Semantic spectrum

The <a href="/facts/Semantics/1L4WwLAP">semantic</a> <a href="/facts/Spectrum/wPUjkpqI">spectrum</a>, sometimes referred to as the ontology spectrum, the smart data continuum, or semantic precision, is in <a href="/facts/Linguistics/oQuamvf2">linguistics</a>, a series of increasingly precise or rather <a href="/facts/Semantics/1L4WwLAP">semantically</a> expressive definitions for <a href="/facts/Data_element/jtyoAIAd">data elements</a> in <a href="/facts/Knowledge_representation/9lnzyILD">knowledge representations</a>, especially for machine use.
At the low end of the spectrum is a simple binding of a single word or phrase and its definition. At the high end is a full <a href="/facts/Ontology_(computer_science)/SQlhl6lp">ontology</a> that specifies relationships between data elements using precise <a href="/facts/URI/UjyqxTpA">URIs</a> for relationships and properties.
With increased <a href="/facts/Specificity_(tests)/pzc9qfdz">specificity</a> comes increased precision and the ability to use tools to automatically <a href="/facts/System_integration/xJKG0sHM">integrate</a> systems, but also increased cost to build and maintain a <a href="/facts/Metadata_registry/DxuCj49r">metadata registry</a>. 
Some steps in the semantic spectrum include the following:

<ol><li><a href="/facts/Glossary/jWSovqDw">Glossary</a>: A simple list of terms and their definitions. A glossary focuses on creating a complete list of the terminology of domain-specific terms and <a href="/facts/Acronym/nlHK7aRt">acronyms</a>. It is useful for creating clear and unambiguous definitions for terms, and because it can be created with simple word processing tools, few technical tools are necessary.</li>
<li><a href="/facts/Controlled_vocabulary/JcYKWx3H">Controlled vocabulary</a>: A simple list of terms, definitions and naming conventions. A controlled vocabulary frequently has some type of oversight process associated with adding or removing data element definitions to ensure consistency. Terms are often defined in relationship to each other.</li>
<li><a href="/facts/Data_dictionary/GyQLYd7j">Data dictionary</a>: Terms, definitions, naming conventions and one or more representations of the data elements in a computer system. Data dictionaries often define data types, validation checks such as enumerated values and the formal definitions of each of the enumerated values.</li>
<li><a href="/facts/Data_model/j1YyzpJ3">Data model</a>: Terms, definitions, naming conventions, representations and one or more representations of the data elements as well as the beginning of specification of the relationships between data elements including abstractions and containers.</li>
<li><a href="/facts/Taxonomy_(general)/QRvFI267">Taxonomy</a>: A complete data model in an inheritance hierarchy where all data elements inherit their behaviors from a single "super data element". The difference between a data model and a formal taxonomy is the arrangement of data elements into a formal tree structure where each element in the tree is a formally defined concept with associated properties.</li>
<li><a href="/facts/Ontology_(computer_science)/SQlhl6lp">Ontology</a>: A complete, machine-readable specification of a conceptualization using <a href="/facts/URI/UjyqxTpA">URIs</a> (and then <a href="/facts/Internationalized_Resource_Identifier/x3JWG8Gx">IRIs</a>) for all data elements, properties and relationship types. The <a href="/facts/W3C/lGWmhF6M">W3C</a> standard language for representing ontologies is the <a href="/facts/Web_Ontology_Language/jkr0IGn8">Web Ontology Language</a> (OWL). Ontologies frequently contain formal business rules formed in discrete logic statements that relate data elements to each another.</li></ol>

Semantic spectrum open-in-new

Semantic spectrum