Tumbling Walls Tumbling Walls & &

Building BridgesBuilding Bridges

Steps towards a Culture Web

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Interoperability: tearing down the walls between collections

• Musea have increasingly nice websites

• But: most of them are driven by stand-alone collection databases

• Data is isolated, both syntactically and semantically

• If users can do cross-collection search, the individual collections become more valuable!

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The Web: “open” documents and links

URL URLWeb link

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The Semantic Web: “open” data and links

URL URLWeb link

Painter“Henri Matisse”

Getty ULAN

creator

Dublin Core

Painting“Green Stripe (Mme Matisse)”Royal Museum of Fine Arts, Copenhagen

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Principle 1: semantic annotation

Description of web objects with “concepts”from a shared vocabulary

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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”

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Principle 3: vocabulary alignment

“Tokugawa”

SVCN periodEdo

SVCN is local in-house ethnology thesaurus

AAT style/periodEdo (Japanese period)Tokugawa

AAT is Getty’s Art & Architecture Thesaurus

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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

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Part of the Dutch national MultimediaN project

CWI, VU, UvA, DEN, ICNAlia 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 Schreiber, Jos Taekema Annemiek Teesing, Anna Tordai

Jan Wielemaker, Bob Wielinga

Artchive.comRijksmuseum Amsterdam

Dutch ethnology musea (Amsterdam, Leiden)

National Library (Bibliopolis)

http://e-culture.multimedian.nl

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Extra slides

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From metadata to semantic metadata

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Example textual annotation

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Resulting semantic annotation (rendered as HTML with RDFa)

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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

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Term disambiguation is key issue in semantic search• Post-query

–Sort search results based on different meanings of the search term

–Mimics Google-type search

• Pre-query–Ask user to disambiguate by

displaying list of possible meanings– Interface is more complex, but more

search functionality can be offered

20Semantic autocompletion

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Faceted (pre query)Faceted search

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skos

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• v

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Multi-lingual labels for concepts

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Learning alignments

• Learning relations between art styles in AAT and artists in ULAN through NLP of art historic texts– “Who are Impressionist painters?”

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Perspectives

• Basic Semantic Web technology is ready for deployment

• Web 2.0 facilities fit well:– Involving community experts in

annotation–Personalization, myArt

• Social barriers have to be overcome!– “open door” policy– Involvement of general public =>

issues of “quality”

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Semantic interoperability• Large, smart web “mash ups”, combining:

– Data: images, metadata & encyclopaedic knowledge (gazetteers, thesauri, Wikipedia, …)

– Visualisations: maps, timelines, social networks, …

• Data too diverse for a traditional database approach– fixed schemas will not work– data includes relational data, XML text, images, video,

…

• Need to link different data sources together– focus on light weight, heuristic approaches– reusing as much as possible (web standards)

• Need new interfaces and search paradigms– need to find relations between pieces of information– need to organize (cluster/rank/filter) the many

relations we will find

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Caveats for museum software • Be wary of Flash

–Accessibility

• Make sure you can connect others and other can connect to you–“Don’t buy software which does not

support standard open API’s”

• Export facilities to common formats (XML, …)

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Semantic Web Myths *)

• Sem Web = Artificial Intelligence on the Web • Relies on centrally controlled ontologies for

“meaning”– as opposed to a democratic, bottom-up

control of terms

• One has to manually add metadata to all Web pages, relational databases, XML data, etc to use it

• It is just ugly XML • One has to learn formal logic, knowledge

representation, description logic, etc. • An academic project, of no interest for industry

*) Adapted from a slide by Frank van Harmelen, panel WWW2006