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Content

What are those "other" relationships that Dewey possesses and that seem so important to surface? Firstly, there is the relationship of concepts to resources. Dewey has been used for a long time, and over 200,000 numbers are assigned to information resources each year and added to WorldCat by the Library of Congress and the German National Library alone. Secondly, we have relationships between concepts in the scheme itself. Dewey provides a rich set of non-hierarchical relations, indicating other relevant and related subjects across disciplinary boundaries. Thirdly, perhaps most importantly, there is the relationship between the same concepts across different languages. Dewey has been translated extensively, and current versions are available in French, German, Hebrew, Italian, Spanish, and Vietnamese. Briefer representations of the top-three levels (the DDC Summaries) are available in several languages in the DeweyBrowser. This multilingual nature of the scheme allows searchers to access a broader range of resources or to switch the language of--and thus localize--subject metadata seamlessly. MelvilClass, a Dewey front-end developed by the German National Library for the German translation, could be used as a common interface to the DDC in any language, as it is built upon the standard DDC data format. It is not hard to give an example of the basic terminology of a class pulled together in a multilingual way: <class/794.8> a skos:Concept ; skos:notation "794.8"^^ddc:notation ; skos:prefLabel "Computer games"@en ; skos:prefLabel "Computerspiele"@de ; skos:prefLabel "Jeux sur ordinateur"@fr ; skos:prefLabel "Juegos por computador"@es .

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Abstract

Multiple groups at Mayo Clinic organize knowledge with the aid of metadata for a variety of purposes. The ontology group focuses on consumer-oriented health information using several controlled vocabularies to support and coordinate care providers, consumers, clinical knowledge and, as part of its research management, information on clinical trials. Poor findability, inconsistent indexing and specialized language undermined the goal of increasing trial participation. The ontology group designed a metadata framework addressing disorders and procedures, investigational drugs and clinical departments, adopted and translated the clinical terminology of SNOMED CT and RxNorm vocabularies to consumer language and coordinated terminology with Mayo's Consumer Health Vocabulary. The result enables retrieval of clinical trial information from multiple access points including conditions, procedures, drug names, organizations involved and trial phase. The jump in inquiries since the search site was revised and vocabularies were modified show evidence of success.