Escaping RGBland: Selecting Colors for Statistical Graphics

Statistical graphics are often augmented by the use of color coding information contained in some variable. When this involves the shading of areas (and not only points or lines) - e.g., as in bar plots, pie charts, mosaic displays or heatmaps - it is important that the colors are perceptually based and do not introduce optical illusions or systematic bias. Here, we discuss how the perceptually-based Hue-Chroma-Luminance (HCL) color space can be used for deriving suitable color palettes for coding categorical data (qualitative palettes) and numerical variables (sequential and diverging palettes).Series: Research Report Series / Department of Statistics and Mathematic

Evaluating global e-government sites: A view using web diagnostics tools

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2004 The AuthorsSeveral governments across the world have embraced the digital revolution and continue to take advantage of the information and communication facilities offered by the Internet to offer public services. Conversely, citizens’ awareness and expectations of Internet based online-public-services have also increased in recent times. Although the numbers of the different national e-Government web portals have rapidly increased in the last three years, the success of these portals will largely depend on their accessibility, quality and privacy. This paper reports the results of an evaluative study of a cross-section of e-Government portals from these three perspectives, using a common set of performance metrics and Web diagnostic engines. Results show that not only are there wide variations in the spectrum of information and services provided by these portals, but that significant work still needs to be undertaken in order to make the portals examples of ‘best practice’ e-Government services

An image-based visual strategy for working with color contrasts during design

acceptedVersio

Predicting visual similarity between colour palettes

This work is concerned with the prediction of visual colour difference between pairs of palettes. In this study, the palettes contained five colours arranged in a horizontal row. A total of 95 pairs of palettes were rated for visual difference by 20 participants. The colour difference between the palettes was predicted using two algorithms, each based on one of six colour‐difference formulae. The best performance (r2 = 0.86 and STRESS = 16.9) was obtained using the minimum colour‐difference algorithm (MICDM) using the CIEDE2000 equation with a lightness weighing of 2. There was some evidence that the order (or arrangement) of the colours in the palettes was a factor affecting the visual colour differences although the MICDM algorithm does not take order into account. Application of this algorithm is intended for digital design workflows where colour palettes are generated automatically using machine learning and for comparing palettes obtained from psychophysical studies to explore, for example, the effect of culture, age, or gender on colour associations

A scientometric analysis of 15 years of CHINZ conferences

CHINZ is the annual conference of the New Zealand Chapter of the Special Interest Group for Computer-Human Interaction (SIGCHI) of the ACM. In this paper we analyse the history of CHINZ through citations, authorship and online presence. CHINZ appears to compare well with the larger APCHI conference on citation-based measures. 42% of CHINZ papers were found as open access versions on the web