DAQUA-MASS: An ISO 8000-61 Based Data Quality Management Methodology for Sensor Data

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Título: DAQUA-MASS: An ISO 8000-61 Based Data Quality Management Methodology for Sensor Data
Autor/es: Perez-Castillo, Ricardo | Carretero, Ana G. | Caballero, Ismael | Rodriguez, Moises | Piattini, Mario | Maté, Alejandro | Kim, Sunho | Lee, Dongwoo
Grupo/s de investigación o GITE: Lucentia
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos
Palabras clave: Data quality | Data quality management processes | ISO 8000-61 | Data quality in sensors | Internet-of-Things | IoT | Smart, Connected Products | SCPs
Área/s de conocimiento: Lenguajes y Sistemas Informáticos
Fecha de publicación: 14-sep-2018
Editor: MDPI
Cita bibliográfica: Perez-Castillo R, Carretero AG, Caballero I, Rodriguez M, Piattini M, Mate A, Kim S, Lee D. DAQUA-MASS: An ISO 8000-61 Based Data Quality Management Methodology for Sensor Data. Sensors. 2018; 18(9):3105. doi:10.3390/s18093105
Resumen: 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.
Patrocinador/es: This work was primarily funded by DQIoT project (Eureka program, E!11737; and CDTI (Centro Para el Desarrollo Tecnológico Industrial), INNO-20171086). Additionally, this work was partially funded by SEQUOIA project (TIN2015-63502-C3-1-R and TIN2015-63502-C3-3-R) (MINECO/FEDER); GEMA SBPLY/17/180501/000293, Consejería de Educación, Cultura y Deporte de la Dirección General de Universidades, Investigación e Innovación de la JCCM); ECD project (Evaluación y Certificación de la Calidad de Datos) (PTQ-16-08504) (Torres Quevedo Program, MINECO). Finally, it was also supported through a grant to Ricardo Pérez-Castillo enjoys from JCCM within the initiatives for talent retention and return in line with RIS3 goals.
URI: http://hdl.handle.net/10045/79749
ISSN: 1424-8220
DOI: 10.3390/s18093105
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Revisión científica: si
Versión del editor: https://doi.org/10.3390/s18093105
Aparece en las colecciones:INV - LUCENTIA - Artículos de Revistas

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