ISO 16354 - Guidelines on Knowledge Libraries and Object Libraries

Gellish is compliant with the ISO 16354 guidelines. The guidelines in this ISO standard aim to guide developers towards interoperability. For that purpose the standard defines a number of basic concepts for

  • Vocabularies (lists of terms)
  • Dictionaries with definitions of concepts
  • Taxonomies, which define specialization hierarchies of concepts
  • Product Models and Knowledge Models, with or without composition.

For each of those categories the standard provides minimum requirements and guidelines. Application of the guidelines will facilitate the interoperability of systems to share or communicate about items in libraries and catalogues of concepts, knowledge and products.

Modeling Time and Measurements

Time can specify a validity period of a fact or opinion, or it can specify a begin or end or duration of an occurrence.
Depending on these situations time is modeled in different ways.

Every fact (or opinion) has a validity period, also called its life time. A fact may have been the case 'always' and may last 'for ever', but it may also have a limited validity period and may change continuously, such as being a measurement of a rapid changing aspect (such as a velocity or temperature), which value is already replaced by another value within a fraction of a second. Thus not only the existence of physical objects, but also the validity period of aspect values need to be modeled and recorded.

The existence of something that appears in a data set starts its life time at the 'date-time of the start of validity' of its classification relation or specialization relation, or one of their subtypes.

The end of its existence period or validity period may be specified explicitly by specifying its date-time of latest change, which indicates the termination of its life when the change includes that the status changes into deleted or replaced or history. The time can be recorded as precise as required, because it is specified as a decimal number (according to the standard '1900 date system' notation).

Every fact in a Gellish data set has in principle an accessory fact that specifies its date-time of start of validity and an accessory fact that enables to record the date-time when its validity terminates. The latter is recorded as the date-time of latest change, in combination with a status deleted, replaced or history for facts that are not valid any more, or have been valid in the past.

In addition to that it can be specified since which date-time a fact became available in the database and at which date-time a particular copy of the expression was made.

In a Gellish Expression Table these four date-time values can be recorded in four separate columns.

In addition to that, it is possible to model the begin or end or duration of occurrences, the period (or date-time) within which something occurs. For example, a possible expression would be:

  • object-1 <has as delivery date> 21 Jan 2013.

Note that a date implies a period of 24 hours. Things that are supposed to happen at a particular moment in time are assumed to occur within a very short period in time, typically denoted by only one value. For example, When something is said to occur at 12.15 h, it means that it occurs within the duration of one second, which starts at 12.15 h. Short events typically have an unspecified duration, although their duration and possible accuracy of measurement can be specified explicitly.

Note: These ways of modeling time mean that it is not needed to create separate 'temporal part' objects for the duration of particular situations (states), such as is required for models according to ISO 15926-2. Nevertheless, Gellish also allows for the creation of temporal-part objects, called a 'physical object in state'. Logic reasoning enables to convert from one way of modeling to the other, if required.

Further guidelines on the modeling of time and measurements are given in the full article and in the Gellish Modeling Methodology Part 9, Measurements and Observations (which can be purchased via the webshop or are available for free for licensees).

Modeling of drawings and 3D shapes

A product model in 3D is a model of a physical object that includes a specification of its shape. When a 3D model is a part of a bigger assembly, such as a building, a transport system, a ship or a process plant, then the model also includes its position and orientation in a 3D space. A 3D model forms just a fraction of all the information that is typically stored about a product and the processes in which it is involved. Those other aspects include for example non-shape properties, such as materials of construction, strengths, temperatures and pressures and also relations, such as assembly relations, connection relations with other products and involvements in processes and activities. This means that 3D shape models  should be integrated in a complete set of information and knowledge about a facility. The modelled collection of all facts about a facility is called a Facility Information Model (FIM) or more specialised a Building Information Model (BIM), etc.

Data integration issues

3D product models and 2D drawings are typically created by using software packages of various suppliers. The resulting models are typically stored in the proprietary formats of those packages. For example, in DWG, DXF, CMG, DGN or RVT format. Each of such formats has its own limitations on the type of data that can be stored. Data that is stored in one format can only be converted to another formet when a single or bi-directional converter is created and when the receiving format is suitable for storing all kinds of data that is to be converted.

Non-3D related information about a facility is typically stored in other proprietary system with their own proprietary formats. For example, properties of products (1D data) may be stored in the format of ERP databases or PLM databases, whereas 2D information is usually stored in proprietary 'drawing formats'. The drawing files are typically stored as such in EDMS systems, whereas the content of the drawings is not integrated with other data in databases. The structure of the data as well as the definitions of the concepts are different in each system and in each file format. Therefore, exchange of data between systems and integration of data of different sources raises all sorts of data conversion issues.

The Gellish solution

The Gellish Modelling Method offers a solution to these data integration issues by providing a standard data structure (in Gellish Databases) as well as a standard electronic dictionary of concepts (the Gellish Dictionary/Taxonomy) that include graphical symbols and parameterized 3D shape correlations. They are all integrated in the definition of the Gellish English language and the method to apply the language to create Facility Information Models (FIMs, BIMs, etc.). Gellish is based on various ISO standards, such as ISO 10303 and ISO 15926 that include business data as well as graphical information. For example, the basic geometric concepts to describe shapes are compliant with the ISO STEP standard for geometric objects: ISO 10303-42.

Conventionally data about an object, such as the wall of a building and its construction, is stored in one or more application specific database structures. But in Gellish all data can be stored in one open standard semantic data structure. This means for example that business process oriented systems can be extended in a relative easy way with 3D shape aspects, by specifying dimensions and referring to the standard shapes that are defined in the Gellish dictionary and by positioning the shapes in the coordinate system of the assembly. 

The full article describes how to create, store and exchange any data about a facility, being 1D, 2D and 3D, in one consistent, standardised, integrated and system independent way, using the Gellish Modelling Method.

This section provides an introduction to the development of electronic Dictionaries-Taxonomies.

What is a Dictionary-Taxonomy or Ontology

A Dictionary-Taxonomy is some kind of dictionary in which the terms (lemma) have explicit relationships with other terms, whereas also the terms that are used in the definitions may be explicitly related to other terms. A Taxonomy is comparable to a Thesaurus, which traditionally is used in libraries for categorization and searching of books and documents. In a thesaurus the terms are related primarily by 'wider term - narrower term relations'. Taxonomies primarily contain 'subtype-supertype relations', also called 'specialization-generalization relations', which are a special kind of norrower term-wider term relations. If the terms in the dictionary-taxonomy are also related to each other by other kinds of relations we call the collection of expressions an ontology.

Furthermore, a smart Dictionary-Taxonomy makes a distinction between concepts and terms, because for many different terms (synonyms, abbreviations, codes, etc.) can be used to denote the same concept. Therefore, a smart Dictionary-Taxonomy will use unique identifiers (UIDs) to represent concepts and relate concepts to each other instead of terms. This enables that multiple terms are included in the dictionary to denote the same concept (possibly including possibly also terms in different languages).

With this in mind, a taxonomy can be defined more precisely as follows:
A taxonomy is a collection of concepts that are arranged in a subtype-supertype hierarchy, whereas each concept may be denoted by one or more terms (names or phrases). Furthermore, a Dictionary-Taxonomy also includes textual definitions of the concepts and is extended to become an ontology when it includes modeled definitions (also called definition models) and relationships of various kinds between the concepts that are referenced in those definition models.

This enables that multiple terms can be used to search for a particular concept and that the relations between the concepts can be used to find other concepts, definitions and also other knowledge, requirements and information about the concepts as far as is made available. The Dictionary-Taxonomy thus becomes a core access point for knowledge and information.

The latest version of the Gellish English Dictionary-Taxonomy can be purchased via the webshop. The 2008 version is free of charge available via the download area. It can be used as such, or can be used as a basis for developing proprietary extensions. It can also be used as part of the application of the Gellish Formal English language for which it is the dictionary.
Proprietary extensions typically will have the form of Domain specific Dictionaries-Taxonomies, of which the top concepts are taken from the Gellish Dictionary-Taxonomy, especially the TOPini section.

How to build a Dictionary-Taxonomy

High quality Dictionary-Taxonomies for various domains should satisfy a number of quality criteria.

The prime quality rule is that each concept shall be defined as being a subtype of another concept, which is called its supertype concept. This means that the definition of a supertype concept is also applicable to all its subtype concepts. It also means that definitions, knowledge and requirements about concepts are "inherited" to all their subtype concepts. For example, when the Gellish English Dictionary-Taxonomy contains that a motorway is a subtype of road, then software can conclude that government rules for roads in general) are also applicable for motorways. This enables that there is no need to respecify that for the subtypes of road again. Furthermore rules that only apply to motorways should be related to the concept motorway (and not to road).

Further guidelines on building high quality dictionary-taxonomies are available via the webshop, in the full article (for licensees only) and in the document: the Gellish Modeling Methodology - Part 2: Creation of Domain Dictionaries & Taxonomies. Those guidelines enable that that various domain dictionary-taxonomies can be integrated into one consistent whole, because they are made conform a consistent method, whereas they are expressed in a common language that is computer interpretable as well as system independent.

Classification and Specialization

Classification is an activity to relate an individual thing to a suitable kind of thing (a concept or a class or a type), such that the kind of thing characterizes the nature of the individual thing. The result of a classification activity is a classification relation between the individual thing and the kind of thing. Such a classification relation (a relation type) is denoted in Gellish by the standard phrase <is classified as a>. That relation type has Unique Identifier (UID) 1225.

Examples of classification relations are:

New York <is classified as a> city
M1 <is classified as a> motorway
L1 <is classified as a> length
A1 <is classified as> cleaning
John <is classified as a> man
D1 <is classified as a> inspection report
R1 <is classified as a> composition relation
John <is classified by role as a> teacher

The above examples illustrate that not only physical objects can be classified, but any individual thing, which includes also things such as products, properties, activities, processes, people, documents, units of measure, mathematical and geometric concepts, roles and even relations.

Most classification relations refer to the nature of a thing, the last example classifies John as a teacher. However, teacher is not a nature of a person, but it is an example of a (temporary) role of a person. Therefore, that is an example of a classification by role. Because of the difference in meaning between classification by nature and classification by role, the relation type that is used is different from an ordinary classification.

The definitions of the kinds of things are provided in a base Formal English Dictionary-Taxonomy. It consists of a collection of Domain Dictionaries-Taxonomies that enable the classification of individual things by Formal English concepts in a large number of domains, including also relations. Together with the standard syntax (the Gellish Expression Table) this enables computerized storage and interpretation of Formal English expressions.
As the dictionary-taxonomy is extensible with proprietary concept definitions and relations, the language becomes open and generally applicable.

Benefits of proper classification

Proper classification and concept and terminology management in organization is very practical and powerful for the following reasons:
Knowledge, requirements and documents is by definition related to the kinds of things (concepts, classes) about which they provide information. When the kinds of things and their names (terms) are included in a formal dictionary-taxonomy and when the information, knowledge and requirements are related to those concepts, then the combination becomes a knowledge base in which the kinds of things and their relations become a powerful navigation mechanisms towards definitions, knowledge and requirements about such kinds of things. Furthermore, when individual things are properly classified, then software can inform the users about information, knowledge and requirements that are applicable for those individual things.

For example, assume a dictionary-taxonomy contains a definition of the concept 'motorway' and a knowledge base contains the specification of a requirement R1 about roads and R2 specifically about motorways and a database contains the statement that M1 is a motorway. The three expressions will be as follows:

motorway <is a specialization of> road
R1 <is a requirement about a> road
R2 <is a requirement about a> motorway
M1 <is classified as a> motorway

Then software can be used to find requirements about motorways, which will result in R1 and R2, because of the definition that a motorway is a specialization of road. The software can also inform a user that R1 and R2 are applicable to M1.

Thus, by classification of individual things by concepts from a dictionary-taxonomy, it becomes explicit which definition applies and which knowledge and which requirements are applicable for all those the individual things. This makes communication less ambiguous. It also enables to apply the knowledge and requirements during design processes and its enables to use the knowledge and requirements during verification processes.

The definition of more specialized concepts, has the advantage that it becomes possible to be more specific about the allocation of knowledge and requirements that are only applicable for specific specialized subtypes. If that knowledge and requirements would be allocated to more generalized kinds of things, then it seems as if they are applicable for all the subtypes. This would cause that users are confronted with knowledge and requirements that are not applicable for their objects. The use of specialized subtypes enables to be more specific to classify things to specialized kinds and thus be selective about what is applicable and what not. Sometimes people object that this will result in too many subtypes. However, the subtype-supertype hierarchy and the inheritance mechanism enable software to hide the subtypes where necessary, so that the users are only confronted with the subtypes they need.

Classification versus Specialization

Classification relations should be distinguished from specialization relations. The first ones are relations between an individual thing and a kind of thing, whereas the latter are relations between a subtype kind and a supertype kind. A specialization relation is defined as a relation between two kinds that specifies that the subtype has all the aspects that the supertype has, whereas one or more aspects of the subtype are more constrained than that aspect of the supertype. A specialization relation is denoted in Gellish by the phrase <is a specialization of> with UID 1146. Examples of specialization relations are:

two lane road <is a specialization of> road
vacuum cleaning <is a specialization of> cleaning
man <is a specialization of> person
teacher <is a specialization of> role
customer <is a specialization of> role
red <is a qualification of> color (colour)
bar <is a qualification of> pressure scale

The above examples illustrate some relations that are used in the Gellish Dictionary-Taxonomy in various domains. The last two examples illustrate the use of a subtype of the specialization relation. Each of those qualification relations is a relation between a particular qualitative concept (red and bar) and a generic concept (colour and scale).

Classification systems

Sometimes the term classification is used to refer to the development of a classification system, being a collection of kinds of things (classes) arranged in a coherent structure, typically a hierarchy. The classes in such a classification system are intended to be used to classify individual things or to act as an entry point on a route to find knowledge (facts or documents). A Gellish Dictionary-Taxonomy is such a classification system. However, in contrast with many existing classification systems, a Gellish Dictionary-Taxonomy is a pure subtype-supertype hierarchy. A main advantage of a pure taxonomy is that the inheritance mechanism can be used, which means that all knowledge and requirements about a kind of thing is also applicable (inherited to) all the subtypes of that kind. Many other classification systems appears to be a hierarchy that is a mixture between collection relations (groupings) and subtype-supertype relations. As a consequence the inheritance mechanism does not work for such classification systems. The Gellish Modeling Methodology provides guidelines for mappings between existing classification systems and the Gellish Taxonomy. The method maintains the definition of the collections of classes and a mapping to the classes in the pure subtype-supertype hierarchy. This makes integration and combined usage perfectly feasible.

Explicit versus implicit classification relations

In the Gellish modeling methodology all classification relations are explicitly represented in a database. In conventional databases the classification relations are usually implicit. (typically they are represented by an instantiation of an entity type or attribute type). This conventional implicit classification limits and fixes the variety of classes that are used and limits the inheritance of aspects and relations from supertype classes to the ones that are predefined. Thus it also limit the application of knowledge and requirements during design and verification processes. Such a constraint does not exist in Gellish, where the number of classes is flexible.

The Gellish Domain Dictionaries-Taxonomies provide an extensible subtype-supertype hierarchy of concepts that enables a detailed classification of any kind of thing.

Full article

The full article (for licensees only) provides further guidance on how to classify products, properties, processes, documents, etc. and on the classification process and the use of knowledge and requirements about kinds of things (classes), for example in Computer Aided Design as well as in Computer Aided Verification of designs and in procurement of products.