SciTech News Volume 71, No. 2 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division 9 Aerospace Section of the Engineering Division 12 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 14 Reviews Sci-Tech Book News Reviews 16 Advertisements IEEE

Storytelling Maps Classification

Interactive maps play an increasingly important part in various fields including journalism, education, traveling, and entertainment, among others. Interactive maps require interactive user engagement. The scope of this interaction can vary from the basic mouse scroll to the complex logical sequence of steps including extensive toolboxes. One of the major applications of interactive maps is in storytelling. A map serves as a powerful tool to tell a story and modern technologies make this tool flexible and potent. This research seeks to analyze and compare cartographic JavaScript APIs and libraries, and to classify storytelling maps with a concentration on ‘path visualization’ type of maps and their technical implementation with an extensive review regarding the function of maps-related API/libraries work under the hood and their improvement. Additional material to this work, a web platform, demonstrates an example of each class and subclass of the classification. The proposed classification has been evaluated by reviewers working with interactive storytelling maps. The web platform provides examples discussed in this work. The main chapter always references this platform, therefore readers have to adopt the web platform as an essential part of this work during reading: https://konstantinbiryukov.github.io/storytelling-classification/

Computing Fast and Scalable Table Cartograms for Large Tables

Given an m x n table T of positive weights and a rectangle R with an area equal to the sum of the weights, a table cartogram computes a partition of R into m x n convex quadrilateral faces such that each face has the same adjacencies as its corresponding cell in T, and has an area equal to the cell's weight. In this thesis, we explored different table cartogram algorithms for a large table with thousands of cells and investigated the potential applications of large table cartograms. We implemented Evans et al.'s table cartogram algorithm that guarantees zero area error and adapted a diffusion-based cartographic transformation approach, FastFlow, to produce large table cartograms. We introduced a constraint optimization-based table cartogram generation technique, TCarto, leveraging the concept of force-directed layout. We implemented TCarto with column-based and quadtree-based parallelization to compute table cartograms for table with thousands of cells. We presented several potential applications of large table cartograms to create the diagrammatic representations in various real-life scenarios, e.g., for analyzing spatial correlations between geospatial variables, understanding clusters and densities in scatterplots, and creating visual effects in images (i.e., expanding illumination, mosaic art effect). We presented an empirical comparison among these three table cartogram techniques with two different real-life datasets: a meteorological weather dataset and a US State-to-State migration flow dataset. FastFlow and TCarto both performed well on the weather data table. However, for US State-to-State migration flow data, where the table contained many local optima with high value differences among adjacent cells, FastFlow generated concave quadrilateral faces. We also investigated some potential relationships among different measurement metrics such as cartographic error (accuracy), the average aspect ratio (the readability of the visualization), computational speed, and the grid size of the table. Furthermore, we augmented our proposed TCarto with angle constraint to enhance the readability of the visualization, conceding some cartographic error, and also inspected the potential relationship of the restricted angles with the accuracy and the readability of the visualization. In the output of the angle constrained TCarto algorithm on US State-to-State migration dataset, it was difficult to identify the rows and columns for a cell upto 20 degree angle constraint, but appeared to be identifiable for more than 40 degree angle constraint

Internet of things

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth

Data and Society:A Critical Introduction

This is the author accepted manuscript. the final version is available from SAGE Publishing via the link in this recordData and Society: A Critical Introduction investigates the growing importance of data as a technological, social, economic and scientific resource. It explains how data practices have come to underpin all aspects of human life and explores what this means for those directly involved in handling data. The book fosters informed debate over the role of data in contemporary society explains the significance of data as evidence beyond the "Big Data" hype spans the technical, sociological, philosophical and ethical dimensions of data provides guidance on how to use data responsibly includes data stories that provide concrete cases and discussion questions. Grounded in examples spanning genetics, sport and digital innovation, this book fosters insight into the deep interrelations between technical, social and ethical aspects of data work.European CommissionAlan Turing Institut

Strategic Approach for Electric Vehicle Charging Infrastructure for Efficient Mobility along Highways: A Real Case Study in Spain

The Electric Vehicle (EV) market has been growing exponentially in recent years, which is why the distribution network of public charging stations will be subject to expansion and upgrading. In order to improve the public charging infrastructure, this paper aims to develop a model capable of analyzing the current situation of a stretch of highway, identifying the congestion points, created by the formation of queues at the charging points. A specific section of a highway in Spain was selected as a case study to evaluate the performance of the model, allowing for rigorous testing and thorough analysis of its performance in a real-world scenario. The first step is to define and evaluate the effects of factors affecting EV consumption, such as the slope of the road, weather conditions, and driving style. Subsequently, a simulation model is developed using the agent-based simulation software AnyLogic, which simulates the journey of a fleet of electric vehicles, taking into account the battery charging and discharging process. Based on the obtained results, the charging infrastructure is improved to minimize the total travel time of an electric vehicle on a long-distance trip

GISualisation: a tool for visually supporting planning processes

The evaluation of quality of life in cities can be supported by the analysis of data coming from different sources and describing different aspects such as economic, social, environmental, energy, housing or mobility issues. Nevertheless, the analysis of such big amounts of data is difficult so that only expert technicians can access to their inner contents. Furthermore, the outcomes of these analyses are often presented in static outcomes which reproduce the reasoning of technicians who have not expertise in urban studies. Thus, planners and decision-makers have to base their own choices on given outcomes without opportunities for personally investigating the inner contents of data. In order to facilitate the data exploration and readability by non-technicians, a GIS-based visualization tool, namely “GISualisation”, has been realized to give to both planners and actors involved in planning processes, a decision support system useful to visualize the inter-relations between data which describe cities. The tool is a web-based interactive visual tool, which works on geo-referenced dynamic maps, currently created with free Web GIS applications. GISualisation displays data on a map and offers the possibility to select and filter data by single attributes, allowing users to interact readily with large databases and customise the visualisation of information. Thus, the tool offers a simple interface to visualise GIS data on the basis of users’ requests, providing a support for planners and decision-makers to explore data and detect issues of inefficiency, ineffectiveness or critical areas which needs further reasoning on their planning or design. Furthermore, it can be used in collaborative and participatory session so to improve the information sharing among participants. Depending on the case study, the tool can be adapted and customized to visualise different type of data, ensuring user-friendliness and possibility to explore the relationships between data. GISualisation has already been applied in investigating inefficiencies in a public transport system (Pensa, Masala, Arnone, & Rosa, 2013), in studying pedestrian paths in an urban area, in analysing urban population health and in the evaluation of social housing projects. Further developments will include the integration with the interactive Visualisation Tool (InViTo) (Pensa, Masala, & Lami, 2013; Pensa & Masala, 2014) and the possibility to include real-time data feeds. Through GISualisation, data on quality of life can be investigated and visually analysed so to offer a new tool to actors involved in planning process for detecting critical areas and improving the urban planning process