Integration Definition for Information Modeling (IDEF1X) is a data modeling language for the development of semantic data models. IDEF1X is used to produce a graphical information model which represents the structure and semantics of information within an environment or system.FIPS Publication 184 released of IDEF1X by the Computer Systems Laboratory of the National Institute of Standards and Technology (NIST). 21 December 1993.
IDEF1X permits the construction of semantic data models which may serve to support the management of data as a resource, the integration of information systems, and the building of computer databases. This standard is part of the IDEF family of modeling languages in the field of software engineering.
Overview A data modeling technique is used to model data in a standard, consistent and predictable manner in order to manage it as a resource. It can be used in projects requiring a standard means of defining and analyzing the data resources within an organization. Such projects include the incorporation of a data modeling technique into a methodology, managing data as a resource, integrating information systems, or designing computer databases. The primary objectives of the IDEF1X standard are to provide: Means for completely understanding and analyzing an organization's data resources Common means of representing and communicating the complexity of data A technique for presenting an overall view of the data required to run an enterprise Means for defining an application-independent view of data which can be validated by users and transformed into a physical database design A technique for deriving an integrated data definition from existing data resources.
A principal objective of IDEF1X is to support integration. The approach to integration focuses on the capture, management, and use of a single semantic definition of the data resource referred to as a “conceptual schema.” The “conceptual schema” provides a single integrated definition of the data within an enterprise which is not biased toward any single application of data and is independent of how the data is physically stored or accessed. The primary objective of this conceptual schema is to provide a consistent definition of the meanings of and interrelationships between data that can be used to integrate, share, and manage the integrity of data. A conceptual schema must have three important characteristics: Consistent with the infrastructure of the business and true across all application areas Extendible, such that new data can be defined without altering previously defined data Transformable to both the required user views and to a variety of data storage and access structures.
History The need for semantic data models was first recognized by the U.S. Air Force in the mid-1970s as a result of the Integrated Computer Aided Manufacturing (ICAM) Program. The objective of this program was to increase manufacturing productivity through the systematic application of computer technology. The ICAM Program identified a need for better analysis and communication techniques for people involved in improving manufacturing productivity. As a result, the ICAM Program developed a series of techniques known as the IDEF (ICAM Definition) Methods which included the following: IDEF0 used to produce a “function model” which is a structured representation of the activities or processes within the environment or system IDEF1 used to produce an “information model” which represents the structure and semantics of information within the environment or system IDEF2 used to produce a “dynamics model”.
The initial approach to IDEF information modeling (IDEF1) was published by the ICAM program in 1981, based on current research and industry needs. The theoretical roots for this approach stemmed from the early work of Edgar F. Codd on Relational model theory and Peter Chen on the entity-relationship model. The initial IDEF1 technique was based on the work of Dr R. R. Brown and Mr T. L. Ramey of Hughes Aircraft working with Dan Appleton and Stu Coleman of D. Appleton Company (DACOM), with critical review and influence by Charles Bachman, Peter Chen, Dr M. A. Melkanoff, and Dr G.M. Nijssen. DACOM and Hughes tested IDEF1 by modeling engineering data. Methodology improvements were proposed in two areas: modeling notation and modeling methodology and rules. Appleton's suggested improvements were accepted, the AF relabled its data modeling methodology IDEF1 Xtended, or IDEF1X.
In 1983, the U.S. Air Force initiated the Integrated Information Support System (I2S2) project under the ICAM program. The objective of this project was to provide the enabling technology to logically and physically integrate a network of heterogeneous computer hardware and software. As a result of this project, and industry experience, the need for an enhanced technique for data modeling was recognized.
From the point of view of the contract administrators of the Air Force IDEF program, IDEF1X was a result of the ICAM IISS-6201 project and was further extended by the IISS-6202 project. To satisfy the data modeling enhancement requirements that were identified in the IISS-6202 project, D. Appleton Company obtained a license to database design software based on the logical database design technique (LDDT) developed by Robert Brown for the Bank of America. Appleton's technology team modified the software to meet IDEF1X modeling graphics and rules.
On September 2, 2008, the associated NIST standard, FIPS 184, has been withdrawn (decision on Federal Register vol. 73 / page 51276 ).
Since September 2012, IDEF1X has been incorporated into international standard ISO/IEC/IEEE 31320-2:2012.ISO/IEC/IEEE 31320-2:2012 Information technology — Modeling Languages — Part 2: Syntax and Semantics for IDEF1X97 (IDEFobject). The standard describes the syntax and semantics of IDEF1X97, which consists of two conceptual modeling languages: a “key-style” language downward compatible with FIPS 184, which supports relational and extended relational databases, and a newer “identity-style” language suitable for object databases and object-oriented modeling.
The Bank of America's logical database design technique (LDDT) had been developed in 1982 by Robert Brown. The central goal of IDEF1X and LDDT was the same: to produce a methodology that consistently and faithfully produced a database-neutral model of the persistent information needed by an enterprise by modeling the real-world entities involved. IDEF1X combined elements of the relational data model, the E-R model, and data generalization in a way specifically intended to support data modeling and the transformation of the data models into database designs.
IDEF1X includes an environmental (namespace) hierarchy, multiple levels of model, the modeling of generalization/specialization, and the explicit representation of relationships by primary and foreign keys, supported by a well defined role naming facility. The primary keys and unambiguously role-named foreign keys expressed sometimes subtle uniqueness and referential integrity constraints that needed to be known and honored by whatever type of database was ultimately designed. Whether the database design used the integrity constraint based keys of the IDEF1X model as database access keys or indexes was an entirely separate decision. The precision and completeness of the IDEF1X models was an important factor in enabling the relatively smooth transformation of the models into database designs. Early IDEF1X models were transformed into database designs for IBM's hierarchical database, IMS. Later models were transformed into database designs for Cullinet's network database, IDMS, and many varieties of relational database.
Appleton produced IDEF1X data modeling software called Leverage. Leverage supported view (model) entry, view merging, selective (subset) viewing, namespace inheritance, normalization, a quality assurance analysis of views, entity relationship graph and report generation, transformation to a relational database expressed as SQL data declaration statements, and referential integrity checking SQL. Logical models were serialized with a structural modeling language.
IDEF1X building blocks
Entities The representation of a class of real or abstract things (people, objects, places, events, ideas, combination of things, etc.) that are recognized as instances of the same class because they share the same characteristics and can participate in the same relationships. Domains A named set of data values (fixed, or possibly infinite in number) all of the same data type, upon which the actual value for an attribute instance is drawn. Every attribute must be defined on exactly one underlying domain. Multiple attributes may be based on the same underlying domain. Attributes A property or characteristic that is common to some or all of the instances of an entity. An attribute represents the use of a domain in the context of an entity. Keys An attribute, or combination of attributes, of an entity whose values uniquely identify each entity instance. Each such set constitutes a candidate key. Primary keys The candidate key selected as the unique identifier of an entity. Foreign keys An attribute, or combination of attributes of a child or category entity instance whose values match those in the primary key of a related parent or generic entity instance. A foreign key can be viewed as the result of the "migration" of the primary key of the parent or generic entity through a specific connection or categorization relationship. An attribute or combination of attributes in the foreign key can be assigned a role name reflecting its role in the child or category entity.
Relationships An association between the instances of two entities or between instances of the same entity. Connection relationships A relationship having no semantics in addition to association. See constraint, cardinality. Categorization relationships A relationship in which instances of both entities represent the same real or abstract thing. One entity (generic entity) represents the complete set of things, the other (category entity) represents a sub-type or sub-classification of those things. The category entity may have one or more characteristics, or a relationship with instances of another entity, not shared by all generic entity instances. Each instance of the category entity is simultaneously an instance of the generic entity. Non-specific relationships A relationship in which an instance of either entity can be related to any number of instances of the other. View levels Three levels of view are defined in IDEF1X: entity relationship (ER), key-based (KB), and fully attributed (FA). They differ in level of abstraction. The ER level is the most abstract. It models the most fundamental elements of the subject area - the entities and their relationships. It is usually broader in scope than the other levels. The KB level adds keys and the FA level adds all the attributes.
IDEF1X topics
The three-schema approach
The three-schema approach in software engineering is an approach to building information systems and systems information management, that promotes the conceptual model as the key to achieving data integration.STRAP SECTION 2 APPROACH. Retrieved 30 September 2008.
A schema is a model, usually depicted by a diagram and sometimes accompanied by a language description. The three schemas used in this approach are:Mary E.S. Loomis (1987). The Database Book. p. 26. External schema for user views Conceptual schema integrates external schemata Internal schema that defines physical storage structures.