Living Globe: Tridimensional interactive visualization of world demographic data

This paper presents Living Globe, an application for visualization of demo- graphic data supporting the temporal comparison of data from several countries represented on a 3D globe. Living Globe allows the visual exploration of the following demographic data: total population, population density and growth, crude birth and death rates, life expectancy, net migration and population per- centage of different age groups. While offering unexperienced users a default mapping of these data variables into visual variables, Living Globe allows more advanced users to select the mapping, increasing its flexibility. The main aspects of the Living Globe model and prototype are described as well as the evaluation results obtained using heuristic evaluation and usability testing. Some conclusions and ideas for future work are also presented.Comment: 11 pages, 6 figures, submitted to HCII 2016 Conference (Toronto, Canada), published on Human Interface and the Management of Information: Information, Design and Interaction Volume 9734 of the series Lecture Notes in Computer Science, pages 14-2

The use of the flux plot in traffic

"Reprinted from Traffic Quarterly July 1965.""July 1965.""During the summer of 1963 the authors used fixed-time interval pictures to study traffic characteristics on a short section of Highway 400, Ontario. The purpose of the study was to obtain density-flow relationships, particularly a flux plot of the traffic for all speeds. Unfortunately, no "jams" occurred, so the low-speed (below 30 miles per hour) data on time flows were obtained on the Queen Elizabeth Way at St. Catharines, Ontario. The section on Highway 400 was isolated from merging and diverging maneuvers. The values on the charts represent observations from a short section (900-1, 600 feet) for small intervals of time extrapolated to commonly used measurements of vehicles per hour and vehicles per mile. The flux plots shown herein were derived from approximately 1, 100 observations of each lane."--Page 36

Provenance analysis for sensemaking. IEEE Computer Graphics and Applications, 39 (6) . pp. 27-29. ISSN 0272-1716

The articles in this special section examine the concept of "sensemaking", which refers to how we structure the unknown so as to be able to act in it. In the context of data analysis it involves understanding the data, generating hypotheses, selecting analysis methods, creating novel solutions, and critical thinking and learning wherever needed. Due to its explorative and creative nature, sensemaking is arguably the most challenging part of any data analysis

Provenance and logging for sense making

Sense making is one of the biggest challenges in data analysis faced by both the industry and the research community. It involves understanding the data and uncovering its model, generating a hypothesis, selecting analysis methods, creating novel solutions, designing evaluation, and also critical thinking and learning wherever needed. The research and development for such sense making tasks lags far behind the fast-changing user needs, such as those that emerged recently as the result of so-called “Big Data”. As a result, sense making is often performed manually and the limited human cognition capability becomes the bottleneck of sense making in data analysis and decision making. One of the recent advances in sense making research is the capture, visualization, and analysis of provenance information. Provenance is the history and context of sense making, including the data/analysis used and the users’ critical thinking process. It has been shown that provenance can effectively support many sense making tasks. For instance, provenance can provide an overview of what has been examined and reveal gaps like unexplored information or solution possibilities. Besides, provenance can support collaborative sense making and communication by sharing the rich context of the sense making process. Besides data analysis and decision making, provenance has been studied in many other fields, sometimes under different names, for different types of sense making. For example, the Human-Computer Interaction community relies on the analysis of logging to understand user behaviors and intentions; the WWW and database community has been working on data lineage to understand uncertainty and trustworthiness; and finally, reproducible science heavily relies on provenance to improve the reliability and efficiency of scientific research. This Dagstuhl Seminar brought together researchers from the diverse fields that relate to provenance and sense making to foster cross-community collaboration. Shared challenges were identified and progress has been made towards developing novel solutions

Prediction and diagnosis of Tropical Cyclone formation in an NWP system. Part I

J. Atmos. Sci., 63 3077-3090The article of record as published may be located at http://dx.doi.org/10.1175/JAS3765.

Communication and Group Perception: Extending the `Saying is Believing' Effect

The saying-is-believing (SIB) effect occurs when tailoring a message to suit an audience influences a communicator's subsequent memories and impressions about the communication topic. Previous studies were restricted to one-person audiences and individuals as the communication topic. The present studies explored the SIB effect with multiple-person audiences and groups as the communication topic. In Study 1, the SIB effect occurred with a 1-person, but not a 3-person, audience. In Study 2, the SIB effect occurred with a 3-person audience when the audience explicitly validated communicators' messages. These findings demonstrate the generalizability of the SIB effect to group contexts, provide further evidence for a shared reality interpretation of this effect, and suggest a potentially important mechanism underlying stereotype development

Prediction and diagnosis of Tropical Cyclone formation in an NWP system. Part II

J. Atmos. Sci., 63 3091-3113The article of record as published may be located at http://dx.doi.org/10.1175/JAS3765.