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CHIME project

This project focuses on improving access to cultural heritage by addressing the challenges of interoperability in museum data. It identifies issues related to syntactic and semantic interoperability, such as disparate naming conventions for object properties and variations in vocabularies. By leveraging Semantic Web technologies, we aim to convert existing data formats into RDF/OWL and utilize standard metadata schemas like Dublin Core and vocabularies such as AAT and WordNet. Our approach also explores the representation of mappings between local and global schemas, promoting better semantic connections among collections.

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CHIME project

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  1. CHIME project Mark van Assem Vrije Universiteit Amsterdam supervisor: Guus Schreiber

  2. Cultural Heritage • CHIME: Cultural Heritage in an Interactive Multimedia Environment • Goal: make cultural heritage (more) accessible • Institutions such as Rijksmuseum have large databases with metadata on their collections

  3. Museum Data • Often database or XML • Art works + background info • No links between data • Own set of metadata items to describe objects, e.g. “title”, “maker” • Own set of vocabularies for metadata values (no ontologies, but thesauri or lists)

  4. Problems • Syntactic interoperability (DB, XML, proprietary text format) • Semantic interoperability • Different names for properties of objects “author” vs. “creator” • Different vocabularies “Rembrandt” vs. “Rembrandt van Rijn”

  5. Solutions • Use Semantic Web technology • Syntactic: convert data to RDF or OWL • Work done: method to convert thesauri to RDF/OWL • Semantic • Use standard metadata schema Dublin Core, VRA • Use standard vocabularies AAT, WordNet, TGN, ULAN • Provide mappings between local and global schemas

  6. Metadata schema • Dublin Core metadata schema: creator • Schema 1: author • Schema 2: maker • s1:author rdfs:subPropertyOf dc:creator • s2:maker rdfs:subPropertyOf dc:creator

  7. Standard Vocabularies • tgn: World, Asia, Thailand • Painting1 s1:createdIn Siam • Painting2 s2:madeIn Thailand • s1:Siam owl:sameAs World, Asia, Thailand • s2:Thailand owl:sameAs …

  8. Current focus • Observation: much mapping research is on how to semi-automatically find them • My focus: how to represent mappings and in which situations they may be useful • Role of ontology learning/text analysis techniques: help in converting museum data, finding semantic links between items

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