Information Visualization in Research Reporting: Guidelines for Representing Quantitative Data

Abstract

This paper presents guidelines for information visualization in quantitative research reporting in a step-wise and graphical format. The ease of use and availability of statistical packages has led to widespread use of statistical methods for information visualization. Without knowledge of statistics or easy-to-follow guidelines there is a very real potential for invalid or incorrect visualizations to be used. This compromises the validity and effectiveness of the research reporting. Here we address this deficiency by proposing a set of guidelines presented as a decision tree to guide the choice of visualization format for maximizing the effectiveness of quantitative data in academic reporting. In this paper we provide a content analysis of the literature on guidelines for statistical analysis from a knowledge visualization perspective. This was triangulated with a set of heuristics gained from experience in providing statistical support on research reporting to masters and doctoral students at the University of South Africa over a period of 11 years. The resulting analysis was integrated and contextualized to derive a set of Guidelines for Visualization of Quantitative data in Academic Reporting (VisQuAR). These guidelines will serve to inform the efforts of students engaged in research reporting and also to support research supervisors who have not been specifically trained in the use of statistical methods.