Design Patterns for Description-Driven Systems

In data modelling, product information has most often been handled separately from process information. The integration of product and process models in a unified data model could provide the means by which information could be shared across an enterprise throughout the system lifecycle from design through to production. Recently attempts have been made to integrate these two separate views of systems through identifying common data models. This paper relates description-driven systems to multi-layer architectures and reveals where existing design patterns facilitate the integration of product and process models and where patterns are missing or where existing patterns require enrichment for this integration. It reports on the construction of a so-called description-driven system which integrates Product Data Management (PDM) and Workflow Management (WfM) data models through a common meta-model.Comment: 14 pages, 13 figures. Presented at the 3rd Enterprise Distributed Object Computing EDOC'99 conference. Mannheim, Germany. September 199

The Reification of Patterns in the Design of Description-Driven Systems

To address the issues of reusability and evolvability in designing self- describing systems, this paper proposes a pattern-based, object-oriented, description-driven system architecture. The proposed architecture embodies four pillars - first, the adoption of a multi-layered meta-modeling architecture and reflective meta-level architecture, second, the identification of four data modeling relationships that must be made explicit such that they can be examined and modified dynamically, third, the identification of five design patterns which have emerged from practice and have proved essential in providing reusable building blocks for data management, and fourth, the encoding of the structural properties of the five design patterns by means of one pattern, the Graph pattern. The CRISTAL research project served as the basis onto which the pattern-based meta-object approach has been applied. The proposed architecture allows the realization of reusability and adaptability, and is fundamental in the specification of self-describing data management components.Comment: 10 pages 11 figure

Meta-Data Objects as the Basis for System Evolution

One of the main factors driving object-oriented software development in the Web- age is the need for systems to evolve as user requirements change. A crucial factor in the creation of adaptable systems dealing with changing requirements is the suitability of the underlying technology in allowing the evolution of the system. A reflective system utilizes an open architecture where implicit system aspects are reified to become explicit first-class (meta-data) objects. These implicit system aspects are often fundamental structures which are inaccessible and immutable, and their reification as meta-data objects can serve as the basis for changes and extensions to the system, making it self- describing. To address the evolvability issue, this paper proposes a reflective architecture based on two orthogonal abstractions - model abstraction and information abstraction. In this architecture the modeling abstractions allow for the separation of the description meta-data from the system aspects they represent so that they can be managed and versioned independently, asynchronously and explicitly. A practical example of this philosophy, the CRISTAL project, is used to demonstrate the use of meta-data objects to handle system evolution

From Design to Production Control Through the Integration of Engineering Data Management and Workflow Management Systems

At a time when many companies are under pressure to reduce "times-to-market" the management of product information from the early stages of design through assembly to manufacture and production has become increasingly important. Similarly in the construction of high energy physics devices the collection of (often evolving) engineering data is central to the subsequent physics analysis. Traditionally in industry design engineers have employed Engineering Data Management Systems (also called Product Data Management Systems) to coordinate and control access to documented versions of product designs. However, these systems provide control only at the collaborative design level and are seldom used beyond design. Workflow management systems, on the other hand, are employed in industry to coordinate and support the more complex and repeatable work processes of the production environment. Commercial workflow products cannot support the highly dynamic activities found both in the design stages of product development and in rapidly evolving workflow definitions. The integration of Product Data Management with Workflow Management can provide support for product development from initial CAD/CAM collaborative design through to the support and optimisation of production workflow activities. This paper investigates this integration and proposes a philosophy for the support of product data throughout the full development and production lifecycle and demonstrates its usefulness in the construction of CMS detectors.Comment: 18 pages, 13 figure