Data Quality: Concepts, Methodologies and Techniques

By Carlo Batini, M. Scannapieco. 2006

914 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/7ac5fce051e3f193ac92df65664f13cb2700ceef

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Citations in the corpus

A Comprehensive Framework for Intrinsic OpenStreetMap Quality Analysis (2014, background): “However, as stated by Batini and Scannapieco (2006), intrinsic data quality analyses capture the data’s inherent quality and according to Wang and Strong (1996) and Batini and Scannapieco (2006) it includes the following dimensions: accuracy, objectivity, believability and reputation.”
Data quality: A survey of data quality dimensions (2012, methodology): “Table I”
Data Matching (2012, methodology): “Most real-world databases contain noisy, inconsistent and missing data due to a variety of factors [19, 135, 218].”
Holistic data cleaning: Putting violations into context (2013, unknown): “For an instance I of S , and an attribute A ∈ U , and a tuple t , we denote by Dom ( A ) the domain of attribute A .”
A Survey on Data Quality: Classifying Poor Data (2015, background): “A dimension is a measurable data quality property that represents some aspect of the data (e.g., accuracy, consistency) that can be used to guide the process of understanding quality [15], [16], [9].”
Big data integration (2013, background): “Algorithm AccuCopy starts by setting the same accuracy for each source and the same probability for each value, then iteratively (1) computes probabilities of copying based on the probabilities of values computed in the previous round, (2) updates probabilities of values, and (3) updates accuracy of”
Methodologies for data quality assessment and improvement (2009, methodology): “The quality of data is recognized as a relevant performance issue of operating processes [Data Warehousing Institute 2006], of decision-making activities [Chengalur-Smith et al. 1999], and of interorganizational cooperation requirements [Batini and Scannapieco 2006].”
Quality assessment for Linked Data: A Survey (2015, methodology): “Additionally, there is a comprehensive review [4], which surveys 13 methodologies for assessing the data quality of datasets available on the Web, in structured or semi-structured formats.”
Open data quality measurement framework: Definition and application to Open Government Data (2016, background): “(Batini & Scannapieco, 2006), (Heinrich, 2002), (Kaiser et al., 2007).”
Evaluation of entity resolution approaches on real-world match problems (2010, unknown): “Recent surveys include [2], [20], and [24].”