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Published in: KI - Künstliche Intelligenz 2/2015

01-06-2015 | AI Market

Facilitating Evolution during Design and Implementation

Author: Richard McClatchey

Published in: KI - Künstliche Intelligenz | Issue 2/2015

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Abstract

The volumes and complexity of data that companies need to handle are increasing at an accelerating rate. In order to compete effectively and ensure their commercial sustainability, it is becoming crucial for them to achieve robust traceability in both their data and the evolving designs of their systems. This is addressed by the CRISTAL software which was originally developed at CERN by UWE, Bristol, for one of the particle detectors at the Large Hadron Collider, which has been subsequently transferred into the commercial world. Companies have been able to demonstrate increased agility, generate additional revenue, and improve the efficiency and cost-effectiveness with which they develop and implement systems in various areas, including business process management (BPM), healthcare and accounting applications. CRISTAL’s ability to manage data and its semantic provenance at the terabyte scale, with full traceability over extended timescales, together with its description-driven approach, has provided the flexible adaptability required to future proof dynamically evolving software for these businesses.

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The Scientific journal "KI – Künstliche Intelligenz" is the official journal of the division for artificial intelligence within the "Gesellschaft für Informatik e.V." (GI) – the German Informatics Society - with constributions from troughout the field of artificial intelligence.

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Literature
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2.
go back to reference McClatchey R et al (1998) A distributed workflow & product data management application for the construction of large scale scientific apparatus. NATO ASI series F: computer & systems sciences, Springer- Verlag. doi:10.1007/978-3-642-58908-9_2 McClatchey R et al (1998) A distributed workflow & product data management application for the construction of large scale scientific apparatus. NATO ASI series F: computer & systems sciences, Springer- Verlag. doi:10.​1007/​978-3-642-58908-9_​2
5.
go back to reference Branson A, McClatchey R, Le Goff J-M, Shamdasani J (2014) CRISTAL: a practical study in designing systems to cope with change information systems 42, Elsevier Publishers. doi:10.1016/j.is.2013.12.009 Branson A, McClatchey R, Le Goff J-M, Shamdasani J (2014) CRISTAL: a practical study in designing systems to cope with change information systems 42, Elsevier Publishers. doi:10.​1016/​j.​is.​2013.​12.​009
8.
go back to reference Shamdasani J et al (2014) CRISTAL-ISE: provenance applied in industry. In: Proceedings of the 16th international conference on enterprise information systems (ICEIS), vol 3, Lisbon. doi:10.5220/,SCITEPRESS Shamdasani J et al (2014) CRISTAL-ISE: provenance applied in industry. In: Proceedings of the 16th international conference on enterprise information systems (ICEIS), vol 3, Lisbon. doi:10.​5220/​,SCITEPRESS
Metadata
Title
Facilitating Evolution during Design and Implementation
Author
Richard McClatchey
Publication date
01-06-2015
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz / Issue 2/2015
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-014-0324-1

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