Relationship Lists
Thesauri. Thesauri are based on concepts and they show relationships among terms. Relationships commonly expressed in a thesaurus include hierarchy, equivalence (synonymy), and association or relatedness. These relationships are generally represented by the notation BT (broader term), NT (narrower term), SY (synonym), and RT (associative or related term). Associative relationships may be more detailed in some schemes. For example, the Unified Medical Language System (UMLS) from the National Library of Medicine has defined more than 40 relationships, many of which are associative. Preferred terms for indexing and retrieval are identified. Entry terms (or nonpreferred terms) point to the preferred terms to be used for each concept.
There are standards for the development of monolingual thesauri (NISO 1998; ISO 1986) and multilingual thesauri (ISO 1985). In these standards, the definition of a thesaurus is fairly narrow. Standard relationships are assumed, as is the identification of preferred terms, and there are rules for creating relationships among terms. The definition of a thesaurus in these standards is often at variance with schemes that are traditionally called thesauri. Many thesauri do not follow all the rules of the standard but are still generally thought of as thesauri. Another type of thesaurus, such as the Roget's Thesaurus (with the addition of classification categories), represents only equivalence.
Many thesauri are large; they may include more than 50,000 terms. Most were developed for a specific discipline or a specific product or family of products. Examples include the Food and Agricultural Organization's Aquatic Sciences and Fisheries Thesaurus and the National Aeronautic and Space Administration (NASA) Thesaurus for aeronautics and aerospace-related topics.
Semantic Networks. With the advent of natural language processing, there have been significant developments in semantic networks. These KOSs structure concepts and terms not as hierarchies but as a network or a web. Concepts are thought of as nodes, and relationships branch out from them. The relationships generally go beyond the standard BT, NT, and RT. They may include specific whole-part, cause-effect, or parent-child relationships. The most noted semantic network is Princeton University's WordNet, which is now used in a variety of search engines.
Ontologies. Ontology is the newest label to be attached to some knowledge organization systems. The knowledge-management community is developing ontologies as specific concept models. They can represent complex relationships among objects, and include the rules and axioms missing from semantic networks. Ontologies that describe knowledge in a specific area are often connected with systems for data mining and knowledge management.
All of these examples of knowledge organization systems, which vary in complexity, structure, and function, can provide organization and increased access to digital libraries.