Formal Transformation of EER and EXPRESS-G Models Z. M. Ma Department of Computer Science and Engineering, Oakland University Rochester, MI 48309, USA E-mail:
[email protected] Phone: 248-656 3435
Shiyong Lu and Farshad Fotouhi Department of Computer Science, Wayne State University Detroit, MI 48202, USA Nowadays computer-based information systems have become the nerve center of current manufacturing systems. The requirement on engineering information modeling is hereby potential (Ma and Mili, 2002). Viewed from database systems, engineering information modeling can be identified at two levels: conceptual data modeling and logical database modeling. Correspondingly we have conceptual data models and logical database models for engineering information modeling, respectively. Engineering information modeling generally starts from conceptual data models and then the developed conceptual data models are mapped into logical database models. In addition, conceptual data models can capture and represent rich and complex semantics in engineering applications at a high abstract level. Therefore, much attention has been directed at conceptual data modeling of engineering information and some conceptual data models have been used for this purpose, e.g., ER/EER, IDEF1X, and EXPRESS. Traditional ER/EER can be used for engineering information modeling at conceptual level. However, limited by their power in engineering modeling, some new conceptual data models have been developed. IDEF1X is a method for designing relational databases with a syntax designed to support the semantic constructs necessary in developing a conceptual schema applied in computer integrated manufacturing systems. In order to implement share and exchange of product data, the Standard for the Exchange of Product Model Data (STEP) is being developed by the International Organization for Standardization (ISO). STEP provides a means to describe a product model throughout its life cycle and to exchange data between different units. STEP consists of 4 major categories: description methods, implementation methods, conformance testing methodology and framework, and standardized application data models/schemata. EXPRESS (Schenck and Wilson, 1994), being the description methods of STEP and a conceptual schema language, can model product design, manufacturing, and production data and EXPRESS model hereby becomes a major one of conceptual data models for engineering information modelling (Eastman and Fereshetian, 1994). It should be noted that, however, not being the same as ER/EER and IDEF1X, EXPRESS is not a graphical schema language. In order to construct EXPRESS data model at a higher level of abstract, EXPRESS-G is introduced as the graphical representation of EXPRESS. Here EXPRESS-G can only express a subset of the full language of EXPRESS, which provides supports for the notions of entity, type, relationship, cardinality, and schema. The functions, procedures, and rules in EXPRESS language are not supported by EXPRESS-G. In addition to EXPRESS-G, it is also suggested in STEP that IDEF1X or ER/EER can be used as one of the optional languages for in EXPRESS data model design. Then EXPRESS-G, IDEF1X, ER/EER, or even UML data model can be translated into EXPRESS data model. That multiple graphical data models can be employed facilitates the designers with different background to design their EXPRESS models easily by using one of the graphical data models they are familiar with. There are already some efforts for converting EXPRESS-G, IDEF1X, ER/EER, or UML data model into EXPRESS data model. However, a complex EXPRESS data model is generally completed cooperatively by a design group, in which each member may use a different graphical data model. All these graphical data models designed by different members should be converted into a union data model finally because of the following reasons. • Creating EXPRESS data models. Then EXPRESS-G is chosen as the target data model and the other graphical data models should be converted into EXPRESS-G. • Creating databases. Then one of no EXPRESS-G graphical data models, say EER model, is chosen as the target data model and EXPRESS-G as well as other graphical data models are converted into the target data model. The last issue is essentially related to the implementation of EXPRESS data model in database systems, which is the foundation of achieving STEP goal that product data can be exchanged and shared among different applications. The relationships among graphical data models (ER/EER, IDEF1X, UML, and EXPRESS-G), EXPRESS data model, and database systems are illustrated in following figure. So far, the data model conversions among EXPRESS-G, IDEF1X, ER/EER, and UML only receive few attentions although such conversions are crucial in engineering information modeling. In (Arnold and Podehl, 1999), a mapping from EXPRESS-G to UML was introduced in order to define a linking bridge and bring the best of worlds of product data technology and software engineering together. 1
ER/EER
IDEF1X
UML
EXPRESS-G
EXPRESS Databases
In this paper, we concentrate on EER model and EXPRESS-G model, which are known well and popular in the areas of database design and engineering information modelling, respectively. After introducing the constructs in each of these two data models briefly, we compare their capability in data modeling and investigate how they match each other. On the basis, we develop the generic rules for mapping from EXPRESS-G to EER as well as mapping from EER to EXPRESS-G. The mapping with examples is presented whereby several problematic cases are discussed and possible solutions presented.
References Arnold, F. and Podehl, G., 1999, Best of Both Worlds − A Mapping from EXPRESS-G to UML, Lecture Notes in Computer Science 1618, 49-63. Booch, G., Jacobson, I. and Rumbaugh, J., 1997, The Unified Modeling Language, Documentation Set 1.1. Chen, P. P., 1976, The Entity-Relationship Model: Toward a Unified View of Data, ACM Transactions on Database Systems, 1 (1), 9-36. Eastman, C. M. and Fereshetian, N., 1994, Information Models for Use in Product Design: A Comparison, Computer-Aide Design, 26 (7), 551-572. IDEF1X Overview, 1993, http://www.idef.com/idef1x.html ISO IS 10303-1 TC184/SC4, 1994, Product Data Representation and Exchange-Part 1: Overview and Fundamental Principles, International Standard. ISO TC184/SC4 WG7 N392, 1995, Industrial Automation Systems and Integration — Product Data Representation and Exchange — Part 22: Implementation Methods: Standard Data Access Interface. Ma, Z. M. and Mili, F., 2002, Database Models for Engineering Information Modeling: Needs and Construction, ASME Transactions: Journal of Computing & Information Science in Engineering (under second review). Schenck, D. A. and Wilson, P. R., 1994, Information Modeling: the EXPRESS Way, Oxford University Press.
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