Evolvable Systems for Big Data Management in Business Article Swipe
YOU?
·
· 2017
· Open Access
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· DOI: https://doi.org/10.1109/hpcs.2017.14
Big Data systems are increasingly having to be longer lasting,\nenterprise-wide and interoperable with other (legacy or new) systems.\nFurthermore many organizations operate in an external environment which\ndictates change at an unforeseeable rate and requires evolution in system\nrequirements. In these cases system development does not have a definitive end\npoint, rather it continues in a mutually constitutive cycle with the\norganization and its requirements. Also when the period of design is of such\nduration that the technology may well evolve or when the required technology is\nnot mature at the outset, then the design process becomes considerably more\ndifficult. Not only that but if the system must inter-operate with other\nsystems then the design process becomes considerably more difficult. Ideally in\nthese circumstances the design must also be able to evolve in order to react to\nchanging technologies and requirements and to ensure traceability between the\ndesign and the evolving system specification. In other words extended design\nperiods necessitate adaptable design specifications. For interoperability Big\nData systems need to be discoverable and to work with information about other\nsystems with which they need to cooperate over time. We have developed software\ncalled CRISTAL-ISE that enables dynamic system evolution and interoperability\nfor Big Data systems, it has been commercialised as the Agilium-NG BPM product\nand is described in this paper.\n
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1109/hpcs.2017.14
- OA Status
- green
- Cited By
- 2
- References
- 15
- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W2754613222Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/hpcs.2017.14Digital Object Identifier
- Title
-
Evolvable Systems for Big Data Management in BusinessWork title
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-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2017Year of publication
- Publication date
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2017-07-01Full publication date if available
- Authors
-
Richard McClatchey, Andrew Branson, Jetendr Shamdasani, Patrick EminList of authors in order
- Landing page
-
https://doi.org/10.1109/hpcs.2017.14Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/1803.07434Direct OA link when available
- Concepts
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Interoperability, Computer science, Traceability, Process (computing), Big data, Business process, Systems design, Information system, Software engineering, Systems engineering, Process management, Work in process, Engineering, World Wide Web, Operations management, Operating system, Electrical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2023: 1, 2018: 1Per-year citation counts (last 5 years)
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15Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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