We present the old-but-also-new problem of data quality from a statistical perspective, in part with the goal of attracting more statisticians, especially academics, to become engaged in research on a rich set of exciting challenges. The data quality landscape is described, and its research foundations in computer science, total quality management and statistics are reviewed. Two case studies based on an EDA approach to data quality are used to motivate a set of research challenges for statistics that span theory, methodology and software tools
While some research has been done to identify the dimensions of data quality and to develop methodol...
Data quality (DQ) has been studied in significant depth over the last two decades and has received a...
https://doi.org/10.21949/14046031997PDFTech ReportDOT HS 808 597Statistical quality controlEmpirical...
Research and practice in data and information quality is characterized by methodological as well as ...
Data quality is a problem studied in many different research disciplines like computer science, stat...
We outline a call to action for promoting empiricism in data quality research. The action points res...
The body of knowledge on data and information quality is highly diversified, primarily due to the cr...
Data Quality is a cross-disciplinary and often do-main specic problem due to the importance of t-nes...
The issue of data quality is as old as data itself. However, the proliferation of diverse, large-sca...
Data quality is crucial in measuring and analyzing science, technology and innovation adequately, wh...
Data quality has been an active area of information systems research, particularly in the 1990s. For...
Although contemporary research relies to a large extent on data, data quality in Information Systems...
Regardless of the field of study, sharing data is one of the most fundamental aspects of maintaining...
The aim of this review is to highlight issues in data quality research and to discuss potential rese...
Attribute data quality is important object for each databases. If data quality doesn’t useful,...
While some research has been done to identify the dimensions of data quality and to develop methodol...
Data quality (DQ) has been studied in significant depth over the last two decades and has received a...
https://doi.org/10.21949/14046031997PDFTech ReportDOT HS 808 597Statistical quality controlEmpirical...
Research and practice in data and information quality is characterized by methodological as well as ...
Data quality is a problem studied in many different research disciplines like computer science, stat...
We outline a call to action for promoting empiricism in data quality research. The action points res...
The body of knowledge on data and information quality is highly diversified, primarily due to the cr...
Data Quality is a cross-disciplinary and often do-main specic problem due to the importance of t-nes...
The issue of data quality is as old as data itself. However, the proliferation of diverse, large-sca...
Data quality is crucial in measuring and analyzing science, technology and innovation adequately, wh...
Data quality has been an active area of information systems research, particularly in the 1990s. For...
Although contemporary research relies to a large extent on data, data quality in Information Systems...
Regardless of the field of study, sharing data is one of the most fundamental aspects of maintaining...
The aim of this review is to highlight issues in data quality research and to discuss potential rese...
Attribute data quality is important object for each databases. If data quality doesn’t useful,...
While some research has been done to identify the dimensions of data quality and to develop methodol...
Data quality (DQ) has been studied in significant depth over the last two decades and has received a...
https://doi.org/10.21949/14046031997PDFTech ReportDOT HS 808 597Statistical quality controlEmpirical...