Journal:DAQUA-MASS: An ISO 8000-61-based data quality management methodology for sensor data
Full article title | DAQUA-MASS: An ISO 8000-61-based data quality management methodology for sensor data |
---|---|
Journal | Sensors |
Author(s) | Perez-Castillo, Ricardo; Carretero, Ana G.; Caballero, Ismael; Rodriguez, Moises; Piattini, Mario; Mate, Alejandro; Kim, Sunho; Lee, Dongwoo |
Author affiliation(s) | University of Castilla-La Mancha, AQC Lab, University of Alicante, Myongji University, GTOne, |
Primary contact | Email: ricardo dot pdelcastillo @ uclm dot es |
Year published | 2018 |
Volume and issue | 18(9) |
Page(s) | 3105 |
DOI | 10.3390/s18093105 |
ISSN | 1424-8220 |
Distribution license | Creative Commons Attribution 4.0 International |
Website | https://www.mdpi.com/1424-8220/18/9/3105/htm |
Download | https://www.mdpi.com/1424-8220/18/9/3105/pdf (PDF) |
This article should not be considered complete until this message box has been removed. This is a work in progress. |
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 artifacts 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.
Keywords: data quality; data quality management processes; ISO 8000-61; data quality in sensors; internet of things; IoT; smart, connected products; SCPs
Introduction
“Our economy, society, and survival aren’t based on ideas or information—they’re based on things.”[1] This is one of the core foundations of the internet of things (IoT) as stated by Ashton, who coined the term. IoT is an emerging global internet-based information architecture facilitating the exchange of goods and services.[2] IoT systems are inherently built on data gathered from heterogeneous sources in which the volume, variety, and velocity of data generation, exchanging and processing are dramatically increasing.[3] Furthermore, there is a certain emergence of IoT semantic-oriented vision which needs ways to represent and manipulate the vast amount of raw data expected to be generated from and exchanged between the “things.”[4]
References
- ↑ Ashton, K. (2009). "That 'Internet of Things' Thing". RFID Journal 22: 97–114.
- ↑ Weber, R.H. (2013). "Internet of things – Governance quo vadis?". Computer Law & Security Review 29 (4): 341-347. doi:10.1016/j.clsr.2013.05.010.
- ↑ Hassanein, H.S.; Oteafy, S.M.A. (2017). "Big Sensed Data Challenges in the Internet of Things". Proceedings from the 13th International Conference on Distributed Computing in Sensor Systems: 207–8. doi:10.1109/DCOSS.2017.35.
- ↑ Atzori, L.; Iera, A.; Morabito, G. (2010). "The Internet of Things: A survey". Computer Networks 54 (15): 2787-2805. doi:10.1016/j.comnet.2010.05.010.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. Grammar was cleaned up for smoother reading. In some cases important information was missing from the references, and that information was added.