Many systems for exploratory and visual data analytics require platform-dependent software installation, coding skills, and analytical expertise. The rapid advances in data-acquisition, web-based information, and communication and computation technologies promoted the explosive growth of online services and tools implementing novel solutions for interactive data exploration and visualization. However, web-based solutions for visual analytics remain scattered and relatively problem-specific.
View Article and Find Full Text PDFStatistical inference involves drawing scientifically-based conclusions describing natural processes or observable phenomena from datasets with intrinsic random variation. There are parametric and non-parametric approaches for studying the data or sampling distributions, yet few resources are available to provide integrated views of data (observed or simulated), theoretical concepts, computational mechanisms and hands-on utilization via flexible graphical user interfaces. We designed, implemented and validated a new portable randomization-based statistical inference infrastructure (http://socr.
View Article and Find Full Text PDFProc 2nd Workshop Hum Loop Data Anal (2017)
April 2017
The modern web is a successful platform for large scale interactive web applications, including visualizations. However, there are no established design principles for building complex visual analytics (VA) web applications that could efficiently integrate visualizations with data management, computational transformation, hypothesis testing, and knowledge discovery. This imposes a time-consuming design and development process on many researchers and developers.
View Article and Find Full Text PDF