STI Summit 2011 - Linked Data & Ontologies

KIT – University of the State of Baden-Wuerttemberg and National Research Center of the Helmholtz Association www.kit.edu

Institute of Applied Informatics and Formal Description Methods (AIFB)

Institute of Applied Informatics and Formal Description Methods (AIFB)

Linked Data & Ontologies Rudi Studer, Elena Simperl, Benedikt Kämpgen 2011 STI Semantic Summit, July 6, 2011

2 July 6, 2011 2011 STI Semantic Summit – Linked Data & Ontologies

Outline

!   Semantic Web ontologies – widely applied !   Did Linked Data kill ontologies? ! Ontologies for Linked Data !   Linked Data for ontologies !   Research and discussion topics


!   Develop and re-organize sites based on domain model !   E.g., sports ontology,

programme ontology

!   One URI per thing !   Link content and allow

exploration of topics !   Leverage external resources

!   E.g., MusicBrainz

Semantic Web Ontologies – widely applied: Content Navigation at BBC

http://www.slideshare.net/reduxd/beyond-the-polar-bear

Created ontologies for its website

Mike Atherton: “the complexities of knowledge call for ontological structures”


Semantic Web Ontologies – widely applied: Content Publishing via schema.org

!   Consensus of Yahoo!, Bing and Google ! Ontologies (and format) to markup web pages !   Web pages more easily interpreted and more

appropriately displayed by search engines !   Large impact on businesses

schema.org

Rich Snippet at Google diTii.com


Semantic Web Ontologies – widely applied: Content Publishing via GoodRelation at BestBuy

! GoodRelation ontology !   Describing businesses

!   Machine interpretable

! BestBuy retailer !   Major GoodRelation

deployer ! RDFa created with forms !   Enhance visibility on the

Web


Semantic Web Ontologies – widely applied: BioPortal at Stanford – Content Navigation and Semantic Search

! Ontologies !   Ontology repository

!   provide means for reuse !   offer standadized vocabulary

!   Enhanced information management: !   biological objects annotated using

the ontology !   improved navigation, filtering

visualization


Summary

!   Many applications for Semantic Web ontologies !   Some adoption at big players with strong

influence on businesses

Nowadays: !   Linked Data principles well adopted !   Many Linked Data sources popping up Not yet clear: What role do ontologies play in the age

of Linked Data?


Did Linked Data Kill Ontologies?

!   A Little Semantics Goes a Long Way (Jim Hendler) !   Lightweight, easy-to-understand ontologies adopted

!   Semantic is not the goal, it is a way to solve a task (Chris Welty) !   Machine learning, statistics and machine power equally

important !   Sloppy, scruffy Semantic Web does not need

ontologies (David R. Karger) ! Ontologies are a luxury and should not hinder open

data publishing and usage


Ontologies in the Age of Linked Data

!   Success of Linked Data !   Viral growth works

surprisingly well

!   Open Data trend

!   Heterogeneous, dirty, inconsistent, not trustworthy…

!   However: Value of grounding Linked Data by ontological structures not yet recognized

!   Slow improvement of ontology usage !   Needs a good balance

between effort and added value that is provided

!   Lightweight ontologies are more easily understood, accepted and used

!   Reuse of ontologies not yet done in practice

vs


Ontologies for Linked Data (1)

!   When publishing and consuming Linked Data, use of ontologies/vocabularies would provide benefits !   Publishing:

!   Less effort in publishing: Reusing well-defined collections of URIs contained in ontologies (e.g., SKOS, Geonames)

!   Easier integration of data when publishing based on ontology !   Having well-defined conceptualizations available


Ontologies for Linked Data (2) !   When publishing and consuming Linked Data, use of

ontologies/vocabularies would provide benefits

!   Consumption: !   Self-describing data guide agents when using Linked Data sources !   Splitting the integration / alignment effort between instance and

schema level !   Reasoning for implicit knowledge

!   e.g., gr:DeliveryModeParcelService rdfs:subClassOf gr:DeliveryMethod


Linked Data for Ontologies !   When building and consuming ontologies use of Linked Data

sources would provide benefits

!   Building: !   Inductive, incremental approach to ontology engineering

!   Less manual modeling effort needed: use Linked Data as source !   No perfection needed: define mappings if you need them

!   Collaborative approach to ontology engineering !   Exploiting Linked Data in games, tagging systems, wikis

!   Consumption: !   The more reuse of Linked Data sources the easier the dynamic

extension of the ontology (e.g., instance of a class)


Research and Discussion Topics

!   New Challengies for ontology engineering methodologies

!   Open Issues for Exploiting Linked Data & ontologies


Do traditional methodologies for ontology engineering and evaluation need to be revised?

Enterprise Ontology [Uschold & King, 1995]

IDEF5 [Benjamin et al. 1994]

CO4 [Euzenat, 1995]

CommonKADS [Schreiber et al., 1999]

Holsapple&Joshi [Holsapple & Joshi, 2002]

On-To-Knowledge [Sure, 2002]

DILIGENT [Pinto et al., 2004]

NeOn Methodology [Gómez-Pérez, 2008]

Ontometric [Gómez-Pérez, 2004]

ONTOCOM [Simperl et al., 2006]


New Requirements for Methodologies

!   More data-driven !   data first, ontology second

!   More reuse-focused !   Leveraging ontology repositories, semantic search

engines !   Emphasis on alignment, especially at the instance level

!   Application-oriented !   Human vs machine-oriented consumption (using

specific technologies)


Open Issues for Exploiting Linked Data & ontologies

!   What ontologies when to reuse for what kinds of data (statistical data, sensor information…) !   What guidelines are around !   Best practices for ontology reuse

!   Statistics of ontology reuse in Linked Data

!   Better usage of modularization concepts !   Application-driven reuse of parts of ontologies and Linked Data


Open Issues for Exploiting Linked Data & ontologies

!   What are the mechanisms for viral growth of Linked Data

!   How to release open data’s potential as a major driver for innovation and for unlocking the full data value

!   Exploiting the social Web !   What are business models for such initiatives

!   Major driver for Open Linked Data: eGovernment !   Specification of standard ontologies in order to push the

release of public sector information as Linked Data


Questions / Comments?

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STI Summit 2011 - Linked Data & Ontologies