Guidelines for Presenting Quantitative Data in HFES Publications

TLDR

The article adopts a reader‑centered design philosophy that emphasizes understanding users’ tasks, supported operations, and matching them to display capabilities, and discusses how data volume, reader information needs, and visualization value influence the choice among text, tables, or graphs. It offers guidelines for presenting quantitative data that align the sensory, perceptual, and cognitive operations required to read a graph with the operations the graph supports. The article details design decisions for graph selection and construction based on reader experience, informational needs, variable characteristics, and empirical and practice‑based guidelines.

Abstract

This article provides guidelines for presenting quantitative data in papers for publication. The article begins with a reader-centered design philosophy that distills the maxim “know thy user” into three components: (a) know your users′ tasks, (b) know the operations supported by your displays, and (c) match user's operations to the ones supported by your display. Next, factors affecting the decision to present data in text, tables, or graphs are described: the amount of data, the readers′ informational needs, and the value of visualizing the data. The remainder of the article outlines the design decisions required once an author has selected graphs as the data presentation medium. Decisions about the type of graph depend on the readers′ experience and informational needs as well as characteristics of the independent (predictor) variables and the dependent (criterion) variable. Finally, specific guidelines for the design of graphs are presented. The guidelines were derived from empirical studies, analyses of graph readers′ tasks, and practice-based design guidelines. The guidelines focus on matching the specific sensory, perceptual, and cognitive operations required to read a graph to the operations that the graph supports.