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Modeling Classification Systems in Multicultural and Multilingual Contexts

Modeling Classification Systems in Multicultural and Multilingual Contexts. Joan S. Mitchell OCLC, Inc. Marcia Lei Zeng Kent State University Maja Žumer University of Ljubljana , Slovenia. History.

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Modeling Classification Systems in Multicultural and Multilingual Contexts

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  1. Modeling Classification Systems in Multicultural and Multilingual Contexts Joan S. Mitchell OCLC, Inc. Marcia Lei Zeng Kent State University Maja Žumer University of Ljubljana, Slovenia

  2. History • Long-term research project to model classification systems using general conceptual models to support organization and discovery in Semantic Web settings • Can the FRSAD conceptual model be extended to model classification data? (presented at UDC Seminar, 2011) • Can the FRBR model be used to represent the complex relationships among different versions of classification systems? (presented at ISKO conference, 2012)

  3. Current Study Can the FRSAD conceptual model be extended to model classification data in order to derive implementable models for classification systems that involve multiple translations and/or multicultural implementations?

  4. Outline • FRSAD conceptual model • FRSAD model for classification systems • DDC translation case study • Chinese Library Classification case study • Use cases • Future work

  5. 1. FRSAD Conceptual Model

  6. The core of the FRSAD conceptual model FRSAD Part 1:WORK has as subject THEMA / THEMA is subject of WORK FRSAD Part 2:THEMA has appellation NOMEN / NOMEN is appellation of THEMA NOMEN = any sign or sequence of signs (alphanumeric characters, symbols, sound, etc.) that a thema is known by, referred to or addressed as

  7. 2. FRSAD model for classification systems • Thema corresponds to the full category description of the class • Nomen is the symbol (or surrogate) used to represent the full category description

  8. Thema: Class 025.04

  9. Nomens: DDC number, Full caption, URI 025.04 Computer science, information & general works/Library & information sciences/Operations of libraries, archives, information centers/Information storage and retrieval systems http://dewey.info/class/025.04/

  10. Alternative nomens: Relative Index terms with explicit functional equivalence relationship ( ) to class 025.04

  11. 3. DDC translation case study

  12. Relationships between DDC classes in translations • Thema [class] 22/eng = Thema [class] 22/swe • Nomens may be used interchangeably (if not limited by a language-specific attribute)

  13. Equivalent classes at same notational level Class 741.5 22/eng Class 741.5 22/swe

  14. Interchangeable Nomens for Class 741.5 741.5 Arts & recreation / Drawing & decorative arts / Drawing and drawings / Special applications / Comic books, graphic novels, fotonovelas, cartoons, caricatures, comic strips Konst & fritid / Teckningskonst och konsthantverk / Teckningskonst och teckningar / Speciella tillämpningsområden / Seriemagasin, grafiska romaner, fotonovelas, tecknade serier, karikatyrer, skämtserier http://dewey.info/class/741.5/

  15. Equivalent classes at same notational level, with further expansion in one edition Class T2—4888 22/eng Class T2—4888 22/swe

  16. Relationship between terminal class in one edition with interoperable subclasses in another edition

  17. 4. Chinese Library Classification case study

  18. CLC Class J29 Calligraphy

  19. Alternative (optional) notation Q Biological sciences [Q89] Environmental biology Preferred class: X17 X1 Environmental Sciences . . . X17 Environmental biology

  20. 5. Use cases • Translation • Mapping • Integration • Discovery

  21. Example: Integration (Virtual scope note) T2—4888 (22/eng) T2—4888+ (22/swe)

  22. Example: Discovery T2—4888 (22/eng) T2—4888+ (22/swe) Relative Index term “Pajala kommun (Sverige)” retrieves T2—4888 (22/eng) or T2—488846 (22/swe)

  23. 6. Future work • Model Relative Index as a separate controlled vocabulary under the FRSAD conceptual model to explore topic-centered approach (exploratory work under way by R. Green) • Investigate mapped terminology from other controlled vocabularies • Investigate mapped relationships between different classification systems

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