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Outline of this Wiki

This Wiki provides information and guidance on

  • the definition of the Gellish family of formalized languages,
  • the application of formal languages for creating databases, queries and messages,
  • the semantic information modeling methodology that uses those formalized languages.

The methodologies make use of an integrated information architecture. The vocabulary of each formal language in the family is defined in a taxonomic dictionary, thus defining formal natural language specific variants of the Gellish family. All dictionaries in the family use the same unique identifiers (UIDs) to represent the defined concepts. This enables that the expressions can be machine tranformed into any other formal natural language variant for which a formal dictionary is available. Thus Gellish Formal English, Formal Dutch (Formeel Nederlands), etc. are all formally defined, but share the defined concepts.

1. The Semantic Modeling Methodology

The Semantic Modeling Methodology delivers semantic information models. Such models consist of collections of expressions in which the meaning (the semantics) of the expressions is included in the expressions themselves. Thus semantic models do not require external documentation nor data models, for their interpretation. The language definition is sufficient for an unambiguous interpretation of the expressions. For that purpose, each expression includes a kind of relation that is defined in the formal language definition. The modeling methodology provides guidelines for modeling in at least the following five area's:

  1. The creation of computer interpretable Taxonomic Dictionaries, in which the defined concepts are arranged in the form of a subtype - supertype hierarchy, which is also called a taxonomy. Definition are textual expressions, which may also be explicitly modeled in the form of Definition Models. Domain taxonomic dictionaries are typically created as extensions (or replacements) of the general purpose taxonomic dictionary.
  2. The creation of collections of Knowledge Models for expressing knowledge about kinds of things in a computer interpretable and reusable form.
  3. The expression of general requirements about kinds of things in the form of Requirements Models. Such requirements models can be used to guide designs, and they can also be used to verify designs or delivered products against requirements that are expressed in a formal language.
  4. The creation of Product and Process Models, including also models of complete facilities and their documentation, Building Information Models (BIM's), etc. Such models may include data and documents about individual objects, including data and documents about designs of objects as well as about realized facilities and their operation and maintenance.
  5. Integrated models include also a taxonomic dictionary and language definition (which enable searching for things of specified kinds as well as definitions of those kinds) and the integration with knowledge and requirements (for reuse and verification of knowledge and requirements).
  6. The exchange of messages, including queries, answers and statements between Gellish enabled software, for a A Gellish based semantic data exchange (Semantic Web).

The Gellish Modeling Methodology improves conventional data modeling methods in various respects. Conventional data modeling, for example Object-Role Modeling (ORM) or Entity-Relationship (ER) modeling, do not provide a dictionary, nor do they provide standardized relation types to express facts, nor do they provide a standard database design or data structure. As a consequence the various models that result from the application of conventional methods are implemented as different dedicated databases, so that every supplier created its own database structure. Such databases are all mutually incompatible, whereas data that is stored in one database can only be transferred to other data stores by the creation of costly conversion and interfacing software. This problem can be solved by using the Gellish Modeling Methodology using a standard formalized language and its predefined dictionary of concepts, including its standardized kinds of relations. Thus it enable to create knowledge and information models in a standard universal Gellish Database or in messages with a standard expression format. When conceptual data models are expressed as knowledge models in formalized languages and when they are stored in a universal Gellish datastructure, then they can be used directly to guide the creation of information models about individual objects. Furthermore, that data can also be stored directly in a standard Gellish Database without the need to create a dedicated database structures. This is enabled by the fact that each Gellish Database consists of one or more of the same universally applicable standard database tables. This general applicability eliminates the need to create dedicated database designs for new applications. As a consequence it is not required anymore to convert the conceptual data models into physical data models for creating a database structure. This also opens the possibility to create software that can operate on database independent queries on any Gellish Database or on the combined content of multiple Gellish Databases as well as on any Gellish exchange message.

2. The Gellish family

Each formal languages in the Gellish family of formalized languages is a generally applicable and formal subset of a natural language and uses the same universal, neutral and system independent data structure. The family of languages is designed to enable people and computers to express, store, exchange and integrate information, knowledge, requirements, queries and responses as well as the language definition itself without the need for costly data conversions and interfaces between systems.

2.1 Formal languages

A Gellish formal language is primarily defined as a structured subset of a natural language, for English the resulting language is called Formal English. However, the formal language definitions are based on the understanding that words and phrases in natural languages are representations of concepts and things that are language independent. Therefore, each concept or thing in a formal language has a language independent unique identifier (UID) that represents the concept or the thing as such in any of the languages of the family. In addition to that, each concept or thing can be denoted by multiple terms ('names'), synonyms and abbreviations in any language and language community. This enables automated translation of expressions between different languages. It means that facts that are expressed in one language do not need to be translated to other languages, as a computer is able to present such a fact in any language for which a formal dictionary is available.
This document primarily describes Formal English, but for any other language variant you may replace the word English by the name of that other language. So, Formal English is a formal structured subset of natural English, in the same way as the Dutch variant (Gellish Nederlands) is a subset of the Dutch language. Other formal language variants are in a similar way subsets of other natural languages.

Formalized languages are intended to facilitate standardization of data in databases, and to provide a universal data structure for data exchange and for a generally applicable database capability. Their main advantages over conventional information and knowledge modeling methods with free (undefined) languages are:

  • Their data structure is universal and flexible and can be extended without software changes or database definition changes, whereas conventional data structures are fixed and inflexible.
  • They are open languages in which any semantically correct information or knowledge can be expressed, whereas conventional database structures only allow for data for which the system was designed.
  • They are defined in an extensive formal taxonomic dictionary of concepts and relation types in the form of a taxonomy / ontology, which eliminates ambiguity and causes that data from different sources can easily be integrated, whereas conventional databases usually don't use standard concepts for their definition, nor for their content.
  • They are open for (ad hoc) extensions and system independent, whereas most data structures and content standards are closed, application software dependent and proprietary.
  • They have automated translation capabilities, uses normal natural language terminology and expressions and do not use a separate meta language for their definition, whereas conventional systems need ad hoc translations and require the use of a separate meta language for their definition and are usually expressed in 'programmers language'.

The Gellish formalized languages are based on the principle that knowledge and information can be expressed as a collection of relations, whereas each related thing plays its own role in a relation. Each relation has the same structure, being two or more Relation - Role - Player combinations. Groups of elementary relations can be combined into expressions (small sentences) that are basically the same in any natural language. Each such expression has the form of an object-relation-object (ORO) structure. Examples of the core of such formal language expressions (without UID's and auxiliary facts) are the knowledge:

  • car <can have as part a> turbine

and the requirement:

  • car <shall have as part a> engine

and the product information:

  • the Eiffel tower <is located in> Paris

Such formal expressions use standardized phrases for the kinds of relations. Those phrases are selected from the formal taxonomic dictionary. The expressions also use standard terms for kinds of things, which shall be selected also from the taxonomic dictionary or from a private or public domain extension of that dictionary. Te names of individual things are introduced and added to an ad hoc dictionary by adding classification relations, as will be discussed later. The standardization of terminology and definitions makes languages into formal languages and that enables that formal expressions can be directly integrated with other formal expressions (without a need for conversion) and it makes that the expressions can be interpreted by computers.

The Gellish formalized languages are also capable to express questions, answers, confirmations, denials and other communicative intents. Therefore, formal languages do not need special query languages. Gellish Databases can thus be queried via queries that are expressed in a formal language. This is further described in the section Querying formal language databases.

A formal dictionary defines the concepts and terminology of the language, including also phrases that denote kinds of relations. Each concept and each relation type is defined as a subtype of a more general concept or relation type. This means that the concepts and relation types are defined and arranged in a subtype-supertype hierarchy, also called a Taxonomy. This means that the subtypes inherit the definitions of their supertypes. A consequence of the Taxonomy structure is that formal expressions can be automatically verified on their consistency and grammatical correctness.

The taxonomic dictionary of kinds of relations can be consulted on-line via relation types is shown in the sheet called 'Gellish English' of the TOPini spreadsheet file of the Gellish English Dictionary. For searching for specific relation types or concepts and for viewing their hierarchy it is recommended to use a Gellish Browser (This Wiki is not suitable to represent that hierarchy, so that the Appendices only present an alphabetic flat list of relation types).

2.2 The Gellish syntax, a standard data structure

Gellish includes a definition of a standard universal data structure for databases and for exchange messages and queries. This means that from an information technology perspective, Gellish can be regarded as a large integrated data model that is flexible and generally applicable and can be implemented in one or more identical database tables. It is flexible, because its application scope and semantic expression capabilities can be extended without a modification of the Gellish data structure. It is generally applicable, because it has generally applicable standard relation types and embedded domain specific knowledge from various discipline areas, which relation types and knowledge can be easily extended to other domain areas.
This means that Gellish expressions can be stored in universal Gellish Databases and can be exchanged between systems via Gellish Messages that use a standardized Gellish interface. The universal data structure is defined in 'Definition of Universal Databases and Messages', available via the Gellish Download area.

3. Formal English

3.1 Structured Formal English

Gellish English uses terminology from the natural English, nevertheless Gellish may also be called a formal language that is computer interpretable, because it limits the language to a formally defined, and computer interpretable subset of a natural language. However, Gellish English does not define its own vocabulary, but uses the English vocabulary that is defined in the electronic Gellish English Dictionary or in user defined Domain Dictionaries. Thus the Gellish English Dictionary provides standardized terminology that can be used as a 'common language' in application systems. Typically it can be used to enhance conventional databases by standardizing their content and thus simplifying data integration and data exchange between systems. For example, the standard terminology and concept definitions can be used for standardizing the content of multiple implementations of systems, such as ERP, PLM and EDMS systems, that need to share or exchange data.

3.2 The Formal English Dictionary

The smart Gellish Formal English Dictionary-Taxonomy is an electronic normal English dictionary that is extended with additional knowledge. All definitions and knowledge in the dictionary is expressed as computer interpretable relationships between the concepts in the dictionary. Most of the relations are specialization relations that specify that the concepts are subtypes of their supertype concepts. This results in a subtype-supertype hierarchy, so that the concepts are arranged in a taxonomy. The other additional relations between concepts provide additional knowledge about the defined concepts and thus make it an ontology. Because the relations are computer interpretable, the Gellish dictionary becomes a ‘smart dictionary’.
The Root Segment of the Gellish English dictionary includes definitions of the standard relation types. The definitions of those relation types and the definition of the related kinds of roles and kinds of role players form an upper ontology or world ontology. That section defines the semantics of the Gellish expressions. The Root Segment contains the generic concepts that are the top concepts that can be further specialized in the various domain ontologies. The Root Segment therefore acts as the integrator of the Domain Dictionaries.

The standard Gellish English Dictionary-Taxonomy consists of a root section (or TOPini section) with a number of branch sections, called Domain Dictionaries-Taxonomies. Usage of Gellish requires the use of the TOPini root section and may use one or more standard Gellish Domain Dictionaries-Taxonomies, or may use 'proprietary Domain Dictionaries.

Examples of standard Gellish Domain Dictionaries-Taxonomies are:

  • Units of Measure
  • Activities, Events and Processes
  • Physical objects of various kinds, such as:
  • - Static equipment, civil, process units and piping
  • - Electrical and Instrumentation, Control and Valves
  • - Rotating equipment, Transport equipment and Solids Handling
  • Aspects, Properties, Qualities and Roles
  • Materials of constructions, Fluids and Waves
  • Documents and Identification, Symbols and Annotation
  • Geographic objects, Lifeforms and Organizations
  • Mathematics, Geometry and Shapes

Users and Organizations are invited to propose extensions of the Root Segment or the standard Domain Dictionaries-Taxonomies and are invited to develop Domain Dictionaries-Taxonomies for their own application domain and to propose to certify their Domain Dictionaries-Taxonomies as approved proprietary or public Gellish Domain Dictionary-Taxonomy.

4. Usage of formal languages

There are basically four kinds of usage of formal languages:

  1. Usage as a Dictionary and/or Taxonomy
  2. Usage as a Language e.g. to create dictionaries or taxonomies, to model knowledge, to specify requirements, to describe designs or real world facilities or to manage information.
  3. Usage as a Data Modeling language
  4. Usage as a Query language

4.1 Usage as a Dictionary

Gellish English is defined in the electronic Gellish Formal English Dictionary-Taxonomy. That dictionary can be used either in stand-alone mode via Gellish Dictionary browser software (such as the Gellish Browser ) or by incorporating the dictionary (or a subset of it) as standard reference data in one or more application systems.

Examples of usage of the Gellish English Dictionary are:

  1. Usage for Data Standardization and common terminology in order to harmonize data in databases in various systems in a company or in an industry. For example, standardize the classification of equipment and their properties, or to standardize document types e.g. in ERP systems, design systems, maintenance systems or document management system.
  2. Usage for the standardization of keywords in document management systems.
  3. Usage to improve search engines for retrieval of information by using the Gellish dictionary terms and synonyms (with possible private extensions) as the basis for allocation of keywords and for the keyword search, while using the taxonomy (subtype-supertype hierarchy) of kinds of things (classes) in the Gellish Taxonomy to find also information that is classified by subtypes of terms.

Usage of the Gellish English dictionary may include not only usage of names and textual definitions, but possibly also the usage of the subtype-supertype hierarchy relations and possible also the facts that express what is definition true for a defined concept.

Application that use only the dictionary may select from the Gellish Dictionary Database only the lines that define concepts and the lines that define synonym names for those concepts. Those lines can be recognized on the relation types which they use, because those lines contain only relation types that are indicated by the following Gellish phrases:

  • is a specialization of - Such a line defines a concept as being a subtype of another concept and provides a textual definition for the concept.
  • is a qualification of - Such a line defines that a qualitative or quantitative aspect <is a qualification of> a conceptual aspect. For example, red <is a qualification of> color, and ASTM 317 <is a qualification of> stainless steel.
  • is a synonym of
  • is an abbreviation of

These relation types are also some of the standard relation types that are used to extend the Dictionary with the definition of additional concepts. Guidelines for the extension of the Dictionary are given in the Gellish English Dictionary Extension Manual. A summary of those guidelines is provided in the rules for proper definitions of new concepts and rules for names of concepts.
If you need only a subset of the concepts in the Dictionary then it is nevertheless recommended to import the whole taxonomy, but to mark only those concepts that will be visible to users. This will simplify to upgrade to newer releases of the Gellish English Dictionary and will support the inclusion of private extensions.

4.2 Usage as a Language

Using Gellish as a language to create a Gellish Databases includes the usage to describe any or all of:

  • Individual objects, their components, properties and behavior.
  • Designs of facilities or real world structures or to manage information about a facility; typically by creating a Facility Information Model or a Building Information Model (BIM).
  • Business processes, transactions and other activities, such as processes that are typically described by graphical methods such as IDEF0 and DEMO.
  • Physical or chemical processes, including fluid or solid product streams.
  • Definitions of concepts and their relations to other concepts, to create smart Dictionaries, Taxonomies and Ontologies.
  • Knowledge by creating Knowledge Models that can be re-used to guide designs or to verify designs.
  • Requirements for projects or products or standard specifications of kinds of things, such as included in product catalogs.
  • Etc.

Usage of the Gellish English language for the modeling of information and knowledge implies that individual things are classified by concepts from the Gellish Dictionary, and in addition to that it implies that standard relation types are used for making expressions of the kind Object-Relationtype-Object (ORO). This is illustrated in the figure below.

The figure illustrates the architecture of a Facility Information Model and its main sections. The left hand section of the figure illustrates a model of a facility, in this example an LNG plant. The facility is decomposed in components, using part-whole relations. The components have properties and can be related to each other. The components can also be related to processes and activities by relations that indicate the way in which they are involved. Each element in the facility model can also be related to one or more documents in a collection of document models, being the second section of the Facility Information Model. These relations in a Gellish model enable to build powerful search engines or product life cycle and document management systems (PLM's and EDMS's) that can use the structure of the facility model to find documents about the facility components. Each element of the facility model and each document is also related by a classification relation to a concept (a class) in the Gellish Dictionary that is the section on the right hand side of the figure. These relations enable to use the structure of the smart dictionary to find documents and requirements that are applicable for components that are classified by such a concept. Finally, the third section illustrates the expression of requirements about kinds of things, in the form of relations between concepts in the Gellish dictionary. Note that the classification relations determine which requirements are applicable to which objects in the facility model.

Alltogether the figure illustrates the following ways to use the full Gellish language:

  • To express knowledge for its storage, retrieval and for the exchange of knowledge between application systems.
  • To express requirements and standard specifications for facilities and products and for the required delivery of data and documents.
  • To model facilities and their components and products (product modeling or product design ) for the storage, retrieval and exchange of data and documents about them, such as in product catalogs.
  • To verify designs or to verify observed real world objects against requirements and specifications.
  • To create Facility Information Models or to express business transactions, measured data, or any other information about facilities and their components as an integration of information from various sources in a central or decentralized distributed database.

Depending on these kinds of usage a different subset of standard Gellish relation types is applicable. Those subsets of the available relation types are described in the various parts of the Gellish Modeling Method.
For example:
Requirements specifications mainly use relation types that specify relations between kinds of things that specify facts that shall be the case. Such relation types are typically indicated by phrases that start with 'shall be…' or shall have…'. Definitions describe facts that are by definition the case. Therefore, definition models include relation type phrases that begin with 'has by definition…' or 'is by definition…'. For example, in Gellish we can specify that a pump shall have a shaft and shall have a volumetric capacity as follows:

Name of left hand object Name of relation type
pump shall have as part a
pump shall have as aspect a

Product descriptions and operational facilities mainly use relation types that specify relations between individual things and classification relations that specify that an individual thing is related to a kind of thing (a class). These kinds of relation types typically start with 'is a…' or 'has a…', whereas the classification relation is expressed by the phrase 'is classified as a'. For example, the information that P-1001 is a pump that has a capacity of 5 dm3/s is described in Gellish as follows:

Name of left hand object Name of relation type Name of right hand object
P-1001 is classified as a pump
P-1001 has as aspect capacity of P-1001
capacity of P-1001 is classified as a capacity (volume flow rate)
capacity of P-1001 is quantified on scale as 5

Note that the relation types and the concepts pump, capacity (volume flow rate), 5 and dm3/s are all standard Gellish English concepts that are selected from the dictionary. The other objects, P-1001 and capacity of P-1001 are private objects that are introduced in the Gellish language by their classification relations.

A more extensive description of an architecture for Facility Information Models, Building Information Models, etc. is provided in the document Gellish Modeling Methodology, Part 1 - Architecture.

4.3 Usage as Data Modeling language

Using the Gellish English language to specify data models, thus using it as a data modeling language. This will result in Gellish English conceptual data models, being data models that are expressed using the relation types that are standardized in Gellish and that use the concepts that are already defined in the Gellish Dictionary or their proprietary extending where necessary. Data models expressed in Gellish have several advantages, such as that they are documented in a database table, they are extensible and they can be directly used by software to guide the creation of data instances, without the need for the design of a physical data model.

4.4 Usage as a Query language

Using the Gellish language to Query a Gellish Database or to communicate in dialogs about transactions with requests, promises, statements, etc., thus using Gellish English as a query language or as a business communication language.

5. Universal Databases and Messages

Gellish Databases are universal semantic databases that enable the storage of virtually any data. They can contain any number of identical database tables. Therefore Gellish Database systems have a universal table structure, which makes them generally applicable and extendable without the need to redefine their data structure (data model). All Gellish databases have as common characteristic that they enable to store any knowledge and information that can be expressed in the Gellish English language. They also have as common characteristic that they have the capability to import and integrate data that are expressed in the form of the content of other Gellish Expression Tables.

Gellish Messages and Queries can be exchanged between computer systems, using a standard data exchange protocol, such as the SOAP protocol. Such a message consists of an envelop, a header and a body. The body is formed by a collection of Gellish expressions, similar to rows in a Gellish Expression Table. When the SOAP protocol is used, the Gellish message or Query is exchanged in XML format. Such messages can be sent as a query or as a response in peer to peer networks of Gellish enabled applications to query a central database or a decentralized distributed database.

Data integration requires the use of a common language, which includes a common dictionary of concepts and relation types. Therefore it is important that users of Gellish should have the discipline to obey the rules for correct Gellish. You should carefully evaluate whether new concepts, especially relation types, are really needed or that existing concepts are already available in the Gellish Dictionary. If you think that a new concept is really required, then you are strongly recommended to provide feedback and to propose your extensions as enhancements of the Gellish Dictionary-Taxonomy.

6. Gellish Domain Dictionaries

The use of Gellish requires at least the use of the TOPini section, which defines the core of the Gellish language (its 'Upper Ontology') and may include part or all of the other Domain Dictionaries of the full Gellish Dictionary-Taxonomy, possibly extended with proprietary defined concepts or Domain Dictionaries-Taxonomies.
Parties may wish to develop and use their own (proprietary) Domain Dictionary-Taxonomy and combine that with the concepts that are defined in the upper ontology of Gellish (the TOPini section), and may use one or more standard Gellish English Domain Dictionaries (such as the Units of Measure Domain Dictionary) or nothing at all of the remainder of the Gellish English Dictionary-Taxonomy.
The Gellish Modeling Method provides guidelines on how to create such Gellish compliant Domain Dictionaries-Taxonomies and how to manage the Unique Identifiers (UID's).

The use of proprietary Gellish Domain Dictionaries is convenient and fast, because of the familiarity of its users with their own dictionary. However, the use of proprietary Gellish Domain Dictionaries has two main risks:

  1. Your Domain Dictionary may overlap or conflict with other Gellish Domain Dictionaries. This means that data integration may still be a problem when you want to communicate with systems that are not familiar with your Domain Dictionary. So you cannot simply integrate data from other parties that use a different Domain Dictionary.
  2. Your Domain Dictionary may contain concepts that are not subtypes of the concepts in the Gellish Root section (TOPini). This is against one of the basic Gellish rules and causes that the correctness and consistency of the Gellish expressions cannot be verified.

For example, not using the full Gellish Dictionary-Taxonomy means that the power of the Gellish taxonomy is not utilized and thus that the benefits of the inheritance capabilities, searching on subtypes and semantic verification possibilities), the synonyms, the definitions and the distinctions between objects and their roles, the standard units of measure and their conversions, etc. are not used.

To avoid these risks of overlap or isolation it is recommended define synonym relations between your own terminology and equivalent names in the Gellish Dictionary that denote the same concepts. This is especially useful when your domain dictionary or the terminology in one or more of your systems is a subset (or translation) of the standard Gellish English Dictionary.
Synonyms can be defined as part of an ordinary Gellish Database table that is part of your Domain Dictionary. Such a Synonym Table should use your Domain name as 'Language Community' and should contain synonym relation types that relate your names to the names from the standard Gellish Dictionary, whereas your concepts are identified by the UID's of the concepts in the standard Gellish Dictionary. For example:

Language Language community Name of left hand object Name of relation type Name of right hand object
English SAP ME_PUM is a synonym of pump
English SAP P is an abbreviation of pump
German SAP Pumpe is a translation of pump

It is also possible to state that a name in your context <is the same as> the same name in the general context of the standard Gellish Dictionary.
You can then add proprietary subtype concepts where necessary.
Examples of such Synonym Tables are available for the ISO 15926-4 Domain Dictionary terminology. Several companies developed such Gellish Synonym Database tables. For example, Synonym tables were made for terminology in various database implementations, such as equipment types and property types in various SAP implementations for maintenance and inspection. In fact in such cases the Synonym table indicates which subset of the standard Gellish Dictionary is used in the application.
A possible implementation could then even use the full Gellish dictionary/taxonomy at the background, while the software only shows the proprietary synonyms of the subset to the users, together with possible proprietary extensions.
Examples of Gellish Domain Dictionaries are the Civil Engineering Domain Dictionary and the Building and Construction Domain Dictionary (in Dutch and English).

7. Gellish in XML and RDF / Notation 3

In Gellish the expression of each main fact accompanied by a number of auxiliary facts. That is the reason why a Gellish Database table consists of a large number of standard columns, although the expression of a main fact basically only requires 3 columns.

Auxiliary facts are for example, facts about the used language, the context for naming and validity, the status, the originator, the date of creation and modification of a fact, unique identifiers, etc. All those auxiliary facts can be expressed on one row in a Gellish Database or data exchange file or message.

A representation of “Gellish in XML” is defined in a free available XML Schema. An XML file with data according to that Schema is recommended to have as file extension GML, whereas GMZ stands for “Gellish in XML zipped”.

Users may wish to ignore some or all of the auxiliary facts in their implementation. For that reason standard subsets of columns are defined as is described in the “The Gellish Database Definition” document (see the Download area of this website). The smallest subset is a triple, which includes a left hand object name, a relation type name and a right hand object name. (In RDF those three components are called subject, property and object). Applications that do not require the implementation of the full set of auxiliary facts can use one of the subsets. Each subset table can be represented in XML or RDF / Notation 3 using a subset of the above XML Schema definition.

8. Development and maintenance of formal languages

Gellish English is developed and maintained as an International Industry Standard by an Open Source project, headed by Dr. Ir. Andries van Renssen at Shell and at the Delft University of Technology, together with a team of domain experts from several international companies. Users of Gellish who want to extent the Gellish Dictionary of concepts and relation types are invited to submit their proposals for additions to the Gellish English dictionary or another language variant.
Gellish is in use for a large variety of applications, including facility design, plant data integration, database content harmonization, knowledge storage and retrieval, electronic product catalogs, database prototyping and development, etc.
Gellish English is a combination and significant extension and at the same time a simplification of the concepts defined in ISO data model standards ISO 10303-221 (AP221) and ISO 15926, especially part 2, 3 and 4 and includes enhanced concept definitions from many other standards. A project is in progress to transform Gellish into an ISO standard, thus becoming ISO 15926-11.

9. Gellish Documentation

For the description of some core concepts of Gellish see the page on Basic Principles of Gellish. Extensive guidance is provided in the documentation that is described below and can be provided by organizations that support the use of Gellish and the Gellish Modeling Method. Explanation of the interpretation of Gellish expressions and of the standard Gellish relation types is given on the page Developing Gellish enabled software.

The Gellish website (Downloads page) contains a number of documents about Gellish, arranged in three packages:

Package 1: The Gellish English Dictionary-Taxonomy - Gellish EN

This includes

  • The Gellish English Dictionary-Taxonomy (earlier called STEPlib). The electronic Gellish Dictionary-Taxonomy includes an advanced English Dictionary, that contains explicit relations between the defined concepts. It also includes the Gellish English language definition (its grammar) in the form of a computer interpretable table (the TOPini section). It consists of a number of Gellish Data tables presented in MS Excel files. The tables can be combined in one Gellish Database and imported in any database that is compliant with the Gellish Database definition data storage capabilities.

Package 2: Examples

This includes

  • An example of a Road (in English and in Dutch). - The example is described in two files:

1. A document that is intended to provide a first introduction in Gellish, using the example. The document describes some knowledge about a road as well as some information about a particular road.
2. An Excel file that contains a Gellish Database table with the knowledge and information about the road as is described in the document. The example also illustrates as follows how Gellish enables automated translation. The English version of the database expresses the knowledge and information in Gellish English and includes a translation of the terms (the names of the concepts) to Dutch. That is sufficient for software to present the knowledge and information in Dutch as well, whereas it is not needed to express the facts in Gellish Dutch again. The inverse is the case for the Gellish Dutch version of the database.

  • An example of Lubrication System. This Gellish Database consists of three tables, one with knowledge, one with requirements and one with the design of a part of a particular (individual) lubrication system.

Package 3. Gellish Documentation

  • A presentation about Gellish.
  • Gellish Database Definition - This document defines the standard Gellish Database table and the meaning of the columns in such a table. Such tables can be implemented as database tables or can be exchanged as a computer interpretable files.
  • The Gellish Application Manual - An extensive manual on the application of Gellish with many examples.
  • A Guide on the extension of Gellish English - This document provides guidance on how to create your own Domain Dictionary or to extent the Gellish English Dictionary with your private terminology and how to raise proposals for the extension of the official Gellish Dictionary. See also the summary of the rules for a proper definition of a new concept and rules for names of concepts.
  • Guidelines on the use of Gellish English for essay writing - This document provides a list of guidelines that provide guidance on the usage of Gellish. It also contains rules to determine whether knowledge or information is expressed in a Gellish compliant way. Those rules form the basis for becoming Gellish certified, which gives the right to use the 'Gellish Powered' logo.
  • Guidelines for the creation of product catalogs in Gellish.
  • A PhD thesis and a summary of that thesis of the originator of Gellish. This provides a description of the fundamentals, the definition, development and application of Gellish as a universal data structure and ontology. See also the book 'Gellish, a Generic Extensible Ontological Language ' or its free available pdf version.

Continue with Basic principles


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