Extremely high correlations between repeated judgments of visual appeal of homepages shown for 50 milliseconds have been interpreted as evidence for a mere exposure effect [Lindgaard et al. 2006]. Continuing that work, the present research had two objectives. First, it investigated the relationship between judgments differing in cognitive demands. Second, it began to identify specific visual attributes that appear to contribute to different judgments. Three experiments are reported. All used the stimuli and viewing time as before. Using a paradigm known to disrupt processing beyond the stimulus offset, Experiment 1 was designed to ensure that the previous findings could not be attributed to such continued processing. Adopting a within-subject design, Experiment 2 investigated the extent to which judgments differing in cognitive demands (visual appeal, perceived usability, trustworthiness) may be driven by the visual characteristics of a Web page. It also enabled analyses of visual attributes that contributed most to the different judgments. Experiment 3 replicated Experiment 2 but using a between-subject design to ensure that no practice effect could occur. The results suggest that all three types of judgments are largely driven by visual appeal, but that cognitively demanding judgments are processed in a qualitatively different manner than visual appeal, and that they rely on somewhat different visual attributes. A model accounting for the results is provided.

This article reports a case study of the iterative design and evaluation of a natural language-driven assistive technology, iGraph-LITE, providing people who are blind access to line graphs. Two laboratory-based usability studies involving blind and sighted people are presented with a discussion of the ensuing implementation of changes. Blind participants were found to adopt different graph interrogation strategies than sighted participants. A small field study is then reported in which a blind user who works with graphs took part to determine the degree to which the iGraph-LITE commands would meet the needs of blind graph experts. The final study invited sighted graph experts and novices to visually inspect and explain a set of line graphs comparable to those used in the usability studies. It aimed to highlight the concepts and the range of words sighted people use, to ascertain the appropriateness of the iGraph-LITE lexicon. A set of preliminary guidelines is presented.

We discuss factors in the design and evaluation of natural language-driven assistive technologies that generate descriptions of, and allow interaction with, graphical representations of numerical data. In particular, we provide data in favor of 1) screen-reading technologies as a usable, useful, and cost-effective means of interacting with graphs. The data also show that by carrying out evaluation of Assistive Technologies on populations other than the target communities, certain subtleties of navigation and interaction may be lost or distorted.

We present Atlas.txt, a novel data-to-text natural language generation system which enables access to geo-referenced information like online census data. We first discuss initial findings from an accessibility study on geo-referenced data and outline needs requirements for visually-impaired users of such data. We then present work towards realising our data-to-text system and indicate how it aims to address this issue.

Designing graphs and charts visually by means of graphing applications such as OpenOffice or MS Excel is extremely efficient and cost-effective. However, one of the drawbacks of such approach is that graphs are sometimes involuntarily made less accessible by, for instance, using a text box as title. In this paper we evaluate a corpus of 120 ecologically-valid statistical graphs for accessibility problems, discuss possible algorithms to solve these problems and finally propose the OM (Object Model) Principle, which states that any digital object is made more accessible by simply using the application's model for that object: for instance, the title field for the title text.