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Semantic data model (SDM) is a high-level semantics-based database description and structuring formalism (database model) for databases. This database model is designed to capture more of the meaning of an application environment than is possible with contemporary database models. An SDM specification describes a database in terms of the kinds of entities that exist in the application environment, the classifications and groupings of those entities, and the structural interconnections among them. SDM provides a collection of high-level modeling primitives to capture the semantics of an application environment. By accommodating derived information in a database structural specification, SDM allows the same information to be viewed in several ways; this makes it possible to directly accommodate the variety of needs and processing requirements typically present in database applications. The design of the present SDM is based on our experience in using a preliminary version of it. SDM is designed to enhance the effectiveness and usability of database systems. An SDM database description can serve as a formal specification and documentation tool for a database; it can provide a basis for supporting a variety of powerful user interface facilities, it can serve as a conceptual database model in the database design process; and, it can be used as the database model for a new kind of database management system. A semantic data model in
software engineering Software engineering is a systematic engineering approach to software development. A software engineer is a person who applies the principles of software engineering to design, develop, maintain, test, and evaluate computer software. The term '' ...
has various meanings: # It is a
conceptual data model A conceptual schema is a high-level description of informational needs underlying the design of a database. It typically includes only the main concepts and the main relationships among them. Typically this is a first-cut model, with insufficient ...
in which semantic information is included. This means that the model describes the meaning of its instances. Such a semantic
data model A data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may specify that the data element representing a car be c ...
is an abstraction that defines how the stored
symbol A symbol is a mark, sign, or word that indicates, signifies, or is understood as representing an idea, object, or relationship. Symbols allow people to go beyond what is known or seen by creating linkages between otherwise very different conc ...
s (the instance data) relate to the real world. # It is a
conceptual data model A conceptual schema is a high-level description of informational needs underlying the design of a database. It typically includes only the main concepts and the main relationships among them. Typically this is a first-cut model, with insufficient ...
that includes the capability to express and exchange information which enables parties to interpret meaning (semantics) from the instances, without the need to know the meta-model. Such semantic models are fact-oriented (as opposed to object-oriented). Facts are typically expressed by
binary relations In mathematics, a binary relation associates elements of one set, called the ''domain'', with elements of another set, called the ''codomain''. A binary relation over sets and is a new set of ordered pairs consisting of elements in and in ...
between
data In the pursuit of knowledge, data (; ) is a collection of discrete values that convey information, describing quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpret ...
elements, whereas higher order relations are expressed as collections of binary relations. Typically binary relations have the form of triples: Object-RelationType-Object. For example: the Eiffel Tower Paris. Typically the instance data of semantic data models explicitly include the kinds of relationships between the various data elements, such as . To interpret the meaning of the facts from the instances, it is required that the meaning of the kinds of relations (relation types) be known. Therefore, semantic data models typically standardize such relation types. This means that the second kind of semantic data models enables that the instances express facts that include their own meanings. The second kind of semantic data models are usually meant to create semantic databases. The ability to include meaning in semantic databases facilitates building distributed databases that enable applications to interpret the meaning from the content. This implies that semantic databases can be integrated when they use the same (standard) relation types. This also implies that in general they have a wider applicability than relational or object-oriented databases.


Overview

The logical data structure of a
database management system In computing, a database is an organized collection of data stored and accessed electronically. Small databases can be stored on a file system, while large databases are hosted on computer clusters or cloud storage. The design of databases ...
(DBMS), whether
hierarchical A hierarchy (from Greek: , from , 'president of sacred rites') is an arrangement of items (objects, names, values, categories, etc.) that are represented as being "above", "below", or "at the same level as" one another. Hierarchy is an important ...
,
network Network, networking and networked may refer to: Science and technology * Network theory, the study of graphs as a representation of relations between discrete objects * Network science, an academic field that studies complex networks Mathematic ...
, or relational, cannot totally satisfy the
requirements In product development and process optimization, a requirement is a singular documented physical or functional need that a particular design, product or process aims to satisfy. It is commonly used in a formal sense in engineering design, inclu ...
for a conceptual definition of data, because it is limited in scope and biased toward the implementation strategy employed by the DBMS. Therefore, the need to define data from a conceptual view has led to the development of semantic data modeling techniques. That is, techniques to define the meaning of data within the context of its interrelationships with other data, as illustrated in the figure. The real world, in terms of resources, ideas, events, etc., are symbolically defined within physical data stores. A semantic data model is an abstraction which defines how the stored symbols relate to the real world. Thus, the model must be a true representation of the real world. According to Klas and Schrefl (1995), the "overall goal of semantic data models is to capture more meaning of data by integrating relational concepts with more powerful abstraction concepts known from the
Artificial Intelligence Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech ...
field. The idea is to provide high level modeling primitives as an integral part of a data model in order to facilitate the representation of real world situations".Wolfgang Klas, Michael Schrefl (1995). "Semantic data modeling" In: ''Metaclasses and Their Application''. Book Series Lecture Notes in Computer Science. Publisher Springer Berlin / Heidelberg. Volume Volume 943/1995.


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. ** IDEF1X a semantic data modeling technique used to produce a graphical information model which represents the structure and semantics of information within an environment or system. Use of this standard 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. * IDEF2 used to produce a “dynamics model” which represents the time varying behavioral characteristics of the environment or system. During the 1990s, the application of semantic modelling techniques resulted in the semantic data models of the second kind. An example of such is the semantic data model that is standardised as
ISO 15926 The ISO 15926 is a standard for data integration, sharing, exchange, and hand-over between computer systems. The title, "''Industrial automation systems and integration—Integration of life-cycle data for process plants including oil and ga ...
-2 (2002), which is further developed into the semantic modelling language
Gellish Gellish is an ontology language for data storage and communication, designed and developed by Andries van Renssen since mid-1990s. It started out as an engineering modeling language ("Generic Engineering Language", giving it the name, "Gellish") bu ...
(2005). The definition of the Gellish language is documented in the form of a semantic data model. Gellish itself is a semantic modelling language, that can be used to create other semantic models. Those semantic models can be stored in Gellish Databases, being semantic databases.


Applications

A semantic data model can be used to serve many purposes. Some key objectives include: * Planning of Data Resources: A preliminary data model can be used to provide an overall view of the data required to run an enterprise. The model can then be analyzed to identify and scope projects to build shared data resources. * Building of Shareable Databases: A fully developed model can be used to define an application independent view of data which can be validated by users and then transformed into a physical database design for any of the various DBMS technologies. In addition to generating databases which are consistent and shareable, development costs can be drastically reduced through data modeling. * Evaluation of Vendor Software: Since a data model actually represents the infrastructure of an organization, vendor software can be evaluated against a company’s data model in order to identify possible inconsistencies between the infrastructure implied by the software and the way the company actually does business. * Integration of Existing Databases: By defining the contents of existing databases with semantic data models, an integrated data definition can be derived. With the proper technology, the resulting conceptual schema can be used to control transaction processing in a distributed database environment. The U.S. Air Force Integrated Information Support System (I2S2) is an experimental development and demonstration of this kind of technology, applied to a heterogeneous type of DBMS environments.


See also

* Semantic technology *
Conceptual schema A conceptual schema is a high-level description of informational needs underlying the design of a database. It typically includes only the main concepts and the main relationships among them. Typically this is a first-cut model, with insufficient ...
* Object-role modeling * Entity-relationship model *
Information model An information model in software engineering is a representation of concepts and the relationships, constraints, rules, and operations to specify data semantics for a chosen domain of discourse. Typically it specifies relations between kinds of t ...
* Relational Model/Tasmania *
Three schema approach The three-schema approach, or three-schema concept, in software engineering is an approach to building information systems and systems information management that originated in the 1970s. It proposes three different views in systems development, ...
* QuakeSim *
Computational mathematics Computational mathematics is an area of mathematics devoted to the interaction between mathematics and computer computation.National Science Foundation, Division of Mathematical ScienceProgram description PD 06-888 Computational Mathematics 2006 ...


References


Further reading


Database Design - The Semantic Modelling Approach
* Johan ter Bekke (1992). ''Semantic Data Modeling''. Prentice Hall. * Alfonso F. Cardenas and Dennis McLeod (1990). ''Research Foundations in Object-Oriented and Semantic Database Systems''. Prentice Hall. * Peter Gray, Krishnarao G. Kulkarni and, Norman W. Paton (1992). ''Object-Oriented Databases: A Semantic Data Model Approach''. Prentice-Hall International Series in Computer Science. * Michael Hammer and Dennis McLeod (1978). "The Semantic Data Model: a Modeling Mechanism for Data Base Applications." In: ''Proc. ACM SIGMOD Int’l. Conf. on Management of Data''. Austin, Texas, May 31 - June 2, 1978, pp. 26–36. * Hammer, Michael, and Dennis McLeod. "Database Description with SDM: A Semantic Database Model." ACM Transactions on Database Systems (TODS) 6.3 (1981): 351-86. Web.


External links



Johan ter Bekke tribute site. {{DEFAULTSORT:Semantic Data Model Data modeling Systems analysis Knowledge representation