Controlled vocabulary

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Controlled vocabulary is a list of terms that have been enumerated explicitly. This list is controlled by and is available from a controlled vocabulary registration authority. All terms in a controlled vocabulary should have an unambiguous, non-redundant definition. This is a design goal that may not be true in practice. It depends on how strict the controlled vocabulary registration authority is regarding registration of terms into a controlled vocabulary. At a minimum, the following two rules should be enforced:

  1. If the same term is commonly used to mean different concepts in different contexts, then its name is explicitly qualified to resolve this ambiguity.
  2. If multiple terms are used to mean the same thing, one of the terms is identified as the preferred term in the controlled vocabulary and the other terms are listed as synonyms or aliases.

Contents

[edit] Controlled vocabulary in Library and information science

In Library and information science Controlled vocabulary is a carefully selected list of words and phrases, which are used to tag units of information so that they may be more easily retrieved by a search.[1][2] The terms are chosen and organized by trained professionals (including librarians and information scientists) who possess expertise in the subject area. Controlled vocabulary terms can accurately describe what a given document is actually about, even if the terms themselves do not occur within the document's text. Fully developed controlled vocabulary systems, such as the Library of Congress Subject Headings, are often published in a reference work that is called a thesaurus. Controlled vocabularies form part of a larger universe of nomenclatural approaches to data classification called metadata.

[edit] Controlled vocabulary versus free text searching

Controlled vocabularies are often developed to improve the accuracy of free text searching, such as to reduce irrelevant items in the retrieval list. These irrelevant items (false positives) are often caused by the inherent ambiguity of natural language. Take the English word football for example. Football is the name given to a number of different team sports. Worldwide the most popular of these team sports is Association football, which also happens to be called soccer in several countries. The English language word football is also applied to Rugby football (Rugby union and rugby league), American football, Australian rules football, Gaelic football, and Canadian football. A search for football therefore will retrieve documents that are about several completely different sports. Controlled vocabulary solves this problem by tagging the documents in such a way that the ambiguities are eliminated.

Compared to free text searching, the use of a controlled vocabulary can dramatically increase the performance of an information retrieval system, if performance is measured by precision (the percentage of documents in the retrieval list that are actually relevant to the search topic). However, a controlled vocabulary search may have unsatisfactory recall, in that it will fail to retrieve some documents that are actually relevant to the search question. This is particularly problematic when the search question involves terms that are sufficiently tangential to the subject area that they are not likely to appear within the controlled vocabulary system.

Numerous methodologies have been developed to assist in the creation of controlled vocabularies, including faceted classification, which enables a given data record or document to be described in multiple ways.

[edit] Applications

Controlled vocabularies, such as the Library of Congress Subject Headings, are an essential component of bibliography, the study and classification of books. They were initially developed in library and information science. In the 1950s, government agencies began to develop controlled vocabularies for the burgeoning journal literature in specialized fields; an example is the Medical Subject Headings by the U.S. National Library of Medicine. Subsequently, for-profit firms (called Abstracting and indexing services) emerged to index the fast-growing literature in every field of knowledge. In the 1960s, an online bibliographic database industry developed based on dialup X.25 networking. These services were seldom made available to the public because they were difficult to use; specialist librarians called search intermediaries handled the searching job. In the 1980s, the first full text databases appeared; these databases contain the full text of the index articles as well as the bibliographic information. Online bibliographic databases have migrated to the Internet and are now publicly available; however, most are proprietary and can be expensive to use. Students enrolled in colleges and universities may be able to access some of these services without charge; some of these services may be accessible without charge at a public library.

In large organizations, controlled vocabularies may be introduced to improve technical communication. The use of controlled vocabulary ensures that everyone is using the same word to mean the same thing. This consistency of terms is one of the most important concepts in technical writing and knowledge management, where effort is expended to use the same word throughout a document or organization instead of slightly different ones to refer to the same thing.

Web searching could be dramatically improved by the development of a controlled vocabulary for describing Web pages; the use of such a vocabulary could culminate in a Semantic Web, in which the content of Web pages is described using a machine-readable metadata scheme. One of the first proposals for such a scheme is the Dublin Core Initiative.

It is unlikely that a single metadata scheme will ever succeed in describing the content of the entire Web.[3] To create a Semantic Web, it may be necessary to draw from two or more metadata systems to describe a Web page's contents. The eXchangeable Faceted Metadata Language (XFML) is designed to enable controlled vocabulary creators to publish and share metadata systems. XFML is designed on faceted classification principles.[4]

[edit] References

  1. ↑  Amy Warner, A taxonomy primer.
  2. ↑  Karl Fast, Fred Leise and Mike Steckel, What is a controlled vocabulary?
  3. ↑  Cory Doctorow, Metacrap.
  4. ↑  Mark Pilgrim, This is XFML.
  5. Controlled Vocabularies Links to examples of thesauri and classification schemes.
  6. Controlled Vocabularies Links to examples of thesauri and classification schemes used in the domain of Agriculture, Fisheries, Forestry etc.

[edit] See also

[edit] External links

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