista, C. Lange, and S. Auer. “daQ, an Ontology for Dataset Quality Information”. In: Linked Data on the Web (LDOW). (Seoul, Apr. 8, 2014). Ed. by C. Bizer, T. Heath, S. Auer, and T. Berners-Lee. 2014. url: http://events.linkeddata.org/ldow2014/. P. Frischmuth, S. Auer, S. Tramp, J. Unbehauen, K. Holzweißig, and C.-M. Marquardt. “Towards Linked Data based Enterprise Information Integration”. In: Proceedings of the Workshop on Semantic Web Enterprise Adoption and Best Practice (WASABI) 2013. 2013. url: http://www.wasabi- ws.org/papers/wasabi03/paper.pdf. Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 41
  47. 47. References References III E. Hyvönen, J. Tuominen, M. Alonen, and E. Mäkelä. “Linked Data Finland: A 7-star Model and Platform for Publishing and Re-using Linked Datasets”. In: M. Kerber, C. Lange, and C. Rowat. ForMaRE. Formal Mathematical Reasoning in Economics. url: http:// cs.bham.ac.uk/research/projects/formare/ (visited on 2013-02-10). C. Lange. “Enabling Collaboration on Semiformal Mathematical Knowledge by Semantic Web Integration”. PhD thesis. Jacobs University Bremen, 2011. Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 42
  48. 48. References References IV A. Zaveri, A. Rula, A. Maurino, R. Pietrobon, J. Lehmann, and S. Auer. “Quality Assessment Methodologies for Linked Open Data (Under Review)”. In: Semantic Web Journal (2013). This article is still under review. url: http://www.semantic- web-journal.net/content/quality- assessment-linked-open-data-survey. Lange/Auer (Bonn) Interlinking Data and Knowledge in Enterprises, Research and Society with Linked Data 2014-06-09 43

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