Integrating Data and Quality Space Interactions in Exploratory Visualizations

Xie, Zhen; Ward, Matthew O.; Rundensteiner, Elke A.; Huang, Shiping

doi:10.1109/cmv.2007.11

Cited by 6 publications

(5 citation statements)

References 19 publications

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“…Quality maps. Xie et al 15 introduced quality maps, a visualization technique that represents the data quality for a data set. This technique takes each attribute of the data set and represents its quality using stripes.…”

Section: Applicationsmentioning

confidence: 99%

“…Many theoretical approaches have been proposed by MacEachren et al, 10 Pang, 8 and Griethe and Schumann. 11 Moreover, several applications have been implemented by researchers like Cui et al, 17 Collins et al, 18 Xie et al, 15 Olston and Mackinlay, 19 and Potter et al, 20 including empirical approaches proposed by MacEachren et al 9 However, there is no broadly accepted definition of uncertainty. 8,21 In computer science, uncertainty is described using metrics of quality called DQDs proposed by Batini and Scannapieco.…”

Section: Data Qualitymentioning

confidence: 99%

“…Moreover, a set of processes considers data quality, 15,[30][31][32] but only in a descriptive way and DQ is not included while performing the analysis or the decisionmaking process.…”

Section: Dqd/data Typementioning

confidence: 99%

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VafusQ: A methodology to build visual analysis applications with data quality features

Triana

Zeckzer

Hagen

et al. 2018

Information Visualization

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The use of interactive applications to support the decision-making process is more common every day. However, a huge amount of data is required in order to make more informed decisions. Fortunately, with the arrival of new technologies there are many data sources available. This requirement of data causes heterogeneity and data quality problems. A set of data quality problems are reduced in the preprocessing stage. However, many data quality issues persist after the preprocessing stage. For this reason, we proposed a methodology to take the data quality problems, to represent them and simultaneously support the analysis process. In addition, an application is developed as a use case of the methodology by analyzing the public transport system in Bogotá. Furthermore, a case study is performed to test the usefulness of the developed application. As a result, the methodology made possible the development of interactive visualizations that constitute an application that is useful to achieve the analysis tasks by including data quality features.

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Section: Applicationsmentioning

confidence: 99%

Section: Data Qualitymentioning

confidence: 99%

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VafusQ: A methodology to build visual analysis applications with data quality features

Triana

Zeckzer

Hagen

et al. 2018

Information Visualization

View full text Add to dashboard Cite

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“…This type of selection could conceivably be considered both direct and indirect, as the operation is performed on a visualization, but not on the data display itself. Similar to structure-based brushing, other attributes of a data set, such as the uncertainty or quality of the data [13], could be used as a focus for brushing.…”

Section: Foundationsmentioning

confidence: 99%

Linking and Brushing

Ward¹

2016

Encyclopedia of Database Systems

Self Cite

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Linked brushing; Linked views Definition Within the context of visual data exploration, Linking refers to the process in which user interactions in one display of a multi-display system are applied to some or all other displays. In this same context, brushing consists of the interactive selection of a subset of the displayed data by either dragging the mouse over the data of interest or using a bounding shape to isolate this subset. Together, linked brushing is one of the most powerful interactive tools for doing exploratory data analysis using visualization.

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“…Regarding interactive interfaces and techniques for quality-aware data information exploration and transformation, Xie et al [3] created an interactive interface to enable users to explicitly explore that data quality information. They also created a framework for the coupling data space and quality space for producing multivariate visualizations.…”

Section: Interactive Interfaces and Visualization Techniquesmentioning

confidence: 99%

A Model to Promote Interaction between Humans and Data Fusion Intelligence to Enhance Situational Awareness

Botega

Berti

Araújo

et al. 2014

Lecture Notes in Computer Science

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The operator of a Command & Control (C2) system has a crucial role on the improvement of information that is processed through data fusion engines to provide Situational Awareness (SAW). Through direct access to data transformations, operators can improve information quality, by reducing uncertainty, according to their skills and expertise. Uncertainty, in this work, is considered an adverse condition, which can make the real information less accessible. Although relevant solutions have been reported in the literature on innovative user interfaces and approaches for quality-aware knowledge representation, these are concerned mostly on transforming the way information is graphically represented and on quantitatively mapping the quality-aware knowledge acquired from systems, respectively. There are few studies that deal more specifically with accessibility for decision-makers in safety-critical situations, such as C2, considering the aspect of data uncertainty. This paper presents a model to help researchers to build uncertainty-aware interfaces for C2 systems, produced by both data fusion and human reasoning over the information. Combined to environmental and personal factors, a tailored and enriched knowledge can be built, interchangeable with systems intelligence. A case study on the monitoring of a conflict among rival soccer fans is being implemented for the validation of the proposed solution.

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Integrating Data and Quality Space Interactions in Exploratory Visualizations

Abstract: Abstract

Cited by 6 publications

References 19 publications

VafusQ: A methodology to build visual analysis applications with data quality features

VafusQ: A methodology to build visual analysis applications with data quality features

Linking and Brushing

A Model to Promote Interaction between Humans and Data Fusion Intelligence to Enhance Situational Awareness

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