@conference{427,
  keywords = {Visualization, metrics, data quality},
  author = {Christian Bors and Theresia Gschwandtner and Silvia Miksch},
  title = {QualityFlow: Provenance Generation from Data Quality},
  abstract = {
	
		
			If properly recorded, provenance information of a data set reveals the story about its origins, which hands it passed through, and how the data has been modified. Moreover, each data operation may have considerable impact on the quality of the data set. This information is of great value for anyone who needs to decide if the quality of a data set is sufficient for further processing. However, current approaches in data quality assessment feature only a limited amount of provenance information. We present the interactive QualityFlow visualization that provides the history of operations on a data set and their influence on respective data quality metrics to support sense-making. QualityFlow allows users to explore this information and share their insights with collaborators. 
		
	

 
},
  year = {2015},
  journal = {Proceedings of the Eurographics Conference on Visualization (EuroVis) - Posters 2015},
  pages = {3},
  publisher = {The Eurographics Association},
  address = {Cagliari, Sardinia, Italy},
  url = {http://publik.tuwien.ac.at/files/PubDat_239176.pdf},
  note = {Posterpräsentation: Eurographics Conference on Visualization (EuroVis 2015), Cagliari, Sardinia, Italy; 2015-05-25 – 2015-05-29
},
}