Preface

In the current information era, most aspects of life depend on and are driven by data, information, knowledge, user experience, and culture. The infrastructure of an information-dependent society relies on the quality of data, information and analysis of such entities for short to long term as well as past to future activities. Information Visualisation, Visual Analytics, Business Intelligence, Machine Learning and Application domains are just a few of the current state of the art developments that effectively enhance understanding of these driving forces

The Future of Mobility with Connected and Autonomous Vehicles in Smart Cities

Cities around the world are being wrecked by the ever-increasing bur-den of traffic. Smart cities are a recent innovation perceived as a winning strategy to cope with some severe urban problems such as traffic, pollution, energy consumption, waste treatment. This concept is attracting significant interest in the world of technology and sensors. Governments can streamline the way cities are run, saving money and making them more efficient as a result. Rapid urban developments, sustainable transportation solutions are required to meet the increasing demands for mobility whilst mitigating the potentially negative social, economic, and environmental impacts. This study analyses the smart mobility initiatives and the challenges for smart cities with connected and autonomous vehicles (CAVs), it also highlights the literature that supports why CAVs are essential for smart maintainable development as part of the intelligent transportation system (ITS)

Conceptualising Green Awareness as Moderator in Technology Acceptance Model for Green IS/IT

Green Information System/Technology adoption is one of the key solutions sought by organisations, policy makers and governments to promote sustainability and deal with environmental issues. Surprisingly, in the research discipline of management information systems measuring the intention of decision maker to adopt Green IS/IT is ignored while only a few studies address the issue of Green IS/IT adoption. But these studies are mostly done in organisational manner and consistently lack to conceptualise the role of Green Awareness or environmental literacy of the end user that may play the role of the facilitator to such adoption models and can significantly moderate the relationship of users' cognitive and behavioural intention factors in decision making process of adopting Green IS/IT. To fill this gap in the Green IS/IT literature, this paper conceptualise the role of Green Awareness as a facilitator by incorporating a subjective green awareness rating scale as a moderator in Technology Acceptance Model. This paper contributes to the existing knowledge in the science of information systems, mapping users' intention to adopt Green IS/IT and sustainability by conceptualising green awareness rating scale for users and a theoretical framework of incorporating the scale in Technology Acceptances model to map its role as a moderator

Evaluation of Visualization by Critiques

In this position paper, we extend design critiques as a form of evaluation to visualization, specifically focusing on unique qualities of critiques that are different than other types of evaluation by inspection, such as heuristic evaluation, models, reviews or written criticism. Critiques can be used to address a broader scope and context of issues than other inspection techniques; and utilize bi-direction dialogue with multiple critics, including non-visualization critics

Texture mapping in a distributed environment

This paper presents a tool for texture mapping in a distributed environment. A parallelization method based on the master-slave model is described. The purpose of this work is to lower the image generation time in the complex 3D scenes synthesis process. The experimental results concerning the speedup of texture mapping algorithm are also presented.

Using text in visualizations for micro/macro readings

This paper presents techniques for creating micro/macro encoding in text visualization using text and font-attributes. Alphanumeric Marks increase information density in standard plots using alphanumeric markers to provide additional micro-level information. In-Context Representations layer additional macro-level data into traditional text lists and blocks using font-based attributes to make high-level patterns easily perceivable. This is a work in progress with novel design contributions regarding generalized use of text and font attributes in visualization

Stem and leaf plots extended for text visualizations

© 2017 IEEE. Stem and leaf plots are data dense visualizations that organize large amounts of micro-level numeric data to form larger macro-level visual distributions. These plots can be extended with font attributes and different token lengths for new applications such as n-grams analysis, character attributes, set analysis and text repetition

Stem & Leaf Plots Extended to Various Ranges of Text

Stem and leaf plots are data dense visualizations that organize large amounts of micro-level numeric data to form larger macro-level visual distributions. These plots can be extended with font attributes and different token lengths for new applications such as n-grams analysis, character attributes, set analysis and text repetition

Using font attributes in knowledge maps and information retrieval

Font specific attributes, such as bold, italic and case can be used in knowledge mapping and information retrieval to encode additional data in texts, lists and labels to increase data density of visualizations; encode data quantitative data into search lists; and facilitate text skimming and refinement by visually promoting of words of interest

Typographic sets: Labeled set elements with font attributes

We show that many different set visualization techniques can be extended with the addition of labeled elements using font attributes. Elements labeled with font attributes can: uniquely identify elements; encode membership in ten sets; use size to indicate proportions among set relations; can scale to thousands on clearly labeled elements; and use intuitive mappings to facilitate decoding. The approach can be applied to many different set visualization layouts, including Venn and Euler diagrams, graphs, mosaic plots and cartograms