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Tumbling Walls Tumbling Walls & &
Building BridgesBuilding Bridges
Semantic Web Technologies for
Practical Applications
Guus SchreiberFree University Amsterdam
Co-chair W3C Semantic WebDeployment Working Group
Overview
• Non-tech intro to Semantic Web• Semantics for the Web• Two application examples• Principles and techniques• W3C activities• Semantic Web: hope or hype?
Non-tech intro to the Semantic Web
The Web: resources and links
URL URLWeb link
The Semantic Web: typed resources and links
URL URLWeb link
ULAN
Henri Matisse
Dublin Core
creator
Painting“Woman with hat
SFMOMA
Principle 1: semantic annotation
• Description of web objects with “concepts”from a shared vocabulary
Principle 2: semantic search• Search for objects
which are linked via concepts (semantic link)
• Use the type of semantic link to provide meaningful presentation of the search results
Paris
Montmartre
PartOf
Query“Paris”
Principle 3: multiple vocabularies. or: the myth of a unified vocabulary• In large virtual collections there are always
multiple vocabularies – In multiple languages
• Every vocabulary has its own perspective– You can’t just merge them
• But you can use vocabularies jointly by defining a limited set of links– “Vocabulary alignment”
• It is surprising what you can do with just a few links
Example“Tokugawa”
AAT style/periodEdo (Japanese period)Tokugawa
SVCN periodEdo
SVCN is local in-house ethnology thesaurus
Semantics for the Web
Challenges
• Machine-processable representation of semantic information
• Defining semantics in an OPEN environment– Adding semantics to other people’s
semantics – Ability for everyone to contribute
• Ability to define mappings between semantic representations– There is no uniform way to classify the
world!
The notion of ontology (as currently used in computer science)
• The Semantic Web needs sets of shared concepts
• These sets of concepts are called “ontologies”
• It is hard and time-consuming to develop ontologies
• Therefore, the Semantic Web developers are looking for existing ontologies, vocabularies, taxonomies
Ontologies and data models
• Main difference with data models is not the content, but the purpose (generalizes over applications)
• You cannot see the difference by just looking at the syntax!
• A conceptual model written in a ontology language is not necessarily an ontology!
Example “ontologies” for SW applications
• Domain-specific vocabularies– Medicine: UMLS, SNOMED, Galen– Art history: AAT, ULAN– Geography: TGN
• Generic ontologies – Top-level categories (reminiscent of
Aristotelian categories)– Lexical vocabularies: WordNet– Units and dimensions, time ontology– Currencies, country codes, …
Good and bad ontologies?!
• Good ontologies are used• Good ontologies represent some form
of consensus in a community• Good ontologies are maintained• Good ontologies do not need to be
complex• Good ontologies may contain
“mistakes”
Levels of interoperability
• Syntactic interoperability– using data formats that you can share– XML family is the preferred option
• Semantic interoperability– How to share meaning / concepts– Technology for finding and representing
semantic links
Two application examples
DOPE: semantic search of large document repositories
• Stuckerschmidt et al. (2003)• EMTREE thesaurus (MeSH-based)• Documents
– 5M Medline abstracts– 500M of full-text articles
• Automatic document indexing• RDF used for syntactic interoperability
– RDF wrapper for SOAP-based access to documents• Disambiguation of search terms• Visualization of search results through semantic
categories– Needed to prevent information overflow
• Part of large Dutch knowledge-economy project MultimediaN
• Partners: VU, CWI, UvA, DEN,ICN
• People: Alia Amin, Lora Aroyo, Mark van Assem, Victor de Boer, Lynda Hardman, Michiel Hildebrand, Laura Hollink, Marco de Niet, Borys Omelayenko, Marie-France van Orsouw, Jacco van Ossenbruggen, Guus SchreiberJos Taekema, Annemiek Teesing,Anna Tordai, Jan Wielemaker, Bob Wielinga
• Artchive.com, Rijksmuseum Amsterdam, Dutch ethnology musea (Amsterdam, Leiden), National Library (Bibliopolis)
E-Culture demonstrator
http://e-culture.multimedian.nl
Semantic Web applicationsprinciples and techniques
Principle 1: Be modest!
• Do the things you’re good at• Use resources of others where
possible– E.g. geographical vocabularies, lexical
resources, such as WordNet
Principle 2: Think Large!
"Once you have a truly massive amount of information integrated as knowledge, then the human-software system will be superhuman, in the same sense that mankind with writing is superhuman compared to mankind before writing."
• Don’t be afraid to include large external resources•The technology can handle it!
Principle 3: Don’t strive for perfection!
• The “not invented here” syndrome• Don’t discard an external resource
because it does not exactly meet your needs
• Just create your local extensions– The technology for this exists
Principle 4: Use open (Web) standards
• Why does the Web work? – Because it moved away from vendor-
specific formats• XML-related standards make shared
life so much easier• Think thrice before embarking on
Flash– Even forgetting the accessibility
problems for a moment
Technique: syntactic vocabulary interoperability
• Make your vocabularies available in the Web standard RDF
• Many organizations are already do this
• W3C provides the SKOS template to make this almost straightforward
• Effort required: at most a few days
Technique:information extraction
MATISSE, HenriLe bonheur de vivre (The Joy of Life)1905-1906Oil on canvas, 69 1/8 x 94 7/8 in. (175 x 241 cm)Barnes Foundation, Merion, PA
Textual annotation mapped to vocabulary terms
Technique: enriching vocabularies
Technique: vocabulary alignment
• Find semantic links between vocabulary terms:– Derain (ULAN) related-to Fauve (AAT))
• Automatic techniques exists, but performance varies
• Often combination of automatic and manual alignment
• Effort strongly dependent on vocabularies– But “a little semantic goes a long way”
(Hendler)
W3C Semantic Web activities
http://www.w3.org/2001/sw/
• RDF/OW: ontology representation• SPARQL: query language• RIF: rule language• Health Care & Life Sciences group• SW Education & Outreach• SW Deployment group
W3C Semantic Web Deployment WG
SKOS: RDF pattern for thesaurus modeling
• Based on ISO standard– broader/narrower. related, multilinguality
• Documentation:http://www.w3.org/TR/swbp-skos-core-guide/
Semantic WebHope or Hype?
16 Nov 200616 Nov 2006
Dave Beckett’s blog about ISWC 2006
http://www.oracle.com/technology/tech/semantic_technologies/index.html
http://esw.w3.org/topic/HCLSIG/Drug_Safety_and_Efficacy
http://www.geneontology.org/GO.downloads.ontology.shtml
et ceterahttp://esw.w3.org/topic/CommercialProducts
http://web.resource.org/rss/1.0/spec
Take-home message
• Basic Semantic Web technology is ready for deployment
• Social barriers have to be overcome!– “open door” policy
• Make sure you can connect others and other can connect to you– “Don’t buy software which does not
support standard open API’s”
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