Gellish is an ontology language for data storage and communication, designed and developed by Andries van Renssen since mid-1990s.
Information and knowledge can be expressed in such a way that it is computer-interpretable, as well as system-independent and natural language independent.
For example, for the complete and unambiguous specification of business processes, products, facilities and physical processes; for information about their purchasing, fabrication, installation, operation and maintenance; and for the exchange of such information between systems, although in a system-independent, computer-interpretable and language-independent way.
To enable an unambiguous interpretation, Gellish includes the definition of a large number (more than 650) of standard relation types that determine the rich semantic expression capability of the language.
For example, the Gellish dictionary-taxonomy contains definitions of many concepts that also appear in ordinary dictionaries, such as kinds of physical objects like building, airplane, car, pump, pipe, properties such as mass and color, scales such as kg and bar, as well as activities and processes, such as repairing and heating, etc.
For example, it defines relation types such as ⟨is a subtype of⟩, ⟨is classified as a⟩, ⟨has as aspect⟩, ⟨is quantified as⟩, ⟨can be a performer of a⟩, ⟨shall have as part a⟩, etc.
Such standard relation types and concept definitions enable a Gellish-powered software to correctly and unambiguously interpret Gellish expressions.
An example of the core of a Message Table is the following: A full Gellish Message Table requires additional columns for unique identifiers, the intention of the expression, the language of the expression, cardinalities, unit of measure, the validity context, status, creation date, author, references, and various other columns.
Gellish Light only requires the three above columns, but then it does not support, for example, capabilities to distinguish homonyms; automated translation; and version management, etc.
The following example illustrates the use of some additional columns in a Gellish Message Table, where UoM stands for 'unit of measure'.
Example applications of a Gellish dictionary are usage as a source of classes for classification of equipment, documents, etc., or as standard terminology (metadata) or to harmonize data in various computer systems, or as a thesaurus or taxonomy in a search engine.
This enables Gellish expressions for queries, such as: Gellish-powered software should be able to provide the correct answer to this query by comparing the expression with the facts in the database, and should respond with: Note that the automatic translation capability implies that a query/question that is expressed in a particular language, say English, can be used to search in a Gellish database in another language (say Chinese), whereas the answer can be presented in English.
Furthermore, the subtype-supertype hierarchy in a Gellish Dictionary-Taxonomy implies that the knowledge and requirements that are specified for a kind of thing are inherited by all their subtypes.
These semantic differences cause that the various categories of information models require their own subsets of standard relation types.
Examples of auxiliary facts are: the intention, status, author, creation date, etc.
The auxiliary facts enable to specify things such as roles, cardinalities, validity contexts, units of measure, date of latest change, author, references, etcetera.
This enables the use of a single table, also for the specification and use of synonyms and homonyms, multiple languages, etcetera.
For example, it can be implemented as a SQL-based database or otherwise, as a STEPfile (according to ISO 10303-21), or as a simple spreadsheet table, as in Excel, such as the Gellish Dictionary itself.
One of the differences between Gellish and RDF, XML or OWL is that Gellish English includes an extensive English Dictionary of concepts, including also a large (and extendable) set of standard relation types to make computer-interpretable expressions (in a form that is also readable for non-IT professionals).
This attractive freedom has the disadvantage that users of 'languages' such as RDF, XML or OWL still don't use a common language and still cannot integrate data that stem from different sources.
There are many similarities between the two languages, such as the use of unique identifiers (Gellish UIDs, OWL URIs)[2] but also important differences.
So OWL does not include definitions of the terms in a natural language, such as road, car, bolt or length.
In OWL, the various terms in different languages and the synonyms are in principle different concepts that need to be declared to be the same by explicit equivalence relations (unless the alternatives are expressed in terms of the alternative label annotation properties).
OWL can be regarded as an upper ontology that consists of 54 'language constructs' (constructors or concepts).
[4] The upper ontology part of Gellish currently consists of more than 1500 concepts of which about 650 are standard relation types.