The purpose of this paper is to propose a Data Quality Measurement Model based on ISO 8000 standard. This paper deals about the concepts implied in the measurement process, not about the measures themselves. Poor quality information causes customer dissatisfaction, lost revenue and higher costs associated with additional time to reconcile information. An understanding of the characteristics of the data that determine its quality, and an ability to measure, manage and report on data quality is required. Measurement is a major activity in data quality management. In literature, there are many proposals contributing somehow to the measurement of data quality. However, these measurement methods lack the unification. ISO 8000 provides a framework for improving data quality that can be used independently or in conjunction with quality management systems. ISO 8000 defines characteristics that can be tested by any organization in the data supply chain to objectively determine conformance of the data to ISO 8000.
Godkänd; 2016; Bibliografisk uppgift: Containing selected papers from the ICRESH-ARMS 2015 conference in Lulea, Sweden, collected by editors with years of experiences in Reliability and maintenance modeling, risk assessment, and asset management, this work maximizes reader insights into the current trends in Reliability, Availability, Maintainability and Safety (RAMS) and Risk Management. Featuring a comprehensive analysis of the significance of the role of RAMS and Risk Management in the decision making process during the various phases of design, operation, maintenance, asset management and productivity in Industrial domains, these proceedings discuss key issues and challenges in the operation, maintenance and risk management of complex engineering systems and will serve as a valuable resource for those in the field. ; 20151223 (andbra)