Classification of Resources III: Research Library Schemes

Classification Definitions

• Classification - the act of organizing a body of knowledge into a systematic order
• In libraries: the systematic arrangement by subject of books and other materials on shelves, or of catalog and index entries, in a manner that is most useful to those who read or those who seek a definite piece of information.
• Shelving device
• Organization device

Characteristic of a Classification System

• Inclusive and comprehensive
• Systematic
• Flexible and expansive (i.e. hospitable)
• Employ terminology that is clear and descriptive
• Indexed

Classified Shelf Arrangement of Books

• Collocating objective: bringing like things together on library shelves:
• Subject criterion: But what about books on multiple topics?
• Author criterion: But what about books by multiple authors?
• Need a system for the unique identification of resources in open stack libraries through the use of notational systems and call numbers.

Notational Systems

• Notation marks (aka "classmarks") represent a book's subject class, including its relation to other subject classes in a classification scheme.
• Most common types:
• Pure - e.g., DDC employs Arabic numerals
• Mixed - e.g., LCC employs an alpha-numeric notation
• Mnemonics:
• Repeating class notation patterns throughout classification
• This technique is also used in the MaRC system

Shelf Arrangement and Sub-arrangement

• Library classification schemes provide:
• A systematic method for shelf arrangement in open stack libraries
• A systematic method for sub-arrangement within each class
• To accomplish this goal, catalogers synthesize (i.e. create) class numbers to represent the subject of a book
• This process remains transparent to the user (i.e. the user is more interested int he fact that books are collocated on the shelf rather than how the numbers were determined.

Cuttering to Create a Call Number

• Used to create call numbers (UIs) for individual library collections.
• Provides the link between the surrogate record an the actual item in the collection
• Provides for both subject and non-subject (e.g. author) oriented sub-arrangement in open stack libraries. 
• After the class notation is determined, then the cuttering process begins.
• Use a cutter table:
• There may be more than one cutter table floating around!
• Cuttering is a flexible process; only use table as a guide
• Steps for cuttering:
• Determine the first letter of main entry (most often taken from 100 tag; but could be 245 tag)
• Use number associated with second letter of main entry
• Add additional numbers until call number is unique 
• Add date
• You may have 1 or 2 cutter numbers, BUT you may never have 3.
• In the LCC, cuttering instructions are given in the schedules:
• Assists in topical, geographical and other non-main entry-based sub-arrangement
• Occasionally, this involves double cuttering, thus precluding the use of main entry-based cutters. 

LCC - General Points

• Mixed notations
• All letters are not used (reserved for expansion)
• Subject specialists develop and maintain the class schedules, rather than centralized editors as is the case with the DDC.
• Designed to meet the needs of the collection of the Library of Congress.
• Based on literary warrant: Schedules developed with reference to what has been published. 
• Hierarchical; however, NOT reflected in notation. 
• LCC Classification outline:
• Divided into main classes according to academic discipline or areas of study and then into sub-classes representing branches of those disciplines
• Larger range of letters for History (C-G) and Social Sciences (H-L)
• Numericals used range from 1-9999 with frequent gaps

LCC is Essentially Enumerative

• Aspects of subjects are explicitly provided for (i.e. enumerated) in the schedules:
• More "pigeonholes" created in advance to represent very specific topics and topical aspects.
• However, tables are also used to synthesize complex class notations (not as often as with the DDC)
• As an enumerative classification, the LCC schedules are more voluminous than many other schemes:
• 50 volumes
• 10,000 pages.

Consistent Structuring: Martel's 7 points

• Initially, Charles Martel provided basis for consistent structuring across divisions:
• General forms: periodicals, societies, dictionaries, etc
• Theory, Philosophy
• History
• Treatises, General works
• Law, Regulations, State relations (now relocated to K)
• Study and teaching
• Special subjects and their subdivision from general to specific

LCC has Many Editors 

• LCC has been referred to as a series of special classifications (though compare with NLM)
• However, individual LCC schedules are structured identically:
• Preface
• Broad outline
• Detailed outline
• The schedule, itself
• Any necessary, auxiliary tables
• Detailed index

Revising LCC with Topic Subdivisions

• Constitute the bulk of the expansion of classes and subclasses
• EXAMPLE: Women Suffrage in U.S. (JK1880)
• Note geographical subdivision of "Women's Suffrage. Women's right to vote" - in this case, cutter by location
• Also note geographic subdivision under subtopic "Biography"

Procedures for Revision and Expansion

• Proposals for changes originate with LC catalogers:
• Anomalies
• New topics
• Some methods for expansion:
• Using unused letters (I, O,W, X and Y)
• Adding a third letter (or sometimes a fourth)
• Extending existing numbers decimally
• Expanding use of cuttering

General Steps for Classifying with LCC

• Because of disciplinary aspects of LCC, first check for appropriate schedule to match subject of item in hand and then determine the best class number within the selected schedule. 
• Class item in hand with similar works:
• Consult existing records
• Consult class numbers mapped from assigned LCSH
• Consult LCC outlines

Classifying General Works

• Under most numbers with subdivisions, a number is designated for "general works."

Classifying Works on Single Topics

• Always use the most specific class number that is co-extensive with the subject matter of the work.
• If no co-extensive number exists, then the next appropriate broader number should be used. 

Classifying Works by Time Period

• For works treating a topic with regard to a particular time period. For those works spanning two periods use earliest. 
• DC History of France:
• DC725 Earliest to 1515
• DC727 16th century
• DC729 17th-18th century
• DC731 1789-1815
• DC733 1815-1870
• DC735 1871-1914
• DC736 1914-1921
• DC737 1922-

Multi-Faceted Single Topic Works

• Works covering multiple facets of a single topic.
• If available, use a class number representing all facets:
• Idea of the English landscape painter: genius as Alibi in the eary ninetheenth century by Kay Dian Kriz
• ND1354.5.K75 1997
• If number covering all facets is not available, go with the emphasized or more prominent facet:
• Elizabethan mineatures, by Carl Winter
• ND1337.G7.W5 1955

Classifying Works on Multiple Topics

• A work on two or three topics treated equally:
• Use number for the topic treated first
• QD412.A7 C53 1994 - Chemistry of organic arsenic, antimony, and bismuth compounds
• A work on four or more topics:
• Use a general number that encompasses all numbers chosen
• RA566.3.C48 1992 - Changing U.S. health care; a study of four metropolitan areas

Classifying Works with Phase Relations

• A work covering the relationship between two topics is classed in the most specific number covering the relationship:
• QK46.5.H85 P66 2001 - Botany of desire; a plant's eye view of the world
• QK46.5.H85 - Botany > Human-plant relationship
• A work covering the influence of one topic on another is classed with the topic being influenced:
• LA2317.T8 M3 1899x - Henry Tutwiler and the influence of the University of Virginia on education in Alabama
• LA2317.T8 - History of U.S. Education > Individual biography

Cuttering for Geographical Aspects

• Geographical cuttering option is often available in parts of the schedules:
• Use either general or specialized cutter table
• EXAMPLE:
• Visual Arts Education:
• N353.A-W - General works in Visual Arts in U.S.
• N354.A-Z - General works in Visual Arts in a state
• N355.A-Z - General works in Visual arts in a city

Cuttering Sub-topics - "Reserve Cutters"

• Cuttering by topical aspect is also sometimes available - this is termed "reserve cuttering"
• Style, Composition, Rhetoric:
• P301 - General Works
• P301.3.A-Z - General Works by region or country
• P301.5.A-Z - Special Aspects A-Z
• P301.5.134 - Idioms
• P301.5.P73 - Propoganda

Verbal Subject Analysis III: Webpage Databases (a.k.a. "Search Engines")

Human vs. Automatic Indexing

• Both are related to the subject analysis of information resources.
• Human indexing is used to describe the subject analysis of various periodical databases.
• Automatic indexing is a term used for the subject analysis operations by the computer algorithms of various webpage databases (a.k.a. search engines).
• Research from the 60s-80s were trying to get a computer to calculate what articles were about. The most frequent words, articles like a, an, the, etc., don't really tell you much about the article, neither do the least used words. The key is finding the sweet spot based  on what the author usually writes about.

Why Webpage Database?

• It is always important to know the documentary unit of an information database. 
• The adjective associated with database is always a cue to the documentary unit. 
• Webpage databases are informational databases in which a webpage is the documentary unit. 
• They are also known as search engines and discovered databases.

Analysis of Websites and their Structure

• What are webpages? What are websites? Webpages:Websites as pages:books
• Standards (or lack thereof) for the authoring of web sites and webpages
• HTML and other markup languages
• Editors
• What are the implications of the lack of authoring standards for web-based information resources?

Location of Webpage Subject Metadata

• In webpage headers: For individual webpages, subject metadata can be created by authors and included in HTML headers.
• In separate metadata record databases:
• Subject metadata can be created by intermediaries using Dublin Core schema
• In search engines, subject metadata is inferred "automatically" by computer algorithm.

Search Engine Questions

• For greater understanding we need to be able to answer:
• Why do search engines produce different results the exact same query?
• What is the principle for ranking the display of search engine records in response to a query?

The Term "Search Engine"

• The term has become the common designation for webpage databases, However, in actuality, webpage databases have three parts:
• Spidering/crawling software to collect webpages.
• Indexing software to build the index of surrogate records.
• Retrieval software to facilitate retrieval of surrogates.

Automatic Indexing in Context

1. Obtain information resource - spidering/crawling
• Steps for spidering/crawling:
• Computers owned by search engine retrieve documents by clicking on all hyperlinks on each retrieved webpage
• Determination is made whether a webpage needs to be indexed (because it is new) or reindexed (if it has already been indexed)
• Determination is made whether reindexing is warranted
• New webpages and those meeting criteria for reindexing are then placed in the indexing queue
2. Describe information resource in surrogate record - read off webpages by indexing software
• Left Side elements must be inferred by searcher:
• Examine structure of retrieved records
• Examine advanced search interface
• Element sets are not standard, i.e., they will vary across search engines.
• Right Side Content:
• What is the source for the content?
• Authority control?
3. Subject analyze information resource in surrogate record - indexing software:
• Verbal - inferred by computer algorithm
• Classification - inferred by computer algorithm
• Subject Indexing in Search Engines
• The subject fields of webpage surrogate records include the words that describe what the webpage is about. 
• Right side subject content is inferred through the application of proprietary algorithms.
• Subject terms added to surrogate records are weighted:
• Doc #1: SU = dogs (.99); breeding (.87);dachshund (.30)
• Doc #2: cats (.92); dogs(.44); dachshund (.03)
• The weights are computed by proprietary algorithm.

Retrieval from Search Engines

• Unlike bibliographic databases, in which the ordering of retrieved surrogate records is reverse chronological, search engines use a relevance-based ranking.
• The search engine component of a search engine takes the entered query and compares it to the terms to the index.
• The documents that are retrieved first are those that contain a higher "relevance" score:
• Doc #1: SU = dogs (.99); breeding (.87);dachshund (.30)
• Doc #2: cats (.92); dogs(.44); dachshund (.03)
• "dog" query would rank document #1 ahead of document #2
• "breeding" query would rank document #1 ahead of document #2
• "cats"query would rank document #2 ahead of document #1

How are Subject Weights Calculated?

• Conventional methods (Dating from the 1950s) for automatically inferring what a document is about include the following three techniques:
• Frequency of word occurrences
• Location of words occurrences
• Size of word occurrences
• In the web era, however, these techniques did not scale well to meet the needs of databases containing billions of records:
• Could facilitate retrieval of relevant documents, but could not distinguish between "good" and "bad" documents.
• Were also subject to manipulation by authors desiring higher search engine retrieval (spamming)

Two responses to Early Indexing Failure

• Yahoo! era (late 1990's)
• Human indexing (website directories)
• More discussion during lectures on classification. 
• Google era (since 1999)
• Additional criteria introduced to infer aboutness, e.g.,;
• $ - paid submissions, such as Alta Vista
• Quality - PageRank algorithm of Google

Google Approach to Authomatic Indexing

• Issue addressed by Google concerns the quality problem: How to cause the "best" documents to rise to the top of a set of retrieved webpages.
• Solution concerns identifying additional criteria to include int he subject weighting algorithm.
• Google maintains additional metadata elements for each surrogate record in its index of webpages:
• How many other webpages link to a given webpage
• The more webpages (i.e. linkers) a dachshund webpage has poiting to it, the more quality it has.
• This factors into the weight assigned to the "dachshund" descriptor inthe subject field of its surrogate record
• Who are the linkers
• Those linkers that have a higher quality rank are given more weight than those linkers with a lower quality rank.

Verbal Subject Analysis II: Periodical and Other Databases

Subject Cataloging vs. Indexing

• Both are related to the subject analysis of resources. 
• Subject cataloging  is a term used for the subject analysis operations in library cataloging. 
• Indexing is a term generally used for the subject analysis operations in various other resource organization contexts, including periodical databases and search engines. 

Brief History of Periodical Indexes

• Around the turn of the 20th century, the library community decided not to add article citations to the catalog. 
• This development led to the growth of the commercial indexing industry. 
• The result of this has been:
• Split files
• Fees for licensing database content
• Difficulty fulfilling Cutter's 2nd objective

Analytical Cataloging

• Analytical cataloging techniques are needed in order to provide access to the component parts of composite information resources, most commonly:
• Book chapters
• Proceedings articles (usually of academic meetings)
• Journal articles
• Definition from AARC2: Analysis is the process of preparing a bibliographic record that describes a part (or parts) of an item for which a comprehensive entry is made.

Analytical Cataloging Techniques

• Complex entries made within the record of composite work [cheap]:
• Analytical added entries:
• Use 740 tag for second of two works mentioned in title of item
• Note area for comprehensive entry of larger work:
• Use 505 tag for structured display of table of contents.
• Separate records created for the component parts of composite works ("In" Analytics)[expensive]:
• Use 773 to trace the component part record to parent record

Analytical Access to Journal Content

• Decision to not provide analytical access to journal content (i.e. directly to articles) was because of the expense:
• Excessive number of records would have to be created.
• Additional authority work would need to be done.
• As a result, through the 20th century, cataloging and periodical indexing/bibliography creation techniques evolved separate approaches. 

Overview Comparison

• Catalog
• Authority work
• Cataloging records represents the holdings of a library
• Periodical indexes:
• Subject indexes are extensive topical bibliographies (often include books and book chapters, too), usually covering large swaths of "territory"
• Domain-wide indexes (e.g. Index Medicus) attempt to capture an entire discipline (may include book chapters, too)
• No single library could ever own all items referred to in exhaustive bibliographies/indexes, thus leading to ILL (inter-Library Loan) services
• Authority work nonexistent (except controlled vocabularies)

Surrogate Records in Periodical Databases

• As is the case with library catalogs, periodical databases contain structured surrogate records. 
• This structuring is fairly consistent across periodical databases, both in terms of stored records (two part metadata model holds) and how records are displayed
• There is some authority control at work, but not in ways that you might think.

Collocation in Periodical Databases

• By subject - what about vocabulary control?
• By author - what about authority control?
• By journal - what about authority control?
• By language
• By publication type
• By date
• Etc., etc., etc. 

In all Collocation Contexts: MATCH!

• EXAMPLES:
• Indexers → author name → match ← author name ← users
• Indexers → journal name → match ← journal name ← users
• Indexers → vocabulary → match ←vocabulary ← users

Inverted File Structures

• How surrogate records are physically stored in the index of a database.
• Each surrogate record has a unique identifies (also called a pointer)
• Each word and phrase of the index has a record in the index; each record contains the UI for each surrogate record that contains that word or phrase:
• Dog: 235, 527; 5,345,672; 117,127,923
• Cat: 127; 2,753; 917,538; 327,543,238

How is Surrogate Information Stored?

• Print periodical indexes and bibliographies. 
• Online periodical databases:
• Examine sample database record for left side metadata elements
• Examine advanced search interface
• EXAMPLES:
• PubMed MEDLINE
• Library Literature
• ALWAYS KNOW THE START DATE OF YOUR ONLINE PERIODICAL DATABASE!
• Manual search of the literature is often needed for exhaustive searches
• Retrospective conversion of print indexes to online is not generally undertaken by database providers due to expense. 

Periodical Database Characteristics

• They usually hold more records than a library catalog.
• Information resources (i.e. journal articles) contain less information than the info resources in library catalogs and there are no detailed secondary navigation aids such as book indexes.
• More fields (i.e. left side elements) available for search word qualification.
• Important to distinguish database producing companies/organizations from database interface companies:
• Some companies/organizations provide both (e.g. PubMed MEDLINE)
• Other companies provide interface services, such as Dialog or EBSCO.

User Interfaces (UI) in Periodical Databases

• Common UIs employed in periodical databases:
• ISSN - uniquely numerical identification for individual serial publications
• Internal numbering systems within a periodical database, such as the PMID in MEDLINE (for known item searches)
• The most important UI is pre-Web and that is the "Address" of an article in the bibliographic universe (also known as the citation data) - also good for known item searches:
• Journal name
• Volume number (in some journals, the issue number also)
• First page number of article. 

Authority Control in Periodical Databases

• Titles - not controlled
• Authors - somewhat controlled:
• Indexers generally enter author name from the information resource
• Control rests with periodical editors, who often have policies on author names that may be different than other periodical editors
• Subjects - controlled:
• Controlled vocabularies are imposed across periodical  and over time by indexers
• However, subject searching is still subject to the problems associated with the "Great Pop vs. Soda Controversy"

Author Indexes in Periodical Databases

• Examine how author data is entered into surrogate records:
• Generally taken from the information resource in hand
• PubMed MEDLINE is an exception
• Some databases will provide lists of author names from which to choose:
• Indicator of authority work?
• Library Literature is an example
• Subject Indexing in Periodical Databases
• Indexing approach is "information access," therefore depth indexing is the general rule. 
• Indexers index to the most specific, therefore, hierarchies remain important in controlled vocabularies. 
• Pre-coordination and post-coordination are important concepts.

Subject Indexes in Periodical Databases

• Depth Indexing:
• General goal is to provide subject access to the information contained in an article.
• However, this practice is not universal across database producers; therefore, determine the depth of indexing of the database you are searching by examining existing records
• Be aware of the lag time related to subject indexing of articles

Management of Controlled Vocabularies

• Homonymy:
• Addressed by domain specificity of most periodical databases
• Various forms of qualification are used, including parenthetical, hierarchy, and scope notes. 
• New concepts:
• Literary warrant is generally not employed in periodical database vocabularies
• New terms are added after new concepts have established themselves in the literature
• This poses a challenge if you are searching at a "research front" (may need to perform a keyword search strategy of the abstract field)

Some Vocabularies for Periodical Databases

• MeSH
• NLM MeSH Browser
• PubMed MeSH Database
• Library Literature
• EBSCO interface

Other Controlled Vocabulary Contexts

• Getty Museum (the folks who created ULAN)
• Subject Terms (search "cubist")
• Thesaurus of Geographic Names (compare "Soviet Union" and "Russia")
• Dublin Core permits various subject vocabularies:
• Specification of subject element
• DC Vocabulary Qualifiers

Web Content for Human Indexing

• A-Z Web Indexes:
• MEDLINEPlus Topics A-Z (organizes access to Web-based information for patients)

Indexing in Context

1. Obtain information resource
2. Describe information resource in surrogate record
3. Subject analyze information resource in surrogate record:
• Verbal 
• Classification

Article Indexing Process

• Two steps:
• Analyze information resource to generate list of candidate concepts that describe its subject content
• Translate those concepts into the controlled vocabulary of the database
• ISO Standard for article indexing - special attention should be paid to certain sources of information:
• Title
• Abstract (when provided)
• Introduction; opening and concluding paragraphs
• Illustrations, diagrams, etc and their captions
• Words or groups of words that are underlined, bold, etc.

Verbal Subject Analysis I: Library Subject Headings

Subject Cataloging versus Indexing

• Both are related to the subject analysis of resources.
• Subject cataloging is a term used for the subject analysis operations in library cataloging. 
• Indexing is a term generally used for the subject analysis operations in various other resource organization contexts, including periodical databases and search engines.

Subject Analysis Jargon

• Documentary unit - depends on type of retrieval tools
• Monograph - in library catalog
• Chapters - i some library catalogs and periodical databases
• Articles - in periodical databases
• Paragraphs - in back of book indexes and search engines
• Web sites - in website directories
• Web pages - in search engines
• Indexable matter - amount of text for each info resource that is subject analyzed
• Exhaustivity - how many subject terms to assign to a surrogate
• Specificity - how specific are the subject terms for a surrogate

Some Subject Analysis Concepts

• Pre-coordinated vs. post-coordinated terms. 
• Collocation by subject
• Computer "matching":
• Indexers > vocab > match < vocab < users
• The computer is getting a little smarter (e.g. misspellings)

Issues that Vocabularies Must Address

• Growth of knowledge over time (i.e. the introduction of new concepts to a domain)
• Terminological changes to existing concepts over time:
• Maintaining new headings (i.e. the introduction of new terms to represent existing concepts in a domain)
• Maintaining new entry terms (i.e. the introduction of new terms to represent existing concepts in a domain) [e.g. Quaddafi, Kaddafi, Gaddafi, etc.]
• Techniques for managing synonymy over time.
• Techniques for managing homonymy over time (i.e. disambiguation)

Library of Congress Subject Headings

• 
  
• Begun in 1898 with Charles Cutter and his plan for a dictionary, rather than a classified, catalog:
• Direct access to subject in alphabetic list
• Easier for end-users to look up subjects
• It is currently in 5 volumes (the "Reds"), and over 245,000 headings (and countless entry terms).

Earlier Version of LCSH Subject Headings

A Later Version of LCSH Subject Headings.
As you can see, the growth of knowledge requires and expanse of entries, and thus the collection has grown from a set of 4 (picutred above) to a set of 6.

Literary Warrant in LCSH

• New headings are generated based on need as indicated by the emergence of new subjects in the published literature that has been selected for library collections. 
• Therefore, the LCSH is NOT a comprehensive subject headings list:
• It represents what the LC collections holds
• HOWEVER, the LC collection holds a LOT. 
• Grows by accretion over time as new headings are added that match what authors are writing about over time.

LCSH Structural Elements

• One-word subject headings (nouns).
• Two-word subject headings (nouns and adjectives):
• normal word order
• inverted word order
• More than 2 word subject headings: Use of conjunctions and prepositional phrases. 
• Parenthetical qualifiers.
• BT, NT, Use, UF, RT, and SA (the latter defined ad "general 'see also; relationships")

LCSH  Features

• Derived from book cataloguing of US Congress.
• Established over a long period, with inconsistencies between subject areas because of major vocabulary management changes introduced in the 1970s.
• Becoming polyhierarchical (i.e. "Fairy Poetry" is a NT of "Poetry" and "Fairies")
• Extensive guidance, including online subscription resources
• American spelling/usage

Hierarchical Relationships (BT and NT)

• Only immediate relationships are listed; user must "ride the rails" to locate desired specificity. 
• Polyhierarchy is used (i.e. multiple broader terms for a subject heading).
• Some BT and NT terms may not be listed in subject heading if they are adjacent alphabetically in list. 

Equivalence Relationships (Use and UF)

• Synonyms: feline heartworm USE Dirofilaria imitis
• Variant spellings: dog USE dogs
• History notes: AIDS UF Acquired Immune Deficiency Syndrome 
• Inverted multi-word headings: educational psychology UF psychology, educational

Associate Relationships (RT)

• Specific reference to other subject headings that are related by association. 
• These related subject headings are topics that are associated in ways other than hierarchically. (e.g. Birds and Ornithology (the study of birds)

Subdivisions in LCSH

• Subdivisions qualify (i.e. further specify) the meaning of subject heading in non-hierarchical ways
• Some subdivisions are editorially pre-coordinated with their subject headings.
• Some subdivisions are not  editorially pre-coordinated; rather, they are free floating:
• Free floating subdivisions have rules for their applications, and are connected via these rules. 
• These free floaters were a major improvement to LCSH and were introduced in the 1970s.  
• Headings are always first, followed by subdivisions.

Subdivision Types:

• Topical subdivisions:
• Qualifies meaning of a subject heading according to a specific subtopical aspect.
• Chronological subdivisions:
• Limits a subject heading to a particular time period.
• Geographic subdivisions:
• Indicated by "May Subd Geog" or disallowed by "Not Subd Geog" 
• Couls be inverted: Massachusetts -- History
• Form subdivisions:
• Not topical, rather used to indicate what a work is, e.g. abstracts, dictionaries, handbooks, pictorial workds
• Added at end of subdivision

Subdivision Type Examples

• Editorially pre-coordinated: Those created by LCSH editors for use under a partiular heading:
• EXAMPLES
• Dogs -- Anatomy
• United States -- History -- 1815-1861
• Free-floating: Those that may be used under heading without being established editorially:
• EXAMPLES
• Biochemistry -- Congresses [form subdivision]
• New York (N.Y.) -- Buildings, structures, etc. [topical subdivision]

General See Also Relationships (SA)

• A blanket reference to a group of related headings. 
• EXAMPLE
• Economic history -- "Subdivision economic conditions under names of countries, cities, etc., and under classes of persons and ethnic groups."

Assigning Headings to Works 

• These rules are taken from the Subject Cataloging Manual that is used by all catalogers:
• Assign one or more subject headings that best summarize the content of the work. 
• Assign headings only for topics that compromise at least 20% of the work.
• Sometimes, one heading is sufficient; generally, a maximum of 6 is appropriate, but never more than 10
• Assign headings that are as specific as the topics they cover.

Subject Analysis by Catalogers

• These guidelines are taken from the Subject Cataloging Manual that is used by all catalogers:
• Titles and subtitles are important because they sometimes state in the words of the author or publisher the subject matter of the work.
• If the title is misleading, euphemistic, or cryptic, do not use the title of the work as a guide to the contents of the work.
• If the title is general, but the work is actually on a more specific topci, assign a heading for the specific topic. 

Subject Analysis, Controlled Vocabularies and Thesaurus Structure

Previous Problem

• Economics of information organization:
• High cost of human-created descriptive metadata
• High cost of maintaining authority files and other sources of right side content
• Solution for description:
• Centralize cataloging work whenever possible, including authority files
• Distribute metadata and authority records using industry standard MaRC encoding

New Problem

• Economics of information organization:
• High cost of human-created subject metadata
• High cost of maintaining authority files and other sources of right side content
• Solution for subject analysis:
• Centralize cataloging work whenever possible, including authority files
• Distribute metadata and authority records using industry standard MaRC encoding.

Shared Authority Files

• Purposes of shared authority files:
• To map from alternative forms of terms to authorized forms
• To provide a common source for cataloging/metadata record content (i.e. for data entry purposes)
• A shared authority file is maintained independently of cataloging/metadata files, and authority files are often shared across different institutions. 
• For description, authority files include LCNAF and ULAN.
• For subject analysis, authority files are called controlled vocabularies

Functional Purposes of Authority Work

• To meet Cutter objectives 1 & 2

1. To locate an item in a library ( a known item search):
• By an author
• On a subject
2. To show what the library has (a collocating search):
• By an author (collocation using author criterion)
• On a subject (collocation using subject criterion)

• Additional purposes of subject authority work:
• Synonymy: To relate different words that represent the same concept
• Homonymy: To distinguish (i.e. disambiguate) between different concepts having the same name. 

Why vocabulary control?

• Problem of natural language variation:
• Varation over time in the way concepts are referred to 
• Geographical variation in the way people ask for resources using a subject criterion - The Great Pop vs. Soda Controversy
• Problem that the same concept (e.g. fizzy liquid) is referred with different strings of character (i.e. words)
• Cataloger's decision: "I know what the subject is (from the resource in hand), but what subject data do I enter into the surrogate record?"

What Vocabulary Control Controls

• Systems of controlled vocabularies map the various words that describe concepts. 
• These concepts are maintained in a thesaurus of headings list, where each concept is located in what we'll call a "semantic neighborhood."
• Problems addressed by controlled vocabularies:
• Lexical and orthographic variation
• Word sequences
• Abbreviations
• Technical language
• Synonymy
• Homonymy 

Lexical and Orthographic Variation

• Same concept different spellings
1. Varying word forms
2. Differences across cultures and coutnries
3. Changes over time

• Examples

1. Varying word forms
• clothes vs. clothing
2. Differences across cultures and countries:
• Orthopedic vs. orthapaedics
• Catalog vs. catalogue
3. Changes over time:
• on line vs. on-line vs. online

Word sequences

• Same multiword concept, different word order:
• Inversion is the process of reversing word order 
• Used to collocated like with like
• Examples
• Educational psychology vs psychology, educational
• Right of asylum vs asylum, right of
• BOTTOM LINE: WE DON'T CARE HOW IT'S ORDERED IT JUST NEEDS TO GET THE INFORMATION

Abbreviations

• Same concept, different word forms:
• Depends on the intended use of the controlled vocabulary
• Abbreviations are normally spelled out
• Exceptions for those concepts with worldwide recognition
• Example:
• Acquired Immunodeficiency Syndrome vs. AIDS

Technical Languages

• Same concept, different words:
• Depends on the intended use of the controlled vocabulary
• Use words that match that of the intended user group
• Example:
• Neoplasms(MeSH) vs cancer (LCSH)

Synonymy

• Same concept, different words. 
• Examples:
• Cats vs felines
• Attire vs dress vs clothing

Homonymy

• Same word and/or pronunciation, different concepts
1. Homographs - same word, different concepts
2. Homophones - same pronunciation, different concepts
• Examples:
1. Homographs
• Mercury (planet) vs Mercury (god)
2. Homophones
• Foul vs Fowl

Vocabulary Control Techniques

• Use of entry terms (mapping):
• Lexical and orthographic variation
• Word sequences
• Abbreviations
• Technical Language
• Synonymy
• Use of various disambiguation techniques:
• Homonymy

Vocabulary Control - Entry Terms

• All words or word forms are mapped to the authorized word form for that concept.
• Quality of controlled vocabulary is directly related to the number of entry terms, which themselves must be maintained over time. 
• EXAMPLE: search MeSH for "brain neoplasms" vs "brain cancer" - brings up the same info. Good mapping!Great example of high quality subject heading terms (LCSH being example of low quality).

Vocabulary Control - Disambiguation

• Qualification
• Parenthetical qualifier to disambiguation meaning
• Mercury (god)
• Mercury (planet)
• Scope notes - specific definition for a term within that domain
• Domain specification:
• Limiting controlled vocabulary to a subject or domain
• Mercury (god) not needed in medical vocabulary because it is out of scope. 
• Hierarchy
• Embed concept in hierarchical context
• Metals 
•  Mercury
• In the case above, Mercury, if within subject of Metals, does not need parenthetical qualifier (metal) to differentiate between the metal and Mercury, the god, because the latter is not related to Metals. 

The "Semantic Neighborhood" Concept

• The concepts represented in controlled vocabularies can be thought of as residing in a semantic neighborhood. 
• Each concept has relationships to other concepts in four directions:
• "North/South" for broader and narrower concepts
• "East/West" for related concepts
• These relationships provide the intellectual infrastructure of a domain to the indexer and the searcher ("riding the rails").

 Broader and Narrower Concepts

• Hierarchical relationships -n "riding the rails" in northerly and southerly directions:
• In classical terms: parent/child relationships - mammal ... dog
• In ontological terms: "is/a relationships" - dog is a mammal
• Broader term (BT) relationships (northerly):
• Also termed "subordinate" relationship.
• Gives the context of the concept for disambiguation purposes
• Narrower term (NT) relationships (southerly):
• Also termed "subordinate" relationship
• Indexers ALWAYS use the most specific term (specific entry)

Related Concepts - East/West

• Equivalence and associative relationships - "riding the rails" in east/west directions.
• Equivalence reltaionships - "use" & "use for" (UF):
• Relates authorized terms and entry terms (i.e. synonyms)
• Maintenance (UF upkeep)
• Upkeep use Maintenance
• i.e. maintenance is the preferred term used for searching.
• Associative relationships - "related terms" (RT):
• Also called "see also" terms
• Terms have non-hierachical relationship (i.e., not synonymous)
• Birds (RT Ornithology)
• If someone comes in and asks for a book on bird, and you ask if they want a book on birds or if they want a book on the study of birds you will know if you should use "ornithology" as your search term.

Semantic Neighborhood Examples

• Library of Congress Subject Heading (LCSH):
• "Soda pop" in LCSH Authorities (note subdivisions) 
• "Dog" in LCSH Authorities 
• "AIDS" in MeSH (note History Note)

Subject Analysis in Context

• Obtain resource
• Describe resource in surrogate record.
• Subject analyze resource in surrogate record:
• Verbal
• Classification

Basic Concepts of Subject Analysis

• The reader is the focus - how do users ask for resources when using retrieval tools?
• Collocation using subject criterion
• Terms must represent common usage among users of the retrieval tool.
• Specific Entry - professional indexers ALWAYS index to the most specific relevant term.

Performing Subject Analysis - Two Steps

1. Read for subject analysis to generate concepts that describe the "aboutness" of the information resource:
• DO NOT read entire work
• DO read:
• Preface
• Introduction
•  Table of Contents
• Some text, especially noting those words that are bold, italicized, part of a caption, etc. 
• Bibliographies
2. Translate concepts into the controlled vocabulary of the information retrieval tool.

Reading for Subject Analysis Purposes

• Take notes while reading.
• Write down common themes.
• Use dictionaries, encyclopedias, etc. to clarify terminologies. 
• Get a clear picture in mind about primary and secondary topics (the "aboutness") of the work.

Indexing Exhaustivity

• Addresses the question: How many subject terms per resource?
• Important to indexers because of the need to maintain consistency across resources indexed in a retrieval tool
• Important for searchers to know in advance of a successful search. 
• Summarization:
• Purpose is to summarize subject content of resource
• Used in library cataloging (books contain secondary indexing)
• Depth Indexing:
• To exhaustively describe subject content of resource
• Used in article indexing (and web page indexing) for resources that often do not have secondary indexing structures. 

Article Summary for Lecture # 7 - Aitchison

The Thesaurus:

A Historical Viewpoint, 

with a Look to the Future

Four decades of use, experimentation, and development have allowed users, researchers, and catalogers to refine thesauri to be very effective search tools. Aitchison and Clarke discuss the history, making note of important, monumental events that help in the creation of what we know as the thesaurus. They draw on earlier printed histories of thesauri (specifically Gilchrist’s Thesaurus in Retrieval), and go on to define thesaurus as “a treasury or storehouse of knowledge, as a dictionary, encyclopedia and the like.” The primary purpose of thesauri is to match the vocabulary used by the indexer with the language of the searcher.

The first time the word “thesaurus” was used (in terms of information retrieval) was in 1957 by Peter Luhn of IBM, and had definitely evolved through the 1950s. One particular highlight on the timeline of the thesaurus is the Uniterm System, which used uncontrolled single words taken from the text of documents, which ultimately proved difficult since only single-word terms were available to deal with synonyms, homonyms, etc. Fortunately, it was superseded by vocabularies containing significant numbers of compound terms. In addition, during this time, the thesauri listed terms in alphabetical order, which was eventually carried into the standardization of format in 1967 when the Thesaurus of Engineering and Scientific Terms (TEST) was published.

This predominant feature alphabetically displays descriptors and non-descriptors - synonyms, broader, narrower, and related terms showing under each descriptor. A subject overview or systematic display was of secondary importance. The idea of a detailed classified arrangement was considered too complex. An example of this is the Descriptor Group Display, within which main groups are divided into subgroups, and within the subgroups, descriptors are further organized into clusters. For example:

14    DEMOGRAPHY. POPULATIONS

                14.01 POPULATION DYNAMICS

                14.01.01

                    CIVIL REGISTRATION

                    DEMOGRAPHIC STATISTICS

                    POPULATION DATA

                       USE: DEMOGRAPHIC STATISTICS

                    etc.

In order to section thesaurus information in this way, the classification scheme is an indispensable tool. When the editor works only with an alphabetical list, it is a sense of working blind, but if rigorous classification is developed, the compiler has a better chance of building accurate and meaningful relationships between the terms. In the early days, most thesauri were compiled manually, which was a massive and both a time and space investment (e.g. Thesaurofacet was held in more than 20 shoeboxes containing cards for 16,000 descriptors and 7,000 non-descriptors), and was greatly vulnerable to human errors or mid-process interruptions. This is where computer-aided compilation becomes handy. In the late 1970s, computer compilation was more common; however, there was no software to maintain a systematic display of the faceted thesaurus style.

During this time, access was usually limited to one workplace. There was either a large tome that stood by the bank of filing cards or optical coincidence viewer, and even computerized thesauri were limited in space. However, trained searchers became fluent with the process, and that alongside trained indexers they were able to fully harness the power of the thesauri to perform effective searches. Nowadays, pcs are everywhere, and each of them provide access to unlimited networks. In order to apply thesauri to information retrieval the authors feel the following challenges need to be addressed:

• Access to information proceeds through any number of different portals, gateways, and search engines, many geared to particular audiences and subject areas. There is no universal thesaurus, but a multitude of different vocabularies for different applications.
• In the publish one, re-utilize many times’ environment, it is hard to predict in which systems or networks a given document may eventually appear. Indexers must struggle to foresee all the needs that may arise for a given document.
• With the data entry/indexing task distributed among a vast number of authors, webmasters, system administrators, etc., quality control cannot be enforced across organizational boundaries.
• How can we train end-users to use a thesaurus properly? The experience of most information providers is that users do not want to cope with anything complicated, and the thesaurus is perceived as very complicated. Those beautifully presented systematic displays, carefully designed for selecting the right term(s) for each required concept, are often rejected as an unnecessary impediment and delay between the user and goal.

Confronting these challenges has recently led to two major trends in thesaurus developments:

• Hunting for adaptations that will make a controlled vocabulary much quicker, easier, and more intuitive to use.
• Drive to interoperability of systems, meaning to design vocabularies for easy integration into downstream applications such as content management systems, indexing/meta-tagging interface, search engines, and portals.

Current technology has users who are more than happy to browse through a simple classified directory, using point-and-click interaction with established headings instead of actively thinking of search terms. This is why some companies are working on developing taxonomies that will make things easier for the searcher, and perhaps even the indexer. There are even mentions of hiding vocabulary all together by implementing synonyms sets for selected terms that can be used to drive automatic expansion of free-text search queries.

Another topic current thesauri developers need to think about is interoperability. It makes things easier for users. Gone are the days of looking up in a printed thesaurus and then key selected terms into the indexing system. Now, copy-paste or clicking on them, a search system has to be capable of interacting with the thesaurus database.These newest concerns were reflected in the updated standards released in the Workshop on Electronic Thesauri held in 1999, which says, “The standard should provide for a broader group of controlled vocabularies than those that fit the standard definition of “thesaurus.” This includes, for example, ontologies, classifications, taxonomies and subject headings, in addition to standard thesauri. The primary concern is with shareability (interoperability), rather than with construction or display. Therefore, this new standard will probably not supersede Z39.19, but supplement it.

Overall, I think Aitchison and Clarke’s article is very thorough and offers a lot of insight into the world of thesauri. This is a great read for anyone interested in the development of thesauri or the organization of information. They have a ton of information and references to support their examples, and write in a way that is easy for even beginners to be able to pull information from the article and form new ideas and appreciation for the thesaurus in their life!

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For more information, check out the full article (citation below)!

Aitchison, J., & Clarke, S.D. (2004). The thesaurus: A historical viewpoint, with a look to the future. Cataloging & Classification Quarterly 37(3/4):5-21.

Article Summary for Lecture # 5 - Schottlaender

Why Metadata?

Why Me?

Why Now?

                “Because it is inescapable and seemingly more evident every day; because it is what we are about; and finally, because not only do we need metadata as another tool in our network of tools to do what we do, but metadata needs us to help fully realize its potential.” This is how Schottlaender answers these questions – Why metadata? Why me? Why now? – though he goes into further detail answering these questions in his article. Fluidity is the first emphasized element of information Schottlaender discusses.  Since data is always changing online, resources are complex, and individual components require management, which reflects the environment of metadata – “structured, encoded data that describes characteristics of information-bearing entities to aid in the identification, discovery, assessment, and management of the described entities.”

                Schottlaender, from there, goes on to define and discuss encoding schema, metadata schema, and architectural schema. His preferred definition of schema is “a set of rules for encoding information that supports specific communities of users.” There are numerous encoding schema, but Schottlaender chooses to focus on MARC (MAchine Readable Cataloging), which is the standard structure for encoding cataloging data – most often bibliographic and authority data; SGML (Standard Generalized Markup Language), an international standard that specifies a method for describing the structure of a specific document; HTML (HyperText Markup Language), which is based on SGML, but intended for marking up hypertext, multimedia, and reasonable small, simple documents; XML (Extensible Markup Language), which is the medium between HTML and SGML – a simplified subset of SGML intended for Web applications.

                Metadata schema are just as numerous (descriptive, administrative, technical, rights and personal information, commercial management, content rating, and preservation), but the author focuses solely on descriptive metadata. The most famous descriptive metadata schema is the Dublin Core (Dublin Metadata Core Element Set), which is a core set of elements meant to be used to describe and facilitate discovery of document-like objects in a networked environment. Schottlaender emphasizes “document-like objects”, because the digital information universe is full of non document-like objects that the Dublin Core may or may not be able to describe. There are also specific descriptive schema for specific documents:

• AGLS (Australian Government Locator Service) – government documents
• REACH (Record Export for Art and Cultural Heritage) – art documents
• TEI (Text Encoding Initiative) – document types within SGML
• EAD (Encoded Archival Description) – document types within SGML

                These metadata schema tend to focus on syntax (i.e. When you describe an object, you should be sure to include in that description its title, creator, etc.), but rarely tell a user how to do that. Another important, highly concentrated descriptive metadata type are “identifiers.” Upon hearing “identifiers, I wasn’t expecting to recognize any of these, but any book lover or student will know International Standard Book Numbers (ISBN) and International Standard Serial Numbers (ISSN) from their book searches. 

Schottlaender then discusses three architectural schema, the Interoperability of Data in E-Commerce Systems (INDECS) – integration a variety of standards developed by communities that concern themselves with copyright, Resource Description Framework (RDF) – an infrastructure for “encoding, exchange, and reuse of structure metadata, and the Warwick Framework – a container architecture for diverse sets of metadata. He also begins to discuss why catalogers should be in the forefront of the metadata movement. Cataloging is about access, describing content, and content relationships. It is an “invisible process of order-making” that is not about rules, nor about the records created because of those rules, but instead about standards, vocabulary development, and the development of systems for description and classification.

I agree with Schottlaender’s conclusion that the ever-changing, non-fixable data of the digital age requires cataloger intervention and organization. This was an informative article that I feel all information organizers, catalogers, librarians, etc. should read. It offers a lot of information and insight to the multiple aspects of metadata. This is a great intro into metadata, and makes the case for a marriage between non-library communities and catalogers – there are always information to organize, and if there are specialists that can offer insight into non-library fields, we can extend our help into different patron populations and get information into the hands of those that need them, which is the purpose of information workers. 

_______________________________________________________________

 For more information, check out the full article (citation below)!

 Schottlaender, B.E.C. (2003). Why metadata? Why me? Why now?. Cataloging &  Classification Quarterly 36(3/4):19-29.

Encoding Standards and the Presentation of Information

The Automation Period in Libraries

By the mid 1960s computers were being used for the production of machine readable catalog records, and by 1985 the NYPL had begun providing access to its catalog through public access computer terminals. Today, since all of our tasks today revolve around computers, we need to understand the general strengths and weaknesses of computers, and understand the strengths and weaknesses of online catalogs and other computerized collections of surrogate records.

Marking Up

In print there are formatting conventions. The printer applies the appropriate format when needed:

• Italics
• Bold
• Underline

For computers, however, there are encoding standards. The computer must be told when to "turn on" and "turn off" the textual mark:

• WordPerfect "reveal codes" option
• Various other "mark up" languages
• SGML: "Standard Generalized Markup" Language
• HTML: "HyperText Markup" Language

In both print and online, marked up (or "tagged" text provides for the unique styling (i.e. design) of resources, the ability for authors to structure resources , the ability for authors to emphasize points, and cues and clues to what a document might be about. 

Encoding Standards - HTML

Purpose: For the computer-to-computer transfer of information
Example: How your computer displays a web page (HTML compliant browser interacting with file hosted on server miles, and miles away)
Problem: Computers are dumb, therefore everything must be explicitly described.
WWW Solution: HTML is an encoding standard that is employed nearly universally by web page realtors  so that their content can be displayed by HTML-compliant computers.

Header () - where metadata is stored (not readable to human viewers BUT is readable by computers) a form of surrogate record.

OPAC records are encoded in HTML, so the design and display of each record can facilitate efficient perusing by end-users. However, HTML doesn't have a set of tags rich enough for the mark up of library surrogate records (e.g. there is no "author" tag in HTML).

Encoding Standards - MaRC

Purpose: For the computer-to-computer transfer of information
Example: How you library catalog knows what to do with the cataloging data it receives from a bibliographic entry. 
Problem: Computers are dumb, therefore everything must be explicitly described.
Solution: MaRC is an encoding standard that is employed nearly universally by librarians so that their surrogate (i.e. bibliographic) records can be shared by catalogs world wide

Basics of MaRC Encoding

MaRC tags encode the left side elements ("signposts") of cataloging records:

• "100=" Main entry, personal name with a single surname
• "245=" Title and Statement of responsibility area, pick up tile for a title added entry, file under "Ra..."

Additional Structureal elements of MaRC:

• Indicators
• Subfield Codes

MaRC tags specify the meaning of the data in its context:

• "260 00 |a New York" indicates NY as a place of publication
• "245 00 |a New York" indicates NY as a title

245 14 |a The American Foreign Legion:

• 4 = 4 non filing characters T (1) h(2) e(3) [space](4)

MaRC Mnemonics

Tags divide by 100s:

• 0XX       Control Information, numbers, codes (local)
• 1XX       Main Entry
• 2XX       Titles, edition, imprint (in general, the title, statement of responsibility, edition, and
                 publication information)
• 3XX       Physical description, etc.
• 4XX       Series statements (as shown in the book)
• 5XX       Notes
• 6XX       Subject added entries
• 7XX       Added Entries other than subject or series
• 8XX       Series added entries (other authoritative forms)

Parallel content:

• X00       Personal Names
• X10       Corporate Names
• X11       Meeting Names
• X30       Uniform titles
• X40       Bibliographic titles
• X50       Topical terms
• X51       Geographic names

Parallel content examples:

• 600 indicates that the subject (6XX) is a person (X00)
• 610 indicates that the subject (6XX) is a corporation (X10)
• 650 indicates that the subject (6XX) is a topic (X50)
• 100 indicates that the author (1XX) is a person (X00)
• 110 indicates that the author (1XX) is a corporation (X10)

The Missing "9s"

• Used by vendors or individual libraries to exchange additional data.
• Can appear in any position within the tag
• 9XX
• X9X
• XX9
• EXAMPLE:
• 269 = locally added publication data
• 590 = locally added contents note

A good key can be found via the Library of Congress.

Article Summary for Lecture # 4 - Carlyle

Understanding FRBR As a Conceptual Model

FRBR and the Bibliographic Universe

Allyson Carlyle, in her article, examines FRBR’s status as a model, and seeks to clarify what it is, what it is not, and what it attempts to do. In essence, FRBR is a conceptual model (or a model of a model – if one considers that a bibliographic record is a representation of a document). Carlyle begins with the deconstruction by reviewing the multiple definitions of “model”. A model can be:

1)      a representation of something (sometimes on a smaller scale)

2)      a schematic description of a system, theory, or phenomenon that accounts for its known or inferred properties and may be used for further study of its characteristics: a model of generative grammar; a model of an atom; an economic model

3)      a simplified description of a complex entity or process

4)      a preliminary work or construction that serves as a plan from which a final product is to be made: a clay model ready for casting.

           Being a conceptual model (sometimes referred to as an abstract model), it is entirely theoretical. This is a major strength, because it helps to facilitate understanding and allows manipulation of complex entities by making them less complex. Conceptual models can also model just about anything, and FRBR is a great way to make something that is abstract into something that is concrete. For example, trying to model love – an abstract concept. In order to make a model of love, we need to operationalize it. How many times two people kiss each other, how much time do they spend together, or whether or not they live together can be observable items that help model love.

        The FRBR Group 1 entities work and expression are abstract ideas that have a lot in common with love. In order to verify the existence of work and expression we need to know:

1)      What documents say about themselves and what others say about them

2)      What people say when they want to find a document – for example:

a.       Do you have Seamus Heaney’s translation of Beowulf? (expression)

b.      Do you have Stephen Hawking’s A Brief History of Time? (work)

Since FRBR is such a specific type of conceptual model, it can be referred to as an entity-relationship (ER) model. Carlyle describes ER modeling as a technique that specifies the structure of a conceptual model (i.e. the kinds of things that have to be in it and the properties those things may have). For FRBR, and an ER model, three things are allowed in it: entities (things – either physical or abstract), attributes (properties or characteristics of entities and relationships), and relationships (interactions among entities). 

       The developers of FRBR aimed to “produce a framework that would provide a clear, precisely stated, and commonly shared understanding of what it is that the bibliographic record aims to provide information about.” However, to clearly understand FRBR, it pays to look at other models.

•  One Entity Model – the only entity recognized it “item” or ‘copy”
• Two-Entity Model – recognizes editions as well as copies
• Three-Entity Model – recognizes editions, copies, and “literary unit” (a.k.a. work)
•  Four-Entity Model – recognizes editions, copies, works, and “text”

FRBR is new and different from these models in that it identifies and defines four entities, recognizes four entities simultaneously, and present a cataloging model using an ER modeling technique. However, according to Carlyle, one of the greatest challenges in implementing FRBR in a code of rules is determining which items will be assigned by catalogers to which set. In the implementation process, decisions about the boundaries of the abstract entities work and expression must be made. (e.g. will a movie version of an original textual work be considered an expression of that work, or will it be considered to be a new work with a derivative relationship to the original?

      Ultimately, Carlyle concludes that successful implementation of FRBR will help patrons successfully perform searches by presenting information about complex works in helpful and intelligent ways, and encourages the viewing of FRBR as a continuation/natural extension of cataloging models used over the centuries cataloging has been around. I would agree with her summarization and emphasis of embracing FRBR. As I have said in previous posts, the job of an information organizer to get quality information into the hands of users through the easiest means. FRBR takes complex entries, and helps break down the information (entities) in such a way retrieval is easy. If you are interested in FRBR, or think you should try and figure out what FRBR is about or clarify a muddy view of the model, this is the perfect article for you!

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If you want to read more about this topic, be sure to check out the whole article (citation below)!
Carlyle, A. (2006). Understanding FRBR as a conceptual model: FRBR and the bibliographic universe. Library Resources & Technical Services 50:264-73