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Fig 1. Requirements of a database for an audio compact disc (CD) collection, presented in EXPRESS-G notation.

EXPRESS is a standard data modeling language for product data. EXPRESS is formalized in the ISO Standard for the Exchange of Product model STEP (ISO 10303), and standardized as ISO 10303-11.^[1]

Overview

Data models formally define data objects and relationships among data objects for a domain of interest. Some typical applications of data models include supporting the development of databases and enabling the exchange of data for a particular area of interest. Data models are specified in a data modeling language.^[2] EXPRESS is a data modeling language defined in ISO 10303-11, the EXPRESS Language Reference Manual.^[3]

An EXPRESS data model can be defined in two ways, textually and graphically. For formal verification and as input for tools such as SDAI the textual representation within an ASCII file is the most important one. The graphical representation on the other hand is often more suitable for human use such as explanation and tutorials. The graphical representation, called EXPRESS-G, is not able to represent all details that can be formulated in the textual form.

EXPRESS is similar to programming languages such as Pascal. Within a SCHEMA various datatypes can be defined together with structural constraints and algorithmic rules. A main feature of EXPRESS is the possibility to formally validate a population of datatypes - this is to check for all the structural and algorithmic rules.

EXPRESS-G

EXPRESS-G is a standard graphical notation for information models.^[4] It is a companion to the EXPRESS language for displaying entity and type definitions, relationships and cardinality.^[5] This graphical notation supports a subset of the EXPRESS language. One of the advantages of using EXPRESS-G over EXPRESS is that the structure of a data model can be presented in a more understandable manner. A disadvantage of EXPRESS-G is that complex constraints cannot be formally specified. Figure 1 is an example. The data model presented in figure could be used to specify the requirements of a database for an audio compact disc (CD) collection.^[2]

Simple example

Fig 2. An EXPRESS-G diagram for Family schema

A simple EXPRESS data model looks like fig 2, and the code like this:

SCHEMA Family;



ENTITY Person

   ABSTRACT SUPERTYPE OF (ONEOF (Male, Female));

     name: STRING;

     mother: OPTIONAL Female;

     father: OPTIONAL Male;

END_ENTITY;



ENTITY Female

   SUBTYPE OF (Person);

END_ENTITY;



ENTITY Male

   SUBTYPE of (Person);

END_ENTITY;



END_SCHEMA;

The data model is enclosed within the EXPRESS schema Family. It contains a supertype entity Person with the two subtypes Male and Female. Since Person is declared to be ABSTRACT only occurrences of either (ONEOF) the subtype Male or Female can exist. Every occurrence of a person has a mandatory name attribute and optionally attributes mother and father. There is a fixed style of reading for attributes of some entity type:

a Female can play the role of mother for a Person

a Male can play the role of father for a Person

EXPRESS Building blocks

Datatypes

EXPRESS offers a series of datatypes, with specific data type symbols of the EXPRESS-G notation:^[2]

Entity data type: This is the most important datatype in EXPRESS. It is covered below in more detail. Entity datatypes can be related in two ways, in a sub-supertype tree and/or by attributes.

Enumeration data type: Enumeration values are simple strings such as red, green, and blue for an rgb-enumeration. In the case that an enumeration type is declared extensible it can be extended in other schemas.

Defined data type: This further specializes other datatypes—e.g., define a datatype positive that is of type integer with a value > 0.

Select data type: Selects define a choice or an alternative between different options. Most commonly used are selects between different entity_types. More rare are selects that include defined types. In the case that an enumeration type is declared extensible, it can be extended in other schemas.

Simple data type
- String: This is the most often used simple type. EXPRESS strings can be of any length and can contain any character (ISO 10646/Unicode).
- Binary: This data type is only very rarely used. It covers a number of bits (not bytes). For some implementations the size is limited to 32 bit.
- Logical: Similar to the boolean datatype a logical has the possible values TRUE and FALSE and in addition UNKNOWN.
- Boolean: With the boolean values TRUE and FALSE.
- Number: The number data type is a supertype of both, integer and real. Most implementations take uses a double type to represent a real_type, even if the actual value is an integer.
- Integer: EXPRESS integers can have in principle any length, but most implementations restricted them to a signed 32 bit value.
- Real: Ideally an EXPRESS real value is unlimited in accuracy and size. But in practice a real value is represented by a floating point value of type double.

Aggregation data type: The possible kinds of aggregation_types are SET, BAG, LIST and ARRAY. While SET and BAG are unordered, LIST and ARRAY are ordered. A BAG may contain a particular value more than once, this is not allowed for SET. An ARRAY is the only aggregate that may contain unset members. This is not possible for SET, LIST, BAG. The members of an aggregate may be of any other data type.

A few general things are to be mentioned for datatypes.

Constructed datatypes can be defined within an EXPRESS schema. They are mainly used to define entities, and to specify the type of entity attributes and aggregate members.

Datatypes can be used in a recursive way to build up more and more complex data types. E.g. it is possible to define a LIST of an ARRAY of a SELECT of either some entities or other datatypes. If it makes sense to define such datatypes is a different question.

EXPRESS defines a couple of rules how a datatype can be further specialized. This is important for re-declared attributes of entities.

GENERIC data types can be used for procedures, functions and abstract entities.

Entity-Attribute

Entity attributes allow to add "properties" to entities and to relate one entity with another one in a specific role. The name of the attribute specifies the role. Most datatypes can directly serve as type of an attribute. This includes aggregation as well.

There are three different kinds of attributes, explicit, derived and inverse attributes. And all these can be re-declared in a subtype. In addition an explicit attribute can be re-declared as derived in a subtype. No other change of the kind of attributes is possible.

Explicit attributes are those with direct values visible in a STEP-File.

Derived attributes get their values from an expression. In most cases the expression refers to other attributes of THIS instance. The expression may also use EXPRESS functions.

Inverse attributes do not add "information" to an entity, but only name and constrain an explicit attribute to an entity from the other end.

Specific attribute symbols of the EXPRESS-G notation:^[2]

Supertypes and subtypes

An entity can be defined to be a subtype of one or several other entities (multiple inheritance is allowed!). A supertype can have any number of subtypes. It is very common practice in STEP to build very complex sub-supertype graphs. Some graphs relate 100 and more entities with each other.

An entity instance can be constructed for either a single entity (if not abstract) or for a complex combination of entities in such a sub-supertype graph. For the big graphs the number of possible combinations is likely to grow in astronomic ranges. To restrict the possible combinations special supertype constraints got introduced such as ONEOF and TOTALOVER. Furthermore, an entity can be declared to be abstract to enforce that no instance can be constructed of just this entity but only if it contains a non-abstract subtype.

Algorithmic constraints

Entities and defined data types may be further constrained with .mw-parser-output .monospaced{font-family:monospace,monospace}WHERE rules. WHERE rules are also part of global rules. A WHERE rule is an expression, which must evaluate to TRUE, otherwise a population of an EXPRESS schema, is not valid. Like derived attributes these expression may invoke EXPRESS functions, which may further invoke EXPRESS procedures. The functions and procedures allow formulating complex statements with local variables, parameters and constants - very similar to a programming language.

The EXPRESS language can describe local and global rules.
For example:

 ENTITY area_unit

   SUBTYPE OF (named_unit);

 WHERE

   WR1: (SELFnamed_unit.dimensions.length_exponent = 2) AND

        (SELFnamed_unit.dimensions.mass_exponent = 0) AND

        (SELFnamed_unit.dimensions.time_exponent = 0) AND

        (SELFnamed_unit.dimensions.electric_current_exponent = 0) AND

        (SELFnamed_unit.dimensions.

          thermodynamic_temperature_exponent = 0) AND

        (SELFnamed_unit.dimensions.amount_of_substance_exponent = 0) AND

        (SELFnamed_unit.dimensions.luminous_intensity_exponent = 0);

 END_ENTITY; -- area_unit

This example describes that area_unit entity must have square value of
length. For this the attribute dimensions.length_exponent must be equal to 2 and all other exponents of basic SI units must be 0.

Another example:

 TYPE day_in_week_number = INTEGER;

 WHERE

   WR1: (1 <= SELF) AND (SELF <= 7);

 END_TYPE; -- day_in_week_number

That is, it means that week value cannot exceed 7.

And so, you can describe some rules to your entities. More details on the given examples can be found in ISO 10303-41

References

This article incorporates public domain material from the National Institute of Standards and Technology website http://www.nist.gov.

^ ISO 10303-11:2004 Industrial automation systems and integration -- Product data representation and exchange -- Part 11: Description methods: The EXPRESS language reference manual

^ ^a^b^c^d Michael R. McCaleb (1999). "A Conceptual Data Model of Datum Systems". National Institute of Standards and Technology. August 1999.

^ ISO International Standard 10303-11:1994, Industrial automation systems and integration — Product data representation andexchange — Part 11: Description methods: The EXPRESS language reference manual, International Organization for Standardization, Geneva, Switzerland (1994).

^ 4 EXPRESS-G Language Overview. Accessed 9 Nov 2008.

^ For information on the EXPRESS-G notation, consult Annex B of the EXPRESS Language Reference Manual (ISO 10303-11)

v t e ISO standards .mw-parser-output .nobold{font-weight:normal} by standard number
List of ISO standards / ISO romanizations / IEC standards
1–9999	1 2 3 4 5 6 7 9 16 17 31 -0 -1 -2 -3 -4 -5 -6 -7 -8 -9 -10 -11 -12 -13 128 216 217 226 228 233 259 269 302 306 361 428 500 518 519 639 -1 -2 -3 -5 -6 646 657 668 690 704 732 764 838 843 860 898 965 999 1000 1004 1007 1073-1 1155 1413 1538 1629 1745 1989 2014 2015 2022 2033 2047 2108 2145 2146 2240 2281 2533 2709 2711 2720 2788 2848 2852 3029 3103 3166 -1 -2 -3 3297 3307 3601 3602 3864 3901 3950 3977 4031 4157 4165 4217 4909 5218 5426 5427 5428 5725 5775 5776 5800 5964 6166 6344 6346 6385 6425 6429 6438 6523 6709 6943 7001 7002 7010 7027 7064 7098 7185 7200 7498 -1 7637 7736 7810 7811 7812 7813 7816 7942 8000 8093 8178 8217 8373 8501-1 8571 8583 8601 8613 8632 8651 8652 8691 8805/8806 8807 8820-5 8859 -1 -2 -3 -4 -5 -6 -7 -8 -8-I -9 -10 -11 -12 -13 -14 -15 -16 8879 9000/9001 9036 9075 9126 9141 9227 9241 9293 9314 9362 9407 9506 9529 9564 9592/9593 9594 9660 9797-1 9897 9899 9945 9984 9985 9995
10000–19999	10005 10006 10007 10116 10118-3 10160 10161 10165 10179 10206 10218 10303 -11 -21 -22 -28 -238 10383 10487 10585 10589 10646 10664 10746 10861 10957 10962 10967 11073 11170 11179 11404 11544 11783 11784 11785 11801 11898 11940 (-2) 11941 11941 (TR) 11992 12006 12182 12207 12234-2 13211 -1 -2 13216 13250 13399 13406-2 13450 13485 13490 13567 13568 13584 13616 14000 14031 14224 14289 14396 14443 14496 -2 -3 -6 -10 -11 -12 -14 -17 -20 14644 14649 14651 14698 14750 14764 14882 14971 15022 15189 15288 15291 15292 15398 15408 15444 -3 15445 15438 15504 15511 15686 15693 15706 -2 15707 15897 15919 15924 15926 15926 WIP 15930 16023 16262 16612-2 16750 16949 (TS) 17024 17025 17100 17203 17369 17442 17799 18000 18004 18014 18245 18629 18916 19005 19011 19092 (-1 -2) 19114 19115 19125 19136 19407 19439 19500 19501 19502 19503 19505 19506 19507 19508 19509 19510 19600 19752 19757 19770 19775-1 19794-5 19831
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EXPRESS (data modeling language)

Contents

Overview

EXPRESS-G

Simple example

EXPRESS Building blocks

Datatypes

Entity-Attribute

Supertypes and subtypes

Algorithmic constraints

See also

References

Further reading

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