CheckMi:Ontology
What can CheckMi:Ontology be used for? The semantic membrane of CheckMi:Ontology is able to provide a contextual referent integrity for many types of knowledge exchange. Including the provisioning of a Business Centric Methodology (BCM) compliant semantic overlay that ensures a contextual consistency in template patterns, data archetypes, schema elements and process actuation choice points. Which, for application governance, is used to:

• Provide trace-ability from business vision to system implementation
• Ensure alignment of business concepts with automated procedures
• Facilitate faster information utilization between business parties
• Enable accurate information discovery and synchronization
• Expand ability to integrate information by interest, perspective or requirement

Coupling of Classification
At its core the CheckMi:Ontology is a semantic grid of controlled vocabularies that increases the power of commonsense understanding while preserving the original semantic intent. Including :

• The body of knowledge is partitioned into logical groupings
• Users can discover information using a single word search term
• Topic to sub-topic, drill down searches are supported
• Domain scopes are declared
• The ambiguities of the (national) language are constrained

Formally Declared As
The semantic declarations that are embedded in a CheckMi:Ontology can take many forms. For instance, a lexicon declaration often just contains the definition of words used by a particular group of professionals. Declarations, in Taxonomies and Thesauri usually relate terms via parent-child and associative relationships that are valid only for a discipline specific realm. Further, declarations complying with an Information-based, Behavior-based and Process-based model notation (ERD,BPM,DFD) not only contain associative relationships, they also contain explicit grammar rules to constrain how to use controlled vocabulary terms to express (model) something meaningful within a domain of interest. More formally :

A controlled vocabulary is a declaration list of elemental terms that have been enumerated explicitly. This list is controlled by and is available from an authority, such as, ACORD. (note: EDI and XML templates only identify the standard syntax). Ideally, all elements in a controlled vocabulary have a unique label and an unambiguous, non-redundant definition, as in:

1. If a (term) token of an element label is commonly used to mean different concepts in different contexts, then that token is explicitly qualified to resolve the ambiguity.
2. If multiple terms are used to mean the same thing, they are considered (equally alternate) synonyms.

A thesaurus is a networked collection of controlled vocabulary terms. This means that a thesaurus declaration uses associative relationships in addition to broader-narrower (parent-child) relationships, e.g. synonym. The expressiveness of the associative relationships in a thesaurus vary and can be as simple as "related to term" as in term A is related to term B. Thesaurus builders can reference multiple standards including Z39.19-1993, ISO2788, ISO5964.

 A taxonomy is a collection of controlled vocabulary terms organized into a hierarchical structure. Each term in a taxonomy declaration is in one or more parent-child relationships to other terms in the taxonomy. There may be different types of parent-child relationships in a taxonomy (e.g., whole-part, genus-species, type-instance). In a poly-hierarchy, a term can have multiple parents, yet it has the same children in every location.

An OWL ontology enables a web service must be defined in un-ambiguous terms. That is, OWL ontologies allow a web service to be ‘published’ using a language that expresses something meaningful within a specified domain of interest. Therein, the ontology grammar declaration contains formal constraints (e.g., specifies what it means to be a well-formed statement, assertion, query, etc.). OWL Web Ontology Language can be used to explicitly represent the meaning of terms in vocabularies and the relationships between those terms. However, it is intended to be used when the information contained in documents needs to be processed by applications, as opposed to situations where the content only needs to be presented to humans.

A business model is an explicit model of the constructs and rules needed to map specific types of processing and data within a domain of interest declaration, e.g. namespace. a concept is perceived as a set of entities, called "concept instances", characterized as such by common agreement rather than formal reasoning on the properties that characterize an individual entity as an instance of a concept. 

A Topic Map is an ISO standard for building knowledge about a domain and integrating this encoded knowledge to information resources that are considered relevant to the domain. Topic map declarations are organized around topics, which represent subjects of discourse; associations, representing relationships between the subjects; and occurrences, which connect the subjects to pertinent information resources.

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