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:''Not to be confused with Object-relational mapping. Object-role modeling (ORM) is used to model the semantics of a universe of discourse. ORM is often used for data modeling and software engineering. An object-role model uses graphical symbols that are based on first order predicate logic and set theory to enable the modeler to create an unambiguous definition of an arbitrary universe of discourse. Attribute free, the predicates of an ORM Model lend themselves to the analysis and design of graph database models in as much as ORM was originally conceived to benefit relational database design. The term "object-role model" was coined in the 1970s and ORM based tools have been used for more than 30 years – principally for data modeling. More recently ORM has been used to model business rules, XML-Schemas, data warehouses, requirements engineering and web forms.〔http://logicblox.pbworks.com/f/Paper+Jarrar+-+automated+reasonning+on+ORM.pdf〕 == History == The roots of ORM can be traced to research into semantic modeling for information systems in Europe during the 1970s. There were many pioneers and this short summary does not by any means mention them all. An early contribution came in 1973 when Michael Senko wrote about "data structuring" in the IBM Systems Journal. In 1974 Jean-Raymond Abrial contributed an article about "Data Semantics". In June 1975, Eckhard Falkenberg's doctoral thesis was published and in 1976 one of Falkenberg's papers mentions the term "object-role model". G.M. Nijssen made fundamental contributions by introducing the "circle-box" notation for object types and roles, and by formulating the first version of the conceptual schema design procedure. Robert Meersman extended the approach by adding subtyping, and introducing the first truly conceptual query language. Object role modeling also evolved from the ''Natural language Information Analysis Method'', a methodology that was initially developed by the academic researcher, G.M. Nijssen in the Netherlands (Europe) in the mid-1970s and his research team at the Control Data Corporation Research Laboratory in Belgium, and later at the University of Queensland, Australia in the 1980s. The acronym NIAM originally stood for "Nijssen's Information Analysis Methodology", and later generalised to "Natural language Information Analysis Methodology" and ''Binary Relationship Modeling'' since G. M. Nijssen was only one of many people involved in the development of the method. In 1989 Terry Halpin completed his PhD thesis on ORM, providing the first full formalization of the approach and incorporating several extensions. Also in 1989, Terry Halpin and G.M. Nijssen co-authored the book "Conceptual Schema and Relational Database Design" and several joint papers, providing the first formalization of object-role modeling. Since then Dr. Terry Halpin has authored six books and over 160 technical papers. A graphical NIAM design tool which included the ability to generate database-creation scripts for Oracle, DB2 and DBQ was developed in the early 1990s in Paris. It was originally named Genesys and was marketed successfully in France and later Canada. It could also handle ER diagram design. It was ported to SCO Unix, SunOs, DEC 3151's and Windows 3.0 platforms, and was later migrated to succeeding Microsoft operating systems, utilising XVT for cross operating system graphical portability. The tool was renamed OORIANE and is currently being used for large data warehouse and SOA projects. Also evolving from NIAM is "''Fully Communication Oriented Information Modeling''" FCO-IM (1992). It distinguishes itself from traditional ORM in that it takes a strict communication-oriented perspective. Rather than attempting to model the domain and its essential concepts, it models the communication in this domain (universe of discourse). Another important difference is that it does this on instance level, deriving type level and object/fact level during analysis. Another recent development is the use of ORM in combination with standardised relation types with associated roles and a standard machine-readable dictionary and taxonomy of concepts as are provided in the Gellish English dictionary. Standardisation of relation types (fact types), roles and concepts enables increased possibilities for model integration and model reuse. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Object-role modeling」の詳細全文を読む スポンサード リンク
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