Difference between revisions of "Template:Article of the week"

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Perez-Castillo Sensors2018 18-9.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Anx1 WHO 2020 2020.5.png|240px]]</div>
'''"[[Journal:DAQUA-MASS: An ISO 8000-61-based data quality management methodology for sensor data|DAQUA-MASS: An ISO 8000-61-based data quality management methodology for sensor data]]"'''
'''"[[Journal:Laboratory testing for coronavirus disease (COVID-19) in suspected human cases|Laboratory testing for coronavirus disease (COVID-19) in suspected human cases]]"'''


The [[internet of things]] (IoT) introduces several technical and managerial challenges when it comes to the use of data generated and exchanged by and between various smart, connected products (SCPs) that are part of an IoT system (i.e., physical, intelligent devices with sensors and actuators). Added to the volume and the heterogeneous exchange and consumption of data, it is paramount to [[Quality assurance|assure]] that data quality levels are maintained in every step of the data chain/lifecycle. Otherwise, the system may fail to meet its expected function. While data quality (DQ) is a mature field, existing solutions are highly heterogeneous. Therefore, we propose that companies, developers, and vendors should align their data quality management mechanisms and artifacts with well-known best practices and [[Specification (technical standard)|standards]], as for example, those provided by ISO 8000-61. This standard enables a process-approach to data quality management, overcoming the difficulties of isolated data quality activities. This paper introduces DAQUA-MASS, a methodology based on ISO 8000-61 for data quality management in sensor networks. ('''[[Journal:DAQUA-MASS: An ISO 8000-61-based data quality management methodology for sensor data|Full article...]]''')<br />
This document provides interim guidance to [[Laboratory|laboratories]] and stakeholders involved in [[COVID-19]] virus laboratory testing of patients. It is based in part on the interim guidance on laboratory testing for [[Middle East respiratory syndrome]] (MERS) coronavirus. [[Information]] on human [[infection]] with the COVID-19 virus is evolving and the [[World Health Organization]] (WHO) continues to monitor developments and revise recommendations as necessary. This document will be revised as new information becomes available. Feedback is welcome and can be sent to WHElab@who.int. The virus has now been named SARS-CoV-2 by the International Committee of Taxonomy of Viruses (ICTV)(2). This virus can cause the disease named coronavirus disease 2019 (COVID-19). WHO refers to the virus as COVID-19 virus in its current documentation. ('''[[Journal:A security review of local government using NIST CSF: A case study|Full article...]]''')<br />
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Revision as of 15:46, 23 March 2020

Anx1 WHO 2020 2020.5.png

"Laboratory testing for coronavirus disease (COVID-19) in suspected human cases"

This document provides interim guidance to laboratories and stakeholders involved in COVID-19 virus laboratory testing of patients. It is based in part on the interim guidance on laboratory testing for Middle East respiratory syndrome (MERS) coronavirus. Information on human infection with the COVID-19 virus is evolving and the World Health Organization (WHO) continues to monitor developments and revise recommendations as necessary. This document will be revised as new information becomes available. Feedback is welcome and can be sent to WHElab@who.int. The virus has now been named SARS-CoV-2 by the International Committee of Taxonomy of Viruses (ICTV)(2). This virus can cause the disease named coronavirus disease 2019 (COVID-19). WHO refers to the virus as COVID-19 virus in its current documentation. (Full article...)

Recently featured:

▪ One tool to find them all: A case of data integration and querying in a distributed LIMS platform
▪ What is the "source" of open-source hardware?
▪ From command-line bioinformatics to bioGUI
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