This training session introduces Knowledge Organization Systems (KOSs) and their applications especially in the Library and Information Science (LIS) field. It talks about various KOS systems including term lists, subject headings, categorization schemas, classification schemas, taxonomies, thesauri, semantic networks and ontologies. It gives many KOS examples especially those pertain to LIS such as BIBFRAME. It also discusses the process and different methods of creating categories, tag libraries and taxonomies. It was delivered to librarians and staff members in Technical Services at the University Central Florida Libraries and aimed to help catalogers better understand knowledge organization related concepts and systems in and beyond the library field

Deng, Sai

English

University of Central Florida (UCF): STARS (Showcase of Text, Archives, Research & Scholarship)

University of Central Florida STARS Faculty Scholarship and Creative Works 3-24-2021 Knowledge Organization Systems & Their Applications Sai Deng University of Central Florida, sai.deng@ucf.edu  Part of the Archival Science Commons, and the Cataloging and Metadata Commons Find similar works at: https://stars.library.ucf.edu/ucfscholar University of Central Florida Libraries http://library.ucf.edu This Other Presentation is brought to you for free and open access by STARS. It has been accepted for inclusion in Faculty Scholarship and Creative Works by an authorized administrator of STARS. For more information, please contact STARS@ucf.edu. STARS Citation Deng, Sai, "Knowledge Organization Systems & Their Applications" (2021). Faculty Scholarship and Creative Works. 966. https://stars.library.ucf.edu/ucfscholar/966 Knowledge Organization Systems & Their ApplicationsSai Deng, Metadata Librarian, University of Central FloridaTERMSHow are these terms related? How to define them? How to group them?Cover image: https://hangingtogether.org/?p=7135Authority files Glossaries Dictionaries Gazetteers ClassificationCategorization Subject HeadingsClassification Schemes TaxonomiesCategorization SchemesThesauri Semantic Networks Ontologies Term ListsRelationship ModelsKOSTerm Lists• Authority files• Glossaries• Dictionaries• GazetteersClassifications and Categories• Subject headings• Classification schemes• Taxonomies• Categorization SchemesRelationship Lists• Thesauri• Semantic networks• OntologiesHodge’s classification of KOS (2000)KOS: Knowledge Organization SystemsKOSZeng's classification of KOSs (2008)• Term Lists• Glossaries/Dictionaries• Synonym Rings…• Metadata-like Models• Authority Files…• Classification & Categorization• Subject Headings• Categorization schemes• Taxonomies• Classification schemes• Relationship Models• Thesauri• Semantic networks• OntologiesGlossaries§ Glossary of Library & Information Science https://www.librarianshipstudies.com/2015/04/glossary-of-library-information-science.html§ Wikipedia. Glossary of library and information science. (see right) https://en.wikipedia.org/wiki/Glossary_of_library_and_information_scienceDictionary§ Cambridge Dictionary. Books & parts of books. SMART Vocabulary: related words and phrases. § Words§ Group of words§ Hierarchy not set up§ Relationships are not defined§ Related words (*new feature?)§ see right graph(https://dictionary.cambridge.org/us/topics/thinking-dreaming-and-ideas/philosophy/)Subject headingsLibrary sciencehttp://id.loc.gov/authorities/subjects/sh85076723LCSHSearch LCSH: https://id.loc.gov/authorities/subjects.htmlLC Linked Data Service: Authorities and Vocabularieshttps://id.loc.gov/• Subject headings: vocabularies of controlled terms, which represent the subject of items in a collection, and include rules to combine such terms into compound headings. –ISKO Encyclopedia of Knowledge Organization• Subdivisions: topical, geographic, chronological, form• E.g., Medical Subject Headings (MeSH), Library of Congress Subject Headings (LCSH)• Hierarchical• Broader terms• Narrower Terms• If equivalence and associative relationships are added, it turns into a thesaurusFASTFAST (Faceted Application of Subject Terminology)• Eliminated hierarchy in LCSH; • User friendly; no need to construct headings;• Search FAST: http://fast.oclc.org/searchfast/• FAST Dataset Download:https://www.oclc.org/research/areas/data-science/fast/download.htmlF A S TCategorization Schemes • Categorization schemes: loosely assembled grouping schemes. – ISKO Encyclopedia of Knowledge Organization• Category: Library science (Wikipedia, see right)https://en.wikipedia.org/wiki/Category:Library_science(Category: Library science)https://en.wikipedia.org/wiki/Outline_of_library_science (Wikipedia article: Outline of library science)Classification Schemes§ Classification schemes: hierarchical and faceted arrangements of numerical or alphabetical notations, which are used for representing broad topics and usually conceived as universal systems (i.e. covering all fields of knowledge). – ISKO Encyclopedia of Knowledge Organization§ E.g., Dewey Decimal Classification System (DDC)§ 10 classes§ Hierarchical; how many levels?§ Example§ 600 Technology (Applied sciences) § 630 Agriculture and related technologies § 636 Animal husbandry § 636.7 Dogs § 636.8 Catshttps://www.oclc.org/content/dam/oclc/webdewey/help/600.pdfhttps://www.oclc.org/content/dam/oclc/webdewey/help/000.pdfLC Classification Outline§ LC Classification§ 21 classes§ Subtopics in alphabetical lists (letter + number)§ Hierarchical, but some subtopics are alphabetical§ Allow for more call numbershttps://www.loc.gov/aba/cataloging/classification/lcco/lcco_z.pdfTaxonomy• Taxonomy, in a broad sense the science of classification, but more strictly the classification of living and extinct organisms—i.e., biological classification.               -- Britannica• taxis (“arrangement”) • nomos (“law”), Greek word• Taxonomies (historically associated to biological classifications): any ordered grouping of items based on particular features.                      – ISKO Encyclopedia of Knowledge Organization (https://www.isko.org/cyclo/kos)Linnaean Classification System: Classification of the Human Species. -- LibreTextsTaxonomy• Taxonomy• Hierarchical system• Grouped by shared properties/ key features• No equivalence or associative relationships defined Taxonomy§ https://www.inphoproject.org/taxonomyInPho: The TaxonomyTaxonomy in Digital Commons§ Disciplines: Digital Commons Three-Tiered Taxonomy of Academic Disciplines https://bepress.com/reference_guide_dc/disciplines/§ https://bepress.com/wp-content/uploads/2016/12/bepress_Disciplines_taxonomy.pdf (Taxonomy PDF)Thesauri§ Thesauri: controlled and structured vocabularies, display hierarchical, associative and equivalence relations among terms/concepts. –ISKO Encyclopedia of Knowledge Organization§ E.g., Art and Architecture Thesaurus (AAT), ERIC Thesaurushttps://www.getty.edu/research/tools/vocabularies/aat/Semantic Networks§ Semantic networks: systems where terms/concepts are modelled like in a network of variable relationship types; richer than thesauri in defining categories or semantic types and semantic relations. – ISKO Encyclopedia of Knowledge Organization§ Expressed in semantic triples§ E.g., Wordnethttps://en.wikipedia.org/wiki/Semantic_networkSemantic Networks§ Semantic networks§ Expressed in semantic triples§ E.g., Wordnet § https://wordnet.princeton.edu/§ an open-access lexical-semantic data base§ Nouns, verbs, adjectives and adverbs are grouped into sets of cognitive synonyms (synsets)§ Synsets are interlinked by means of conceptual-semantic and lexical relationshttps://openscience.com/wordnet-open-access-data-in-linguistics/Ontologies§ Ontologies: formal, explicit specification of a shared conceptualization (Gruber 1993). § Usually consist of complex relations between entities, include rules and axioms which support logical reasoning. Conceptual vocabularies with properties and instances.  – ISKO Encyclopedia of Knowledge Organization§ e.g., Gene Ontology (GO), PREMIS OWL Ontologyhttps://www.loc.gov/standards/premis/ontology/pdf/owl-ontology-slides-feb22-2018.pdf (PREMIS Ontology data model)Ontologies§ Ontologies§ e.g., BIBFRAME§ BIBFRAME (Bibliographic Framework) § Linked data modelhttps://www.loc.gov/bibframe/docs/bibframe2-model.html (BIBFRAME 2.0 Model)Ontologies§ BIBFRAME§ http://id.loc.gov/ontologies/bibframe/§ Classes§ + Work§ + Instance§ Item§ + Agent§ + Person§ Properties§ Content§ hasInstance§ Subclass§ Text§ …https://id.loc.gov/ontologies/bibframe.html#c_Work (BIBFRAME 2.0.1: Work)Ontologies§ BIBFRAME§ A record in BIBFRAME format in Alma<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bf="http://id.loc.gov/ontologies/bibframe/" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:bflc="http://id.loc.gov/ontologies/bflc/" xmlns:madsrdf="http://www.loc.gov/mads/rdf/v1#"><bf:Work rdf:about="https://open-na.hosted.exlibrisgroup.com/alma/01FALSC_UCF/bf/entity/990376376830606596#Work"><bf:adminMetadata>…<bf:language><bf:Language rdf:about="http://id.loc.gov/vocabulary/languages/eng"/></bf:language><bf:genreForm><bf:GenreForm rdf:about="http://id.loc.gov/authorities/genreForms/gf2014026039"><rdfs:label>academic theses</rdfs:label></bf:GenreForm><bf:agent>…<rdf:type rdf:resource="http://id.loc.gov/ontologies/bibframe/Person"/>…<bflc:name00MarcKey>1001 $aRoberts, Donna Anne$eauthor</bflc:name00MarcKey><rdfs:label>Roberts, Donna Anne</rdfs:label></bf:agent>…<bf:title><bf:Title><rdfs:label>Personality and life crisis factors in nurse drug users</rdfs:label><bflc:titleSortKey>Personality and life crisis factors in nurse drug users</bflc:titleSortKey><bf:mainTitle>Personality and life crisis factors in nurse drug users</bf:mainTitle></bf:Title></bf:title>…Creating Categories/Tags/Taxonomies§ Project purpose, needs assessment, creators, users§ Literature research, information gathering§ Survey existing term lists, keywords/tags, subjects, taxonomies, thesauri etc.§ Research existing projects, examples• Books and their indexes, Table of Content• Documents• Databases• Encyclopedia • Glossaries• Web resources• Search logs• Users• ExpertsWhere to collect terms?§ Design and building§ To decide on taxonomy structures§ Hierarchies§ Facets§ Organize terms: § Sort into big categories (top terms);§ Start from 10-20;§ Analyze gaps, modify/add/deleteMaterials in this section is mainly from Taxonomies for Indexing: A Hands-On Approach (Workshop), by Hlava, Marjorie, Access InnovationsCreating Categories/Tags/Taxonomies§ Term structure and relationships§ Hierarchical relationships: broader, narrower terms (BT, NT)§ Generic relationship (genus-species), e.g., type§ Whole-part relationship§ Instance relationship§ Creating hierarchies: depth, breadth, arrangement, grouping categories§ Polyhierarchical relationship: can have multiple broader termsCreating Categories/Tags/Taxonomies§ Equivalence relationships:§ Preferred term (thesaurus notation: Use)§ NonPreferred term (thesaurus notation: Used for, UF)§ When to use: synonyms, slang, lexical variants (spelling, grammar variations)§ Scope notes (SN): indicate meaning, restriction, range, instruction, use only as needed§ Associative relationships: related terms (RT), cousins§ Terms related conceptually but not hierarchically, not equivalent § Term and related terms both used for indexing• Museums• Art museums• Natural history museum• Children’s museums• METS• The Metropolitan Museum of Art• Curators• PaintingsHow are these terms related?Creating Categories/Tags/Taxonomies§Facets§Use semantic categories§Mutually exclusive§Built for Faceted navigation§Examples: §Art & Architecture Thesaurus (AAT) facets§ Associated Concepts, Physical Attributes, Styles and Periods, Agents, Activities, Materials, Objects• Gardens• America gardens• Cottage gardens• Chinese gardens• Bird gardens• Butterfly gardens• Tropical gardens• Historical gardens• Monet’s gardenPropose facet indicators and group these terms into facetsCreating Categories/Tags/TaxonomiesCreating categories/tags/ taxonomies: More about terms§ More about terms§ Term format§ Short and simple; § Grammatical issues§ Nouns and noun phrases (e.g., adj. + n. – Art history, n. + prep. +n – History of Art)§ Verbs: gerund form -- Fishing§ Adjectives: rare; can be combined with another term§ Adverbs: no, except as part of a proper name§ Initial articles: no, except as part of a proper nameCreating categories/tags/ taxonomies: More about terms§ Singular and plural forms§ Plural form for count nouns: animals, books§ Singular form for mass nouns: oxygen§ Exceptions: unique entities -- singular, user warrant – plural/singular (e.g., fishes)§ Spelling§ Alternative spelling in the same taxonomy (if needed), NonPreferred Term for secondary spelling§ Abbreviations and acronyms§ Use only when full form is rarely seen –DNA, LASER§ Alternative becomes NonPreferred Term§ Be consistentCreating categories/tags/ taxonomies: More about terms§ Capitalization§ Use all lower case, except for: Initialisms, Proper names, Trade names etc.; differs in practice§ Punctuation: parentheses (use to disambiguate), hyphens (only when necessary), diacritical marks (keep if possible), apostrophes (keep for possessive case)§ Compound terms vs. factored terms§ Compound terms (precoordinated, put together at indexing stage)§ Factored terms (postcoordinated, put together at search stage)§ To factor or not: is each factor a single concept? Is each factor in your thesaurus/list? Will factoring be confusing? (e.g., Philosophy library)§ Review, test and revise; write policies and guidelinesAutomatic Tag Library/ Taxonomy Construction§ Use software to support creation§ Human/automatic/hybrid categorizer§ Content management systems provide ways of adding and presenting categories/tags/taxonomies (e.g., Wordpress), subjects and tags (e.g., Omeka)§ Thesaurus software§ MultiTes, Data Harmony Thesaurus Master, Synaptica etc. (Commercial)Automatic Tag Library/ Taxonomy Construction§ Creation of a Tag Library§ Folksonomy: users provide tags to online resources, rich/diverse, flat, lack of semantic relations§ Tags: can be concepts, categories, facets, entities; can define time, space, concepts, characters...§ Tag Library helps users to apply tags and classify documents/resources§ Methods: Using semantic dictionary to compare and standardize tags, user annotation control, tag recommendation, optimum selection of user tags§ Auto-categorization§ Preprocessing, training set, test set, tag cleaning, tag standardization§ Algorithms: Vector Space Model, Naive Bayes, Decision Tree, K-means…ContactSai Deng Metadata LibrarianUniversity of Central Florida Libraries sai.deng@ucf.eduThank you!

Knowledge Organization Systems & Their Applications

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Knowledge Organization Systems & Their Applications

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