Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives

Djamel Ghernaout; Mohamed Aichouni; Abdulaziz Alghamdi

doi:doi:10.11648/j.ijsqa.20180403.14

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Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives

Djamel Ghernaout, Mohamed Aichouni, Abdulaziz Alghamdi

Published in International Journal of Science and Qualitative Analysis (Volume 4, Issue 3)

Received: 1 May 2018 Accepted: 17 May 2018 Published: 14 June 2018

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Abstract

The greatest common standard for the expertise of testing and calibration laboratories has recently been bring up to date, considering the newest improvements in laboratory environment and work practices. ISO/IEC 17025:2017, General requirements for the competence of testing and calibration laboratories, is the international reference for laboratories implementing calibration and testing actions through the globe. This article gives a short review on ISO/IEC 17025:2017 and its related data which are increasingly produced every day in the laboratory and suggests Big Data as a fundamental tool of treating such data. ISO/IEC 17025:2017 is gaining a huge part in laboratory legal status and activities; in its side, Big Data is reaching high level of mastery and expansion. On the other hand, there is a huge amount of data around and inside laboratory everyday activities. Besides the experimental and analytical results, there are findings from its financial management. Therefore, Big Data through its enormous capabilities of managing details would imbricate ISO/IEC 17025:2017. The near future would provide more details of how will be the final figure of this intersection.

Published in	International Journal of Science and Qualitative Analysis (Volume 4, Issue 3)
DOI	10.11648/j.ijsqa.20180403.14
Page(s)	83-92
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

ISO/IEC 17025:2017, Measurement Uncertainty (MU), Proficiency Testing (PT), Reference Materials (RMs), Big Data

References

[1]	ISO/IEC 17025, General requirements for the competence of testing and calibration laboratories. International Organization for Standardization/International Electrotechnical Committee, Geneva, 2017.
[2]	S. Tranchard, New edition of ISO/IEC 17025 just published, (1/12/17) https://www.iso.org/news/ref2250.html (Accessed on 21/04/18).
[3]	V. Agostini, Evolution of laboratory procedures for water quality analysis, A. Gilardoni (Ed.), The Italian water industry, Springer International Publishing AG, Berlin, 2018.
[4]	U. Ricci, Establishment of an ISO 17025:2005 accredited forensic genetics laboratory in Italy, Accred. Qual. Assur. 19 (2014) 289-299.
[5]	ISO, ISO/IEC 17025: General requirements for the competence of testing and calibration laboratories, (1/12/17) https://www.iso.org/publication/PUB100424.html (Accessed on 21/04/18).
[6]	ISO/IEC 17025, General requirements for the competence of testing and calibration laboratories. International Organization for Standardization/International Electrotechnical Committee, Geneva, 2005.
[7]	ISO, Discover the new ISO/IEC 17025:2017, (1/12/17) https://www.youtube.com/watch?time_continue=46&v=dH1Kf7gtrBw (Accessed on 21/04/18).
[8]	C. N. Murphy, J. Yates, The International Organization for Standardization (ISO), Global governance through voluntary consensus, T. G. Weiss, R. Wilkinson (Eds.), Routledge Global Institutions, Taylor & Francis, New York, 2009.
[9]	S. Wong, Risk-based thinking for chemical testing, Accred. Qual. Assur. 22 (2017) 103-108.
[10]	K. C. Tsimillis, Measurement uncertainty: requirements set in the accreditation standards, Accredit. Qual. Assur. 23 (2018) 109-114.
[11]	T. Venelinov, Uncertainty estimation of the determination of chemical sum parameters in water, Accred. Qual. Assur. 22 (2017) 347-351.
[12]	K. C. Tsimillis, Training needs to understand quality assurance, Accred. Qual. Assur. 20 (2015) 53-59.
[13]	K. Middlebrook, Do accredited laboratories perform better in proficiency testing than non-accredited laboratories?, Accred. Qual. Assur. 22 (2017) 111-117.
[14]	N. Hots, Investigation of temperature measurement uncertainty components for infrared radiation thermometry, R. Szewczyk, M. Kaliczyńska (Eds.), Recent advances in systems, control and information technology, Advances in intelligent systems and computing 543, Springer International Publishing AG, Berlin, 2017.
[15]	ISO 15189, Medical laboratories—requirements for quality and competence. International Organization for Standardization, Geneva, 2012.
[16]	A. Küchler, Testing, measuring and diagnosis (ch. 6), High voltage engineering, VDI-Buch, Springer-Verlag GmbH Germany, Berlin, 2018.
[17]	ISO 17034, General requirements for the competence of reference material producers. International Organization for Standardization, Geneva, 2016.
[18]	ISO/IEC 17043, Conformity assessment—General requirements for proficiency testing. International Organization for Standardization/International Electrotechnical Committee, Geneva, 2010.
[19]	I. H. Grochau, C. S. ten Caten, M. M. de Camargo Forte, Current American landscape in laboratory accreditation according to ISO/IEC 17025, Accred. Qual. Assur. 22 (2017) 57-62.
[20]	I. Papadakis, F. D. Krokos, C. Trapalis, Interaction of analytical chemistry with accreditation/certification, Environ. Sci. Pollut. Res. 24 (2017) 7872-7879.
[21]	ILAC, www.ilac.org (Accessed on 23/04/18).
[22]	EA, www.european-accreditation.org (Accessed on 23/04/18).
[23]	BIPM, www.bipm.org (Accessed on 23/04/18).
[24]	OIML, www.oiml.org (Accessed on 23/04/18).
[25]	A. Bošnjaković, A. Badnjević, Z. Džemić, Legal metrology system—Past, present, future, A. Badnjević et al. (Eds.), Inspection of medical devices, Series in Biomedical Engineering, Springer Nature Singapore Pte Ltd., Singapore, 2018.
[26]	JCGM, https://www.bipm.org/en/committees/jc/jcgm/ (Accessed on 23/04/18).
[27]	E. Iacob, Experience of accreditation in a surface science laboratory, Accred. Qual. Assur. 21 (2016) 9-17.
[28]	Eurachem, www.eurachem.org (Accessed on 23/04/18).
[29]	V. Barwick (Ed.), Eurachem/CITAC Guide: Guide to quality in analytical chemistry: an aid to accreditation, 3^rd Ed., 2016. https://www.eurachem.org/images/stories/Guides/pdf/Eurachem_CITAC_QAC_2016_EN.pdf (Accessed on 23/04/18).
[30]	Eurolab, www.eurolab.org/publications (Accessed on 23/04/18).
[31]	R. H. Catini, F. J. P. de Souza, M. M. Pinhel, A. de Oliveira Mendonça, V. H. P. Pacces, I. R. B. Olivares, Application of indicators and quality index as a tool for critical analysis and continuous improvement of laboratories accredited against ISO/IEC 17025, Accred. Qual. Assur. 20 (2015) 431-436.
[32]	ISO/IEC 17011, Conformity assessment - Requirements for accreditation bodies accrediting conformity assessment bodies. International Organization for Standardization/International Electrotechnical Committee, Geneva, 2017.
[33]	G. M. P. Silva, R. Nogueira, A. C. O. Faria, The lead assessor role in the ISO/IEC 17025:2005 accreditation of Brazilian calibration and testing laboratories by the General Coordination of Accreditation (Cgcre), Accred. Qual. Assur. 19 (2014) 127-132.
[34]	D. Holcombe, Eurachem/CITAC Quality assurance for research and development and non-routine analysis, 2nd Ed., 1998. https://www.mwa.co.th/download/prd01/reference_ISO17025/Eurachem-nonroutine-1998.pdf (Accessed on 23/04/18).
[35]	V. Machado, M. S. Sundin, Analysis of uncertainty in calibration curves, A. Braidot and A. Hadad (Eds.), VI Latin American Congress on Biomedical Engineering CLAIB 2014, Paraná, Argentina 29, 30 & 31 October 2014, IFMBE Proceedings 49, Springer International Publishing, Switzerland, 2015.
[36]	P. Pereira, B. Magnusson, E. Theodorsson, J. O. Westgard, P. Encarnacão, Measurement uncertainty as a tool for evaluating the ‘grey zone’ to reduce the false negatives in immunochemical screening of blood donors for infectious diseases, Accred. Qual. Assur. 21 (2016) 25-32.
[37]	I. Claramunt, L. Perez, Estimation of measurement uncertainty in the determination of orthophosphates in seawater by continuous flow analysis (CFA), Accred. Qual. Assur. 19 (2014) 205-212.
[38]	ISO 21748, Guide to the use of repeatability, reproducibility and trueness estimates in measurement uncertainty estimation. International Organization for Standardization, Geneva, 2010.
[39]	ISO/TS 19036, Microbiology of food and animal feeding stuffs—guidelines for the estimation of measurement uncertainty for quantitative determinations. International Organization for Standardization, Geneva, 2006.
[40]	ISO 29201, Water quality—the variability of test results and the uncertainty of measurement of microbiological enumeration methods. International Organization for Standardization, Geneva, 2012.
[41]	ISO/IEC Guide 98-4, Uncertainty of measurement—part 4: role of measurement uncertainty in conformity assessment. International Organization for Standardization, Geneva, 2012.
[42]	EA-4/02 M: 2013, Evaluation of the uncertainty of measurement in calibration, 2013. http://www.european-accreditation.org/publication/ea-4-02-m-rev01--september-2013 (Accessed on 23/04/18).
[43]	EA-4/16 G: 2003, EA guidelines on the expression of uncertainty in quantitative testing, 2003. http://www.european-accreditation.org/publication/ea-4-16-g-rev00-december-2003-rev (Accessed on 23/04/18).
[44]	ILAC P10:01/2013, ILAC policy on the traceability of measurement results, International Laboratory Accreditation Cooperation, 2013. http://www.enao-eth.org/publication_documents/ILAC_P10_01_2013%20ILAC%20Policy%20on%20Traceability%20of%20Measurement%20Results.pdf (Accessed on 23/04/18).
[45]	ILAC-P14:01/2013, ILAC Policy for uncertainty in calibration, International Laboratory Accreditation Cooperation, 2013. http://ilac.org/publications-and-resources/ilac-policy-series/ (Accessed on 23/04/18).
[46]	ILAC-G17:2002, Introducing the concept of uncertainty of measurement in testing in association with the application of the Standard ISO/IEC 17025, 2002. http://ilac.org/publications-and-resources/ilac-guidance-series/ (Accessed on 23/04/18).
[47]	S. L. R. Ellison, A. Williams (Eds.), Eurachem/CITAC guide: Quantifying uncertainty in analytical measurement, 3^rd Ed., 2012. https://eurachem.org/images/stories/Guides/pdf/QUAM2012_P1.pdf (Accessed on 24/04/18).
[48]	R. Bettencourt da Silva, A. Williams (Eds.), Eurachem/CITAC Guide: Setting and using target uncertainty in chemical measurement, 1^st Ed., 2015. https://www.eurachem.org/images/stories/Guides/pdf/STMU_2015_EN.pdf (Accessed on 24/04/18).
[49]	S. L. R. Ellison, A. Williams (Eds.), Eurachem/CITAC guide: Use of uncertainty information in compliance assessment, 1^st Ed., 2007. https://www.eurachem.org/images/stories/Guides/pdf/Interpretation_with_expanded_uncertainty_2007_v1.pdf (Accessed on 24/04/18).
[50]	Technical Report No. 1/2007, Measurement uncertainty revisited: Alternative approaches to uncertainty evaluation, 2007. http://www.eurolab.org/documents/1-2007.pdf (Accessed on 24/04/18).
[51]	J. A. Sładek, Classic (nonsimulative) methods of measurement accuracy assessment (Ch. 3), Coordinate Metrology, Springer Tracts in Mechanical Engineering, Springer-Verlag Berlin, Heidelberg, 2016.
[52]	J. A. Sładek, Measurement uncertainty and requirements of production system. Selected issues of measurement uncertainty theory (Ch. 2), Coordinate Metrology, Springer Tracts in Mechanical Engineering, Springer-Verlag Berlin, Heidelberg, 2016.
[53]	M. H. Ramsey, S. L. R Ellison (Eds.), Eurachem/EUROLAB/CITAC/Nordtest/AMC Guide: Measurement uncertainty arising from sampling: a guide to methods and approaches Eurachem, 1^st Ed., 2007. https://www.eurachem.org/images/stories/Guides/pdf/UfS_2007.pdf (Accessed on 24/04/18).
[54]	C. E. de Oliveira Pereira, M. A. Castro e Souza, G. A. Pianetti, S. V. Carvalho de Souza, Overview of proficiency testing provision in pharmaceutical area in Brazil and an educational scheme for determining mefenamic acid in raw materials, Accred. Qual. Assur. 22 (2017) 63-72.
[55]	A. Sorbo, M. Ciprotti, A. Colabucci, C. Zoani, M. Di Gregorio, A. C. Turco, L. Ciaralli, Preparation of an infant formula proficiency testing material and assessment of its homogeneity and stability, Accred. Qual. Assur. 20 (2015) 373-380.
[56]	G. T. Smith, Uncertainty of measurement and statistical process control (Ch. 7), Machine tool metrology, Springer International Publishing, Switzerland, 2016.
[57]	G. T. Smith, Measurement and machine tools—An introduction (Ch. 1), Machine tool metrology, Springer International Publishing, Switzerland, 2016.
[58]	ISO/IEC Guide 99, International vocabulary of metrology -- Basic and general concepts and associated terms (VIM), 2007. https://www.iso.org/obp/ui/#iso:std:iso-iec:guide:99:ed-1:v2:en, fr (Accessed on 25/04/18).
[59]	ISO Guide 34, General requirements for the competence of reference material producers. International Organization for Standardization, Geneva, 2009.
[60]	T. Steiger, R. Pradel, COMAR: the international database for certified reference materials—an overview, Accred. Qual. Assur. 20 (2015) 47-52.
[61]	R. Kaarls, L. Mackay, A. Samuel, D. W. Sin, C. Mok, Y. Wong, Y. Yip, Laboratory capacity building through the use of metrologically traceable reference values in proficiency testing programmes, Accred. Qual. Assur. 22 (2017) 321-334.
[62]	F. de Medeiros Albano, L. H. Faustini, The influence of a quality system according to ISO/IEC 17025 on the performance of Brazilian laboratories in proficiency testing in the environmental area, Accred. Qual. Assur. 21 (2016) 19-23.
[63]	F. M. de Albano, C. S. ten Caten, Proficiency tests for laboratories: a systematic review, Accred. Qual. Assur. 19 (2014) 245-257.
[64]	S. Chakravarty, A. Mohanty, B. Ghosh, M. Tarafdar, S. G. Aggarwal, P. K. Gupta, Proficiency testing in chemical analysis of iron ore: Comparison of statistical methods for outlier rejection, MAPAN-J. Metrol. Soc. India 29 (2014) 87-95.
[65]	W. T. Estler, Traceability, The International Academy for Production Engineering et al. (Eds.), CIRP Encyclopedia of Production Engineering, CIRP, 2016.
[66]	R. L. Mianes, C. S. ten Caten, Organisation of proficiency schemes by testing and calibration laboratories, Accred. Qual. Assur. 22 (2017) 119-123.
[67]	J. Singh, N. Dilawar Sharma, A. Kumar, A. K. Bandyopadhyay, Report of the proficiency testing in the pneumatic pressure region up to 5 MPa, MAPAN-J. Metrol. Soc. India 29 (2014) 213-222.
[68]	A. Jotanovic, S. Suljagic, Comparison of different approaches used for the interpretation and presentation of PT results, Accred. Qual. Assur. 20 (2015) 395-399.
[69]	M. Cotman, A. Pintar, Proficiency testing of wastewater sampling: What did we learn?, Accred. Qual. Assur. 20 (2015) 387-394.
[70]	T. Näykki, M. Leivuori, K. Björklöf, R. Väisänen, M. Laine, T. Väisänen, I. Leito, Proficiency test of pH, conductivity and dissolved oxygen concentration field measurements in river water, Accred. Qual. Assur. 19 (2014) 259-268.
[71]	T. Näykki, S. Koponen, T. Väisänen, T. Pyhälahti, T. Toivanen, I. Leito, Validation of a new measuring system for water turbidity field measurements, Accred. Qual. Assur. 19 (2014) 175-183.
[72]	D. Ghernaout, M. Aichouni, A. Alghamdi, Applying Big Data (BD) in water treatment industry: A new era of advance, Intern. J. Adv. Appl. Sci. 5 (2018) 89-97.
[73]	Y. Chen, Y. Lin, X. Yuan, B. Shen, LIMS and clinical data management (Ch. 9), B. Shen et al. (Eds.), Translational biomedical informatics, Advances in experimental medicine and biology 939, Springer Science+Business Media, Singapore, 2016.
[74]	S. Bouhouche, Advanced quality control systems using intelligent modeling and simulation methods (Ch. 18), C. Kahraman, S. Çevik Onar (Eds.), Intelligent techniques in engineering management, Intelligent Systems Reference Library 87, Springer International Publishing, Switzerland, 2015.
[75]	M. Šućur, D. Ćućilo, Standardization in Bosnia and Herzegovina—Today’s approaches and future challenges, M. Hadžikadić and S. Avdaković (Eds.), Advanced technologies, systems, and applications, Lecture Notes in Networks and Systems 3, Springer International Publishing AG, Berlin, 2017.
[76]	K. Saeed, Can single-operator laboratories comply with all of the requirements of ISO/IEC 17025:2005?, Accred. Qual. Assur. 21 (2016) 305-308.
[77]	D. Ghernaout, M. Aichouni, A. Alghamdi, N. Ait Messaoudene, Big Data: Myths, realities and perspectives: A remote look, American J. Inform. Sci. Technol. 2(1) (2018) 1-8.

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Djamel Ghernaout, Mohamed Aichouni, Abdulaziz Alghamdi. (2018). Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives. International Journal of Science and Qualitative Analysis, 4(3), 83-92. https://doi.org/10.11648/j.ijsqa.20180403.14

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ACS Style

Djamel Ghernaout; Mohamed Aichouni; Abdulaziz Alghamdi. Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives. Int. J. Sci. Qual. Anal. 2018, 4(3), 83-92. doi: 10.11648/j.ijsqa.20180403.14

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AMA Style

Djamel Ghernaout, Mohamed Aichouni, Abdulaziz Alghamdi. Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives. Int J Sci Qual Anal. 2018;4(3):83-92. doi: 10.11648/j.ijsqa.20180403.14

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@article{10.11648/j.ijsqa.20180403.14,
  author = {Djamel Ghernaout and Mohamed Aichouni and Abdulaziz Alghamdi},
  title = {Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives},
  journal = {International Journal of Science and Qualitative Analysis},
  volume = {4},
  number = {3},
  pages = {83-92},
  doi = {10.11648/j.ijsqa.20180403.14},
  url = {https://doi.org/10.11648/j.ijsqa.20180403.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsqa.20180403.14},
  abstract = {The greatest common standard for the expertise of testing and calibration laboratories has recently been bring up to date, considering the newest improvements in laboratory environment and work practices. ISO/IEC 17025:2017, General requirements for the competence of testing and calibration laboratories, is the international reference for laboratories implementing calibration and testing actions through the globe. This article gives a short review on ISO/IEC 17025:2017 and its related data which are increasingly produced every day in the laboratory and suggests Big Data as a fundamental tool of treating such data. ISO/IEC 17025:2017 is gaining a huge part in laboratory legal status and activities; in its side, Big Data is reaching high level of mastery and expansion. On the other hand, there is a huge amount of data around and inside laboratory everyday activities. Besides the experimental and analytical results, there are findings from its financial management. Therefore, Big Data through its enormous capabilities of managing details would imbricate ISO/IEC 17025:2017. The near future would provide more details of how will be the final figure of this intersection.},
 year = {2018}
}

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TY  - JOUR
T1  - Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives
AU  - Djamel Ghernaout
AU  - Mohamed Aichouni
AU  - Abdulaziz Alghamdi
Y1  - 2018/06/14
PY  - 2018
N1  - https://doi.org/10.11648/j.ijsqa.20180403.14
DO  - 10.11648/j.ijsqa.20180403.14
T2  - International Journal of Science and Qualitative Analysis
JF  - International Journal of Science and Qualitative Analysis
JO  - International Journal of Science and Qualitative Analysis
SP  - 83
EP  - 92
PB  - Science Publishing Group
SN  - 2469-8164
UR  - https://doi.org/10.11648/j.ijsqa.20180403.14
AB  - The greatest common standard for the expertise of testing and calibration laboratories has recently been bring up to date, considering the newest improvements in laboratory environment and work practices. ISO/IEC 17025:2017, General requirements for the competence of testing and calibration laboratories, is the international reference for laboratories implementing calibration and testing actions through the globe. This article gives a short review on ISO/IEC 17025:2017 and its related data which are increasingly produced every day in the laboratory and suggests Big Data as a fundamental tool of treating such data. ISO/IEC 17025:2017 is gaining a huge part in laboratory legal status and activities; in its side, Big Data is reaching high level of mastery and expansion. On the other hand, there is a huge amount of data around and inside laboratory everyday activities. Besides the experimental and analytical results, there are findings from its financial management. Therefore, Big Data through its enormous capabilities of managing details would imbricate ISO/IEC 17025:2017. The near future would provide more details of how will be the final figure of this intersection.
VL  - 4
IS  - 3
ER  -

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Author Information

Djamel Ghernaout

Chemical Engineering Department, College of Engineering, University of Ha’il, Ha’il, Saudi Arabia
Mohamed Aichouni

National Initiative on Creativity and Innovation Project, College of Engineering, University of Ha’il, Ha’il, Saudi Arabia
Abdulaziz Alghamdi

National Initiative on Creativity and Innovation Project, College of Engineering, University of Ha’il, Ha’il, Saudi Arabia

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APA Style

Djamel Ghernaout, Mohamed Aichouni, Abdulaziz Alghamdi. (2018). Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives. International Journal of Science and Qualitative Analysis, 4(3), 83-92. https://doi.org/10.11648/j.ijsqa.20180403.14

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ACS Style

Djamel Ghernaout; Mohamed Aichouni; Abdulaziz Alghamdi. Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives. Int. J. Sci. Qual. Anal. 2018, 4(3), 83-92. doi: 10.11648/j.ijsqa.20180403.14

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AMA Style

Djamel Ghernaout, Mohamed Aichouni, Abdulaziz Alghamdi. Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives. Int J Sci Qual Anal. 2018;4(3):83-92. doi: 10.11648/j.ijsqa.20180403.14

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@article{10.11648/j.ijsqa.20180403.14,
  author = {Djamel Ghernaout and Mohamed Aichouni and Abdulaziz Alghamdi},
  title = {Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives},
  journal = {International Journal of Science and Qualitative Analysis},
  volume = {4},
  number = {3},
  pages = {83-92},
  doi = {10.11648/j.ijsqa.20180403.14},
  url = {https://doi.org/10.11648/j.ijsqa.20180403.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsqa.20180403.14},
  abstract = {The greatest common standard for the expertise of testing and calibration laboratories has recently been bring up to date, considering the newest improvements in laboratory environment and work practices. ISO/IEC 17025:2017, General requirements for the competence of testing and calibration laboratories, is the international reference for laboratories implementing calibration and testing actions through the globe. This article gives a short review on ISO/IEC 17025:2017 and its related data which are increasingly produced every day in the laboratory and suggests Big Data as a fundamental tool of treating such data. ISO/IEC 17025:2017 is gaining a huge part in laboratory legal status and activities; in its side, Big Data is reaching high level of mastery and expansion. On the other hand, there is a huge amount of data around and inside laboratory everyday activities. Besides the experimental and analytical results, there are findings from its financial management. Therefore, Big Data through its enormous capabilities of managing details would imbricate ISO/IEC 17025:2017. The near future would provide more details of how will be the final figure of this intersection.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - Overlapping ISO/IEC 17025:2017 into Big Data: A Review and Perspectives
AU  - Djamel Ghernaout
AU  - Mohamed Aichouni
AU  - Abdulaziz Alghamdi
Y1  - 2018/06/14
PY  - 2018
N1  - https://doi.org/10.11648/j.ijsqa.20180403.14
DO  - 10.11648/j.ijsqa.20180403.14
T2  - International Journal of Science and Qualitative Analysis
JF  - International Journal of Science and Qualitative Analysis
JO  - International Journal of Science and Qualitative Analysis
SP  - 83
EP  - 92
PB  - Science Publishing Group
SN  - 2469-8164
UR  - https://doi.org/10.11648/j.ijsqa.20180403.14
AB  - The greatest common standard for the expertise of testing and calibration laboratories has recently been bring up to date, considering the newest improvements in laboratory environment and work practices. ISO/IEC 17025:2017, General requirements for the competence of testing and calibration laboratories, is the international reference for laboratories implementing calibration and testing actions through the globe. This article gives a short review on ISO/IEC 17025:2017 and its related data which are increasingly produced every day in the laboratory and suggests Big Data as a fundamental tool of treating such data. ISO/IEC 17025:2017 is gaining a huge part in laboratory legal status and activities; in its side, Big Data is reaching high level of mastery and expansion. On the other hand, there is a huge amount of data around and inside laboratory everyday activities. Besides the experimental and analytical results, there are findings from its financial management. Therefore, Big Data through its enormous capabilities of managing details would imbricate ISO/IEC 17025:2017. The near future would provide more details of how will be the final figure of this intersection.
VL  - 4
IS  - 3
ER  -

Copy | Download