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DAQUA-MASS: An ISO 8000-61 Based Data Quality Management Methodology for Sensor Data.
Perez-Castillo, Ricardo; Carretero, Ana G; Caballero, Ismael; Rodriguez, Moises; Piattini, Mario; Mate, Alejandro; Kim, Sunho; Lee, Dongwoo.
Afiliação
  • Perez-Castillo R; Information Technologies & Systems Institute (ITSI), University of Castilla-La Mancha, 13071 Ciudad Real, Spain. ricardo.pdelcastillo@uclm.es.
  • Carretero AG; Information Technologies & Systems Institute (ITSI), University of Castilla-La Mancha, 13071 Ciudad Real, Spain. anaisabel.gomez@uclm.es.
  • Caballero I; Information Technologies & Systems Institute (ITSI), University of Castilla-La Mancha, 13071 Ciudad Real, Spain. ismael.caballero@uclm.es.
  • Rodriguez M; Information Technologies & Systems Institute (ITSI), University of Castilla-La Mancha, 13071 Ciudad Real, Spain. moises.rodriguez@uclm.es.
  • Piattini M; AQC Lab, 13051 Ciudad Real, Spain. moises.rodriguez@uclm.es.
  • Mate A; Information Technologies & Systems Institute (ITSI), University of Castilla-La Mancha, 13071 Ciudad Real, Spain. mario.piattini@uclm.es.
  • Kim S; AQC Lab, 13051 Ciudad Real, Spain. mario.piattini@uclm.es.
  • Lee D; Lucentia Lab, University of Alicante, 03690 San Vicente del Raspeig, Alicante, Spain. amate@lucentialab.es.
Sensors (Basel) ; 18(9)2018 Sep 14.
Article em En | MEDLINE | ID: mdl-30223516
ABSTRACT
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 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 artefacts with well-known best practices and 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. The methodology consists of four steps according to the Plan-Do-Check-Act cycle by Deming.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline Idioma: En Revista: Sensors (Basel) Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Espanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline Idioma: En Revista: Sensors (Basel) Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Espanha