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Prof. Ray Larson & Prof. Marc Davis UC Berkeley SIMS Tuesday and Thursday 10:30 am - 12:00 pm Fall 2004 http://www.sims.berkeley.edu/academics/courses/is202/f04/. Lecture 22: Thesaurii and Metadata. SIMS 202: Information Organization and Retrieval. Lecture Overview.
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Prof. Ray Larson & Prof. Marc Davis UC Berkeley SIMS Tuesday and Thursday 10:30 am - 12:00 pm Fall 2004 http://www.sims.berkeley.edu/academics/courses/is202/f04/ Lecture 22: Thesaurii and Metadata SIMS 202: Information Organization and Retrieval
Lecture Overview • Review (and expansion) • Facetted Classification • Thesaurus Design and Development • Metadata And Markup • XML As A Metadata Lingua Franca • Dublin Core Revisited • METS • Other Metadata schemas and protocols in XML • Discussion
Lecture Overview • Review (and expansion) • Facetted Classification • Thesaurus Design and Development • Metadata And Markup • XML As A Metadata Lingua Franca • Dublin Core Revisited • METS • Other Metadata schemas and protocols in XML • Discussion
Indexing Languages • An index is a systematic guide designed to indicate topics or features of documents in order to facilitate retrieval of documents or parts of documents • An indexing language is the set of terms used in an index to represent topics or features of documents, and the rules for combining or using those terms
Controlled Vocabularies • Vocabulary control is the attempt to provide a standardized and consistent set of terms (such as subject headings, names, classifications, etc.) with the intent of aiding the searcher in finding information • That is, it is an attempt to provide a consistent set of descriptions for use in (or as) metadata
Hierarchical Classification Literature English French Spanish ... ... ... Prose Poetry Drama ... Prose Poetry Drama ... 16th 17th 18th 19th 16th 17th 18th 19th Slide author: Marti Hearst
Labeled Categories for Hierarchical Classification • LITERATURE • 100 English Literature • 110 English Prose • English Prose 16th Century • English Prose 17th Century • English Prose 18th Century • ... • 111 English Poetry • 121 English Poetry 16th Century • 122 English Poetry 17th Century • ... • 112 English Drama • 130 English Drama 16th Century • … • 200 French Literature Slide author: Marti Hearst
Facetted Categories • Mutually exclusive • Non-overlapping, distinct categories • Relational • Relations between facets, subfacets, and foci (elements) are not restricted to hierarchical generalization-specialization relations • Composable • Combined using grammars of order and relation to form compound descriptions
A Language a English b French c Spanish B Genre a Prose b Poetry c Drama C Period a 16th Century b 17th Century c 18th Century d 19th Century Aa English Literature AaBa English Prose AaBaCa English Prose 16th Century AbBbCd French Poetry 19th Century BbCd Drama 19th Century Facetted Classification Along With Labeled Categories Slide author: Marti Hearst
Ranganathan • PMEST Facets • P(ersonality) • WHO: Types of things • M(atter) • WHAT: Constituent materials • E(nergy) • HOW: Action or activity terms • S(pace) • WHERE: Where things occur • T(ime) • WHEN: When things occur
What is being done? Entity Kind Product By-Product What are its parts? Part What are its properties? Property Material How is this achieved? Process By what means? Operation By whom? Agent Patient Where? Space When? Time “Classical” Facet Analysis
Semantic relationships Is-A (thing/kind, genus/species) Mammals Primates Humans Has-Parts Human Head Eyes Syntactic relationships Compounds Wheat + harvesting = “wheat harvesting” Object + operation = operation on object Semantic and Syntactic Relationships
Facetted Classification • Clearly distinguishes between semantic relationships and syntactic relationships • Semantic relationships • Within a facet • Containment relations • Syntactic relationships • Across facets • Combinatoric relations • Have a “syntax” for syntactic combination of semantic terms
Power of Facet Combinations • The syntactic relations of facetted classifications enable a small controlled vocabulary to produce • Many, many structured descriptions • Complex, but formally structured descriptions using nested compound descriptions • Descriptions for things we do not have words for
Lecture Overview • Review (and expansion) • Facetted Classification • Thesaurus Design and Development • Metadata And Markup • XML As A Metadata Lingua Franca • Dublin Core Revisited • METS • Other Metadata schemas and protocols in XML • Discussion
Types of Indexing Languages • Uncontrolled keyword indexing • Indexing languages • Controlled, but not structured • Thesauri • Controlled and structured • Classification systems • Controlled, structured, and coded • Facetted classification systems
Thesauri • A Thesaurus is a collection of selected vocabulary (preferred terms or descriptors) with links among synonymous, equivalent, broader, narrower and other related terms
Thesaurus Standards • National and International Standards for Thesauri • ANSI/NISO z39.19-1994 — American National Standard Guidelines for the Construction, Format and Management of Monolingual Thesauri • ANSI/NISO Draft Standard Z39.4-199x — American National Standard Guidelines for Indexes in Information Retrieval • ISO 2788 — Documentation — Guidelines for the establishment and development of monolingual thesauri • ISO 5964 — Documentation — Guidelines for the establishment and development of multilingual thesauri
Thesaurus Examples • Examples • The ERIC Thesaurus of Descriptors • The Medical Subject Headings (MESH) of the National Library of Medicine • The Art and Architecture Thesaurus
ERIC Thesaurus – Online http://www.ericfacility.net/extra/pub/thessearch.cfm
MESH - Online http://www.nlm.nih.gov/mesh/meshhome.html
AAT – Hierarchies (online) http://www.getty.edu/research/tools/vocabulary/aat/
Why Develop a Thesaurus? • To provide a conceptual structure or “space” for a body of information • To make it possible to adequately describe the topical content of information resources at an appropriate level of generality or specificity • To provide enhanced search capabilities and to improve the effectiveness of searching (i.e., to retrieve most of the relevant material without too much irrelevant material)
Why Develop a Thesaurus? • To provide vocabulary (or terminological) control • When there are several possible terms designating a single concept, the thesaurus should lead the indexer or searcher to the appropriate concept, regardless of the terms they start with
Preliminary Considerations • What is used now? • Continue using an existing thesaurus? • Ad hoc modification of existing thesaurus? • Develop a new well-structured thesaurus? • What is the scope and complexity of the subject field? • What kind of retrieval objects or data will be dealt with? • How exhaustive and specific is the desired description of objects?
Preliminary Considerations • The scope and complexity of the field will provide some indication of the scope and complexity of the thesaurus • It is better to plan for a larger and more comprehensive system than a smaller system that rapidly will become inadequate as the database grows • Development of a good thesaurus requires a major intellectual effort as well as clerical operations like data entry and production of sorted lists
Development of a Thesaurus • Term selection • Merging and development of concept classes • Definition of broad subject fields and subfields • Development of classificatory structure • Review, testing, application, revision
Flow of Work in Thesaurus Construction Select Sources Define Broad Subject Fields Improve Class Structure Assign codes Sort Terms into Broad Subject Fields Print Classified Index and review Select Terms Define Subfields within one Subject Field Discuss with Experts and Users Record Selected Terms Work out detailed structure of the Subject Field Select descriptors and checklist items Revise as needed Many Modifications? Select Preferred Terms Sort Terms Yes No All Subfields of Broad Subject finished? No Merge identical Terms Assign Notation Yes Merge Terms in Same Concept class Produce Full Thesaurus and Check references All Broad Subjects finished? No Review and Test Based on Soergel, pp 327-333 Yes
1. Term Selection • Select sources for the collection of terms • Prearranged Sources • Open-ended Sources • Assign codes to each source • Selection of terms • For part of pre-arranged and for all open-ended sources • Enter terms into database with all information
1.1 Kinds of Sources • Prearranged Sources • Existing descriptor lists, classification schemes thesauri • This includes universal schemes like DDC or LCSH • Nomenclatures of single disciplines • Treatises on the terminology of a field • Encyclopedias, lexica, dictionaries and glossaries • Tables of contents of textbooks and handbooks • Indexes of journals or abstracting journals • Indexes of other publications in the field
1.1 Kinds of Sources • Open-ended sources • Lists of search requests or interest profiles • Description of projects/activities to be served by the information retrieval system • Discussion with specialists in the field • Sample of documents in the field • Ask users why and how these documents relate to the field • Have documents indexed by experts in the field • Lists of titles of documents in the field • Abstracts and reviews of documents • Your own knowledge
Selection of Sources • Prearranged sources require less effort in gathering the material, and may already indicate some relationships between terms and concepts and relationships among terms • Open-ended sources can reflect current terminology and may provide more complete coverage • Choose a set of sources that are current, as complete as possible, and considered authoritative
Selection of Terms • In open-ended sources you read through the source and pick out terms (i.e. words and phrases) that might be useful in retrieval or as references to other terms • Alternatively, use keyword and phrase extraction software to create lists of terms and select from those • Transfer selected terms to the recording medium (cards or database)
Work Form – Still relevant?? From Soergel, p. 399
2. Merging and Development of Concept Classes • Sort Term DB into alphabetical order • First Round • Merge information for identical terms, possibly pulling info from additional sources • Second Round • Merge synonyms or terms in the same concept class
3. Definition of Broad Subject Fields and Subfields • Define broad subject fields and sort terms into these broad fields • Define subfields within each broad field and sort terms into these subfields • Work out the detailed structure • Select preferred terms • Merge information for terms in the same concept class • Repeat these steps • For each subfield within a broad field • And for each broad field • Until all terms have been consolidated and preferred terms selected
4. Development of Classificatory Structure • Produce preliminary version of classified index and update the working database • Improve classificatory structure • Reality check • Produce and distribute a version of the classified index • Distribute to users/experts
5. Final Stages • Review • Testing • Application • Revision