Dongwoo Lee
Research Subjects
Dongwoo Lee has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Alejandro Mate
Lucentia Lab, University of Alicante, 03690 San Vicente del Raspeig, Alicante, Spain
1 shared publication - Ana G. Carretero
Information Technologies & Systems Institute (ITSI), University of Castilla-La Mancha, 13071 Ciudad Real, Spain
1 shared publication - Ismael Caballero
University of Castilla-La Mancha (UCLM)
1 shared publication - Mario Piattini
University of Castilla-la Mancha, Ciudad Real, Spain
1 shared publication - Moisés Rodríguez
Castilla-La Mancha University, Ciudad Real, Spain
1 shared publication - Ricardo Pérez-Castillo
Universidad de Castilla-La Mancha
1 shared publication
Latest Publications
- Open Access
DAQUA-MASS: An ISO 8000-61 Based Data Quality Management Methodology for Sensor Data
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.
Open AccessDAQUA-MASS: An ISO 8000-61 Based Data Quality Management Methodology for Sensor Data
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.