Abstract
Enterprises need to cope with increasing volumes of complex and evolving data and at the same time to reduce ‘time-to-market’ for products. As data volumes increase and user communities grow and change with time, enterprise systems must be able to provide access to the enterprise data appropriate to multiple application viewpoints. In addition, the enterprise model must be flexible, adaptable and secure and be designed to maximise reusability of code, to cope with distribution of the enterprise activities and to inter-operate with legacy systems. The era where business rules are buried deep within the application code is coming to an end. Today users themselves seek to dynamically change their business rules and they need systems which can adapt to their evolving business needs, meet their requirements and scale to large installations. This paper outlines how an enterprise model that integrates process and product data modelling has been constructed following a description-driven design approach for the management of large-scale scientific apparatus.
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References
Philpotts, M. (1996) An Introduction to the Concepts, Benefits and Terminology of Product Data Management, Industrial Management & Data Systems, Vol 4 pp11–17
Pikosz, P. and J. Malmqvist (1996) Possibilities and Limitations when Using PDM Systems to Support the Product Development Process, In proc of NordDesign’96, Helsinki, Finland.
Georgakopoulos, D., M. Hornick and A. Sheth (1995) An Overview of Workflow Management: from Process Modelling to Infrastructure for Automation, Journal of Distributed and Parallel Database Systems Vol 3(2), pp119–153.
Ramanathan, J. (1996) Process Improvement and Data Management, IIE Solutions, 1996 28 12 pp24–27.
Technical Proposal. The CMS Collaboration (1995), ftp://cmsdoc.cern.ch/TPref/TP.html
McClatchey, R. et al. (1997) A Distributed Workflow and Product Data Management Application for the Construction of Large Scale Scientific Apparatus. NATO ASI Series F: Computer & Systems Sciences Vol 164.pp 18–34.
Fowler M. and K. Scott.(1997) UML Distilled-Applying the Standard Object Modelling Language. Addison-Wesley Longman publishers.
Bachi, G and A. Hameri (1995) What to be Implemented at the early Stages of a Large-Scale Project. CERN MT/95-02 (DI) LHC Note 315.
Baker, N. et al. (1998) An Object Model for Product and Workflow Data Management. In proc. of the 9th ACM Int Workshop & Conf on Database and Expert System Applications (DEXA’98) pp 731–738.
Blaha M. and W. Premerlani (1999) Object-Oriented Modelling and Design for Database Applications. Prentice Hall publishers.
Le Goff, J-M et al. (1998) Detector Construction Management and Quality Control: Establishing and Using a CRISTAL System. CERN CMS NOTE 1998/033.
Kerherve, B. and A. Gerbe (1997) Models for Metadata or Metamodels for Data? In proc. of the 2nd IEEE MetaData conference, 1997.
Schulze. W., „Fitting the Workflow Management Facility into the Object Management Architecture“. Proc of the Business Object Workshop at OOPSLA’97.
OMG (1997 & 1999) Meta-Object Facility RFP TC Doc cf/96-02-01, Evaluation Report TC Doc ad/97-08-14 and ad/99-09-04
OMG (1992) The Common Object Request Broker: Architecture & Specifications, OMG Publications.
Bazan A. et al. (1999) The Use of Production Management Techniques in the Construction of Large Scale Physics Detectors. IEEE Trans on Nuclear Sci. 1999 Vol 46 No 3 pp 392–400 ISBN 0018-9499
Hardwick, M., et al. (1996) Sharing Manufacturing Information in Virtual Enterprises. Communications of the ACM Vol 39(2) pp 46–54.
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© 2000 Springer-Verlag Berlin Heidelberg
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Bazan, A. et al. (2000). Integrated Data Management and Enterprise Models. In: Lu, H., Zhou, A. (eds) Web-Age Information Management. WAIM 2000. Lecture Notes in Computer Science, vol 1846. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45151-X_15
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DOI: https://doi.org/10.1007/3-540-45151-X_15
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