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1. Introduction to Formalized Languages

The Gellish family of Formalized Languages, including Formal English, Formal Dutch and other formal language variants) are semantic modeling languages for the modeling of knowledge, requirements, definitions, queries as well as information about any individual things and individual processes. They are called formal languages, because they are formally defined, so that computers can unambiguously interpret the meaning from the expressions, which is not the case with natural languages. Information that is expressed in a Gellish formal language is thus computer interpretable and application system independent. It can be generated when exporting data from systems for data exchanged between systems and parties in Gellish Messages and can be imported, interpreted and stored in Database systems and files. Queries can also be expressed in formal languages. The language has a native standard Gellish Expression format, although it can also be stored in other formats.

Definitions of formal languages include electronic Taxonomic Dictionaries that provide the concepts and terminology of the languages, together with natural language independent unique identifiers (UIDs) for those concepts. Those UIDs represent the concepts independent of language. Information that is expressed in one of the formal languages include those UIDs, which enable that the expressions can be automatically translated by Gellish enabled software from one formal language to another. For example, queries in Formal Dutch, can be executed on databases that are in English, and the queries as well as the results can be presented to users in Dutch and vice versa. This is possible between any languages for which formal dictionaries are available.

The Gellish Semantic Information Modeling Methodology is a methodology that provides guidance on how to express, store and exchange information, knowledge and requirements in high quality semantic models that are unambiguous, consistent and by definition integrated.
The Methodology is documented in the book: 'Semantic Information Modeling Methodology'. The book discusses general principles and guidelines for semantic modeling as well as among others the following topics: A generic information model architecture, the creation of taxonomic dictionaries and product catalogs, modeling knowledge (the creation of knowledge models), requirements modeling, the creation of facility and products as well as processes and activities, including also modeling of 2D drawings and 3D models.

The Gellish Information Management Methodology provides guidance for organizations on a systematic approach for the management, integration and quality control of their information, knowledge and requirements, including data, textual documents, drawings and 3D models.

For information about Gellish in other languages see: Russian and for Dutch speaking people see Gellish Nederlands

2. Table of content of this Wiki

We recommend to study formalized languages in general and Formal English in particular by following the wiki pages in the sequence below. The language and application methodology can be studies more in depth by reading the books: 'Semantic Information Modeling in Formalized Languages' and 'Semantic Information Modeling Methodology'.

Table of content of this Wiki:

  1. Home (this page: Introduction)
  2. Gellish English Dictionary -Taxonomy (Gellish Dictionary)
  3. Facility Information Models (FIM), Building Information Models (BIM), etc.
  4. Product Modeling (Product Design)
  5. Universal Databases (Gellish Expression Tables)
  6. Dictionary Extension (Proper definition of a concept)
  7. Gellish messages for data exchange

Note that each Wiki page has its own table of content about the details on that page.

3. Categories of kinds of relations (relation types)

The expression power of formal languages is largely determined by the number and variety of kinds of relations that are available in the language definition. The Gellish formalized language definition includes more than 650 standard kinds of relations. They are defined in the upper ontology section of the Taxonomic Dictionary-Ontology. Their textual definitions and subtype-supertype hierarchy is documented in the book Taxonomic Dictionary of Relations and in its Dutch equivalent Taxonomisch Woordenboek van Relaties. The electronic version also includes definitions of the allowed roles and role players for those kinds of relations. Together that defines what are correct formal expressions. The electronic definitions can be licensed, and can then be directly imported in Gellish enabled databases to enable computer interpretation of formal language expressions.

Each relation type is identified by a unique identifier (Gellish UID). Furthermore, each relation type is denoted by at least one base phrase and by at least one inverse phrase. For example, a part-whole relation between two individual things is denoted in Formal English by the phrase <is a part of> and by the inverse phrases <has as part> and <is a whole for>. This means that the same fact can be expressed in either of the two ways. For example, the expression 'A <is a part of> B' has the same meaning as the expression 'B <has as part> A'. A relation type can also be denoted by alternative phrases, such as <is an assembly of>, or by phrases in other languages. Users may even define their own synonym phrases (provided that the UID remains the same) and they can indicate a 'language' and/or a 'language community' in which their phrase is preferred. For example: the Dutch (Nederlands) equivalent of the above example is: <is een deel van>.

The kinds of relations form a taxonomy (subtype-supertype hierarchy of kinds of relations) with the following branches:

  1. Kinds of relations between individual things
  2. Kinds of relations between an individual thing and a kind of thing
  3. Kinds of relations between kinds of things
  4. Kinds of relations between a single thing and a plurality
  5. Kinds of relations between pluralities

The kinds of relations include binary relations as well as higher order relations. Higher order relations include relations for modeling occurrences, such as processes, activities and events and relations to model correlations, such as for physical laws or geometric and mathematical formula.

For different application area's different kinds of relations are applicable.

start.txt · Last modified: 2017/08/11 15:10 (external edit)