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The Gellish Modeling Methodology is a methodology that covers the following six area's:

1. Creation of Domain Dictionaries-Taxonomies

This inludes the creation of Smart Dictionaries or Taxonomies with Definition Models for particular application domains in any natural language.
The method includes the creation of Definition Models in which facts about the defined concepts that are by definition true are explicitly modeled such that the expressions are computer interpretable. Each Definition Model includes at least a subtype-supertype relation and a specification of at least one aspect that distinguishes a subtype concept from its supertype concept and from its neighbouring concept(s). This ensures that the concepts in the Dictionary are arranged in a Taxonomy structure. A Definition Model also includes the specification of one or more names, synonyms, abbreviations, symbols, etc. to denote the concept in one or more languages and contexts (language communities). Furthermore the Dictionary includes the definition of kinds of aspects and aspect values that are used to define concepts. The relation types that are used to specify relations between concepts are themselves also defined in the dictionary. A collection of Definition Models thus forms a semantic network of concepts, which make it a computer interpretable Smart Dictionary / Taxonomy that is an extension of the general purpose Gellish Smart Dictionary. Guidelines for the creation of Definition Models can be found in the document 'Guide for the extension of the Gellish Dictionary' in the download area of this website.

2. Creation and use of Knowledge Models

The method to create Knowledge Models includes the expression of knowledge about kinds of things in a computer interpretable form. For example, the possible decomposition of objects of a particular kind in components of particular kinds and the kinds of properties that such an object or its components can have. Knowledge models expressed in Gellish will use the concepts that are defined in the Gellish Smart Dictionary or concepts in a proprietary extension or Domain Dictionary. Knowledge Models are in fact extensions of the Definition Models, because they added facts that can be true to facts that are by definition true. Collections of Knowledge Models in a particular domains are often called an Ontology for that domain and may be included in 'Knowledge Libraries', also called an 'Object Libraries'. Guidelines for such knowledge libraries are for example also provided in the Dutch Standard NTA8611 'Guidelines for Object Libraries', available from the NEN (the Dutch standards institute), which is proposed as a new ISO standard. The Gellish Modeling Methodology also describes how Knowledge Models can be used. For example, to guide a design process or to provide knowledge about standard solutions for designs.

3. Creation and use of Standard Specification Models and Requirements Models

Standard specifications are specifications of standardised products and components, often called product types or product models. There are many of such specifications published as documents in national and international standards as well in company specific product catalogues. They are usually called 'products', although they are in fact kinds of products and not individual products. This part of the Gellish Modeling Method provides guidelines for the expression of information about such standard product types and component types in the form of neutral computer interpretable models that can bestored in databases and can be exchanged between parties and are expressed in system independent Gellish English, Gellish Nederlands (Dutch) or any other Gellish language. The method also provides guidance on the use of these models for example for procurement.

This part of the Gellish Modeling Methodology is among others intended to transform Product Catalogues of manufacturers and suppliers in an electronic form for usage in e-commerce, whereas conventionally this is done in proprietary formats. The method is also intended for the conversion of standards for product types from national and international standards organizations, which are currently still published in paper form and are usually not yet made available in a system independent computer interpretable electronic form.

Standard requirements are requirements about kinds of things. For example, requirements for data and documents about facilities that have to be delivered by contractors, manufacturers and suppliers that realise capital projects. Such requirements are usually applicable in a particular company or project context in which they are declared to be applicable. They may include requirements for data and documents about products, procedures and applications. Such requirements are expressed for example in best practices guides of companies, but also in national and international standards as well as in governmental rules. Usually such requirements are expressed in textual documents. This part of the Gellish Modeling Method provides guidance for the creation of requirements models that are computer interpretable and that can be used for computer-aided support for the verification whether a deliverable (such as a design or a fabricated product) satisfies those requirements.
Standard Specification Models as well as Requirements Models that are expressed in Gellish use the concepts that are defined in a Gellish Dictionary.

4. The creation of Facility Information Models

Facility Information Models are models with information about individual objects. This may be data and documents about imaginary objects, such as designs of objects, it may also be data and documents about realised facilities and their operation and/or maintenance. This part of the Gellish Modeling Method provides guidance on how to create such a Facility Information Model in a neutral computer interpretable form as a Gellish Database. This means that there is no need to specify a database structure for such a model. The resulting Facility Information Model will usually include at least four sections:

1. Facility models and product models

A model of the facility or product and its components and processes, such as a building, a ship, a process plant, a railway, a car, etc.

2. Document models

A document and data sets repository with the data sets and documents, including also electronic drawings and 3D model files about the components in the facility and product models with relations to the components, so that the facility models and product models can be used to search for the data and the documents about them.

3. A Dictionary-Taxonomy

A Dictionary-Taxonomy is required, because the individual components, their properties and documents will be classified by standard concepts (classes) as defined the Gellish Dictionary or a Domain Dictionary. As a consequence the Facility Information Model is expressed in a consistent common language that enables to integrate data from various sources, and it also enable very powerful searching, especially by making use of the knowledge that is contained in the Gellish taxonomy.

4. Requirement models and knowledge models

A collection of Requirements Models and knowledge models that express the requirements and knowledge for the first and second section (the facility model and the documents and data set) so that they can be verified on completion and other information quality aspects.

5. Creation and interpretation of messages between systems

The part of the Gellish Modeling Methodology describes how to create messages for the exchange fo data between systems. This includes messages that express queries to people or to query central or distributed databases, messages that contain responses with answers and messages with statements. The method describes how software should create and interpret (parse) such messages that are exchanged between Gellish enabled software. In other words, it describes messages for system independent communication via Internet through a A Gellish Semantic Web.

6. Creation of Queries

Expressions that specify queries on Gellish databases are models in which unknowns appear for which constraints are specified. The methodology describes how such queries can be formulated. This does not require a separate query language, but the queries can be formulated in normal Gellish Formal English.

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