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Dynamic data maintenance for quality data, quality research
International Journal of Information Management, 2012Abstract Just like any other scientific research field, the value of data quality is undisputed in the field of transportation. From policy planning to performance evaluation, from model development to impact studies, good quality data is essential to generate ideas and clear-cut solutions to be implemented by transportation professionals and ...
Dilruba Ozmen-Ertekin, Kaan Özbay
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ACM SIGMOD Record, 2018
We outline a call to action for promoting empiricism in data quality research. The action points result from an analysis of the landscape of data quality research. The landscape exhibits two dimensions of empiricism in data quality research relating to type of metrics and scope of method.
Shazia Sadiq +9 more
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We outline a call to action for promoting empiricism in data quality research. The action points result from an analysis of the landscape of data quality research. The landscape exhibits two dimensions of empiricism in data quality research relating to type of metrics and scope of method.
Shazia Sadiq +9 more
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2019
We are living in a world of information abundance, surplus, and access. We have technologies to acquire any type of information but we still face the challenge of extracting the underlying valuable knowledge. Data analyses and mining processes may be severely impaired whenever data are corrupted by noise, ambiguity and distortions.
Alexandra Oliveira +4 more
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We are living in a world of information abundance, surplus, and access. We have technologies to acquire any type of information but we still face the challenge of extracting the underlying valuable knowledge. Data analyses and mining processes may be severely impaired whenever data are corrupted by noise, ambiguity and distortions.
Alexandra Oliveira +4 more
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Studies in health technology and informatics, 2015
The relationship between data quality and data standards has not been clearly articulated. While some directly state that data standards increase data quality, others claim the opposite. Depending on the type of data standard and the aspects of data quality considered, both arguments may in fact be correct.
Meredith Nahm, W. Ed Hammond
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The relationship between data quality and data standards has not been clearly articulated. While some directly state that data standards increase data quality, others claim the opposite. Depending on the type of data standard and the aspects of data quality considered, both arguments may in fact be correct.
Meredith Nahm, W. Ed Hammond
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Proceedings of the 29th ACM International Conference on Information & Knowledge Management, 2020
Data quality issues have been widely recognized in IoT data, and prevent the downstream applications. In this tutorial, we review the state-of-the-art techniques for IoT data quality management. In particular, we discuss how the dedicated approaches improve various data quality dimensions, including validity, completeness and consistency. Among others,
Shaoxu Song, Aoqian Zhang
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Data quality issues have been widely recognized in IoT data, and prevent the downstream applications. In this tutorial, we review the state-of-the-art techniques for IoT data quality management. In particular, we discuss how the dedicated approaches improve various data quality dimensions, including validity, completeness and consistency. Among others,
Shaoxu Song, Aoqian Zhang
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Proceedings of the 2nd international workshop on Information quality in information systems, 2005
In the field of sensor networks, data integration and collaboration, and intelligence gathering efforts, information on the quality of data sources are important but are often not available. We describe a technique to rank data sources by observing and comparing their behavior (i.e., the data produced by data sources) to rank.
Raymond K. Pon, Alfonso F. Cardenas
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In the field of sensor networks, data integration and collaboration, and intelligence gathering efforts, information on the quality of data sources are important but are often not available. We describe a technique to rank data sources by observing and comparing their behavior (i.e., the data produced by data sources) to rank.
Raymond K. Pon, Alfonso F. Cardenas
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Nursing Management, 2010
The Healthcare Quality Improvement Partnership has produced a guide covering all aspects of data collection, from what data quality means and how to improve it, to how to ensure that the purpose or objective ofclinical audits clearly identifies the nature of the data needed.
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The Healthcare Quality Improvement Partnership has produced a guide covering all aspects of data collection, from what data quality means and how to improve it, to how to ensure that the purpose or objective ofclinical audits clearly identifies the nature of the data needed.
openaire +2 more sources