It's becoming quite clear that we are entering an exciting new age of possibilities for both the business and IT centered on semantics.  I would like to go on the record as early as possible to establish sensible meanings for important buzzwords sure to emerge.  If you suspect am making these up as I go, you are absolutely right.  That's how I can be sure I have their semantics (meaning) just right.  You can never be wrong using your own buzzwords, can you?!

Semantic Community:  a group of people who are able to communicate with each other effectively about non-trivial matters because they share common understanding of a significant set of concepts, though not necessarily the same symbols (e.g., terms) for those concepts.  (To be contrasted with 'speech community,' a community that shares the same symbols for the concepts as well.)

Legacy Semantics:  the current semantics of an organization, often implicit in legacy systems or tacit in minds of business workers.  The lack of explicit semantics (i.e., shared, organization-wide business vocabularies) is a fundamental cause of miscommunication, misunderstanding, and defects in specifications and implementations.  The problem of legacy semantics often masquerades as 'data quality' problems, but these represent the symptoms of the problem, not the problem itself.  The challenge of legacy semantics not only impacts timely implementation of new business initiatives, but also represents a significant barrier to the retention, encoding, and exploitation of knowledge -- especially business rules.

Stovepipe Semantics:  legacy semantics implicit in stovepipe applications.

Semantic Impurity:  any content problem with a business vocabulary, including ambiguity, homonyms, misnomers, overlaps, conflicts, etc.

Semantic Inventory:  a collection of terms (representing concepts) and facts -- that is, a business vocabulary -- for which the organization has (a) developed a shared understanding in the form of explicit, business-based definitions, and (b) provided the requisite support for it to be managed, extended, and re-used in a timely, coordinated manner.

Semantic Visualization:  any diagram (e.g., a fact model) supporting visual inspection of business vocabulary, especially the relation of concepts as represented by terms.

Semantic Migration:  the change process of moving the company from legacy semantics to a semantic inventory.  Semantic migration often thought of as 'data migration,' but this misnomer obscures the fact that the difficult issues concern business policy, not simply data transformation.

Real-Time Semantics:  An on-line, interactive semantic inventory, which is proactively involved as business people and analysts create specifications of all kinds, including but not limited to definitions, business rules, queries, and communications.

Semantic Rule:  A rule that arises from the meaning of concepts and/or how they relate to one another, as expressed in definitions, generally reflecting either necessities or impossibilities.  Examples:  "Every function must have an input." and "Every order must be placed by a customer."  These rules arise by virtue of definitions -- that is, the definitions for 'function' and 'order,' respectively.  (To be contrasted with 'business rule,' which represents a selective means to achieve business goals, protect against business risks, support business tactics, etc.  Business rules are generally about prohibition (of something that would otherwise be possible) or obligation (for something that would otherwise not be necessary), and reflect choices relating to guidance made by the organization.)

Semantic Completeness:  The state of a business vocabulary in which (a) shared understanding (i.e., an approved definition) has been achieved for each concept within scope, and (b) all relations (fact types) between concepts (as represented by terms), and all semantic rules, have been formalized.

Semantic Consistency:  The state of a business vocabulary in which all semantic rules are satisfied.  (To be contrasted with 'consistency' (general), which requires all business rules be satisfied as well.  General consistency is more difficult to achieve than semantic consistency.)

Semantic Event:  An occurrence of creating or discontinuing a fact that can be expressed using the business vocabulary.  Semantic events are particularly important for both semantic rules and business rules, both of which are defined based on types of facts.  Semantic events therefore represent highly selective points where rules need to be immediately evaluated to maintain consistency.

Semantic Scenario:  The use of a semantic event to analyze a business rule, to determine (a) what policy issues arise, if any, and if so, what revision(s) or exception(s) to the business rule should be made, and (b) what selective reaction to a violation, if any, is appropriate.

Stratified Semantics:  An architectural technique featuring well-designed layering of a business vocabulary and associated business rules.  Fundamental, universal constructs are managed at a lower or more basic layer, which is then used to support selective extensions at the next higher level, and so on.  Semantic stratification enables highly scalable application of a semantic inventory to achieve mass customization of an organizations product(s) or service(s), and/or one of its core competencies.

Semantic Pattern:  A set of terms, facts, and rules providing a template for exercising a core competency of the business in a specific manner and/or for a specific market.  A semantic pattern must be based on a corresponding set of highly generalized terms, facts, and rules at the next lower semantic strata.

Semantic Query:  A query pertaining to knowledge or data that is expressed purely on the basis of a common business vocabulary, without any reference to how or where the data is stored.

Semantic Communication:  Communication conducted between communities on the basis of a common business vocabulary, possibly specialized.  Semantic communication assumes the communities share a semantic inventory, or an appropriate mapping between their respective semantic inventories.

Semantic Noise:  Any non-semantic content in semantic communication -- e.g., content pertaining to the means of delivery, platforms supporting the communication, random insertions, etc.

Semantic Adoption:  The act of accepting a particular business vocabulary from another organization to start or enhance a semantic inventory, and optionally deferring to the other organization for continuing revisions and enhancements.

Semantic SuperCommunity:  The union of communities capable of semantic communication based on a common specialized business vocabulary.

Semantic Supply Chain:  A group of communities consisting of one or more creators of a common specialized business vocabulary, the adopter(s) of that vocabulary, and the adopters' end-customers.  All organizations in a semantic supply chain are mutually dependent on the given vocabulary for the associated area of activity.

Only a Matter of Semantics:  Everything that is important in effective business communication within or between organizations, and all business specifications relating thereto.

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