Interactive Parallel Coordinates Research Articles

Exploratory Data Analysis of Adverse Birth Outcomes and Exposure to Oxides of Nitrogen Using Interactive Parallel Coordinates Plot Technique

We propose that a parallel coordinates plot can be used to study multidimensional data particularly to explore discovery of patterns across the variables. This can assist researchers from the health sciences to visualize their cohort data with interactive data analysis. The study used data from Mother and Child in the Environment birth cohort in Durban, South Africa for the period 2013 to 2017 retrospectively registered. In this paper, we demonstrate that the exploration of multidimensional data with parallel coordinates plot and use of brushing using different colours assists with the identification of relationships and patterns. Parallel coordinates plot visualization facilitates the researcher’s skills to find trends, identify outliers and perform quality checks in large multivariate data. We have identified trends in the data that provide directions for further research, and illustrated thereby the potential of parallel coordinates plot to explore patterns and relationships of prenatal oxides of nitrogen exposure with multidimensional birth outcomes. The study recognized the co-occurrence of adverse birth outcomes among infants and these infants had mothers with moderate to high level of NOx exposure during pregnancy. Brushing using different colours facilitated the detection of patterns of relationships to perform basic and advanced statistical model-based analysis.

Parasol: an open source, interactive parallel coordinates library for multi-objective decision making

This paper introduces Parasol—an open source, interactive visualization library to support the development of web applications for multi-objective decision making. Multi-objective optimization is a popular way to explore competing objectives in environmental management problems. Interactive visualizations allow stakeholders to explore and gain insights about the large, high-dimensional datasets produced by multi-objective optimization. Among visualization methods, parallel coordinates are well-suited for this task. However, current software and open source libraries have limited support for these plots. The Parasol library described in this work provides developers with the building blocks to create sharable, interactive parallel coordinates web applications. Moreover, by incorporating state of the art clutter reduction techniques—such as clustering, linking, brushing, marking, and bundling—Parasol improves upon traditional parallel coordinates visualizations. We demonstrate the benefit of such features through simple examples and by exploring a real-world water resources problem commonly used in multi-objective optimization literature.