Software Tools and Evaluation Models for Visual Analytics: Trends, Challenges, and Future Directions

Visual analytics (VA) is a complex interdisciplinary field which applies data visualization and analysis methods in order to extract knowledge from Big Data. This paper aims at presenting an overview of the most common software tools and assessment frameworks for VA with an emphasis on the open source, commercial and specific tools for BI, healthcare and scientific purposes. It discusses the issues that VA has concerning varied data types, their usability and how the system can be expanded to accommodate large data sets. The paper also considers recent trends in AI and machine learning, virtual and augmented reality, and synchronous shared environments. Privacy and data bias issues are also drawn out as ethical concerns. Last, the paper presents the directions of further research to enhance the efficiency and usability of VA tools and make them more ethical in data decision-making.