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Designing Traceability into Big Data Systems

Providing an appropriate level of accessibility and traceability to data or process elements (so-called Items) in large volumes of data, often Cloud-resident, is an essential requirement in the Big Data era. Enterprise-wide data systems need to be designed from the outset to support usage of such It...

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Detalles Bibliográficos
Autores principales: McClatchey, Richard, Branson, Andrew, Shamdasani, Jetendr, Kovacs, Zsolt
Lenguaje:eng
Publicado: 2015
Materias:
Acceso en línea:http://cds.cern.ch/record/2002631
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author McClatchey, Richard
Branson, Andrew
Shamdasani, Jetendr
Kovacs, Zsolt
author_facet McClatchey, Richard
Branson, Andrew
Shamdasani, Jetendr
Kovacs, Zsolt
author_sort McClatchey, Richard
collection CERN
description Providing an appropriate level of accessibility and traceability to data or process elements (so-called Items) in large volumes of data, often Cloud-resident, is an essential requirement in the Big Data era. Enterprise-wide data systems need to be designed from the outset to support usage of such Items across the spectrum of business use rather than from any specific application view. The design philosophy advocated in this paper is to drive the design process using a so-called description-driven approach which enriches models with meta-data and description and focuses the design process on Item re-use, thereby promoting traceability. Details are given of the description-driven design of big data systems at CERN, in health informatics and in business process management. Evidence is presented that the approach leads to design simplicity and consequent ease of management thanks to loose typing and the adoption of a unified approach to Item management and usage.
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institution Organización Europea para la Investigación Nuclear
language eng
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spelling oai-inspirehep.net-13431702021-05-03T08:19:50Zhttp://cds.cern.ch/record/2002631engMcClatchey, RichardBranson, AndrewShamdasani, JetendrKovacs, ZsoltDesigning Traceability into Big Data Systemscs.DBcs.DBProviding an appropriate level of accessibility and traceability to data or process elements (so-called Items) in large volumes of data, often Cloud-resident, is an essential requirement in the Big Data era. Enterprise-wide data systems need to be designed from the outset to support usage of such Items across the spectrum of business use rather than from any specific application view. The design philosophy advocated in this paper is to drive the design process using a so-called description-driven approach which enriches models with meta-data and description and focuses the design process on Item re-use, thereby promoting traceability. Details are given of the description-driven design of big data systems at CERN, in health informatics and in business process management. Evidence is presented that the approach leads to design simplicity and consequent ease of management thanks to loose typing and the adoption of a unified approach to Item management and usage.arXiv:1502.01545oai:inspirehep.net:13431702015
spellingShingle cs.DB
cs.DB
McClatchey, Richard
Branson, Andrew
Shamdasani, Jetendr
Kovacs, Zsolt
Designing Traceability into Big Data Systems
title Designing Traceability into Big Data Systems
title_full Designing Traceability into Big Data Systems
title_fullStr Designing Traceability into Big Data Systems
title_full_unstemmed Designing Traceability into Big Data Systems
title_short Designing Traceability into Big Data Systems
title_sort designing traceability into big data systems
topic cs.DB
cs.DB
url http://cds.cern.ch/record/2002631
work_keys_str_mv AT mcclatcheyrichard designingtraceabilityintobigdatasystems
AT bransonandrew designingtraceabilityintobigdatasystems
AT shamdasanijetendr designingtraceabilityintobigdatasystems
AT kovacszsolt designingtraceabilityintobigdatasystems