Interactions in Visualization

The overall goal of this thesis is to define the interactions and a classification of interactions in visualization valid in different application domains. The defined interactions will be applied to the states and transformations of the visualization process. In this context, it is necessary to define a representation for the data sets involved in the process. This representation must be sufficiently flexible to support the different classifications of data, attributes, data sets and visual mappings present in the visualization literature.Resúmen de la Tesis de Doctorado presentada por la autora el 16 de marzo de 2018 en la UNS para la obtención del título de Doctor en Ciencias de la ComputaciónEs revisión de: https://digital.cic.gba.gob.ar/handle/11746/7863Facultad de Informátic

Interactions in Visualization

The overall goal of this thesis is to define the interactions and a classification of interactions in visualization valid in different application domains. The defined interactions will be applied to the states and transformations of the visualization process. In this context, it is necessary to define a representation for the data sets involved in the process. This representation must be sufficiently flexible to support the different classifications of data, attributes, data sets and visual mappings present in the visualization literature.Resúmen de la Tesis de Doctorado presentada por la autora el 16 de marzo de 2018 en la UNS para la obtención del título de Doctor en Ciencias de la ComputaciónEs revisión de: https://digital.cic.gba.gob.ar/handle/11746/7863Facultad de Informátic

Data visualization: foundations, techniques, and applications

The idea that there is no precedence for the amount of data that is being generated today, and that the need to explore and analyze this vast volumes of data has become an increasingly difficult task that could benefit from using Data visualization is presented. It is pointed that the goals of data visualization are data-driven and depend largely on the type of application, but the final objective is to convey to people information that is hidden in large volumes of data. Finally, the visualization pipeline is presented to review aspects of visualization methodology and visualization tool design, to conclude that the true potential of visualization emerge from the interaction of the user with the visualization model. The paper concludes establishing that the current processes of digital transformation will increase the need for visual analytics tools

The influences of user generated ‘Big data’ on urban development

Cities are the nucleus for creativity and ideas, as it has all the potentials for people to work, explore and live. People always come to cities because they want to be part of something, this magnet in the cities created the problem of population (Ericsson: Thinking Cities in the Networked Society, 2012). Approximately 50% of world’s population lives in urban areas, a number which is expected to increase to nearly 60% by 2030. (Mutizwa-Mangiza ND, Arimah B C, Jensen I, Yemeru EA, Kinyanjui MK, 2011). According to the rapid change in cities’ population there exists a need to utilize intelligent prediction tools to deliver a better way of living. Smart cities provide an opportunity to connect people and places using innovative technologies that help in better city planning and management ( Khan, Anjum, Soomro, & Tahir, 2015). Data is never a new thing, but data sources are always in change. The internet made everything easier and more reachable. This wide range of technologies such as IOT (internet of things) and M2M (machine to machine) (Gartner, 2015), is believed to offer a new potential to deliver an analytical framework for urban optimization. The real value of such data is gained by new knowledge acquired by performing data analytics using various data mining, machine learning or statistical methods. According to this technologically mutated, data comes from weather channels, street security cameras, Facebook, Twitter, sensor networks, in-car devices, location-based smartphone apps, RFID tags, smart meters, among other sources (Hinssen, 2012). This massive amount of information that comes from real-time based tools, made the world in front of a new era of data called ‘Big Data’. However, turning an ocean of messy data into knowledge and wisdom is an extremely challenging task. The proposed paper will discuss the IOT developed frameworks which are used to improve cities infrastructure and their vital systems. Analyzing these frameworks will help developing a conceptual proposal of data visualizing software; with the aim of helping urban planners get a better and easier way to comprehend the usage of multi-data sources for city planning and management. The full control of data is an open challenge, however proposing the fundamental bases of framework with the ability to extend and having an application layer above would be very helpful for urban process shifting. The Egyptian case is our main scope to have a smarter city that provides an opportunity to connect people and places using innovative technologies

Using Icicle Trees to Encode the Hierarchical Structure of Source Code

This paper presents a study which evaluates the use of a tree visualisation (icicle tree) to encode the hierarchical structure of source code. The tree visualisation was combined with a source code editor in order to function as a compact overview to facilitate the process of comprehending the global structure of a source code document. Results from our study show that pro- viding an overview visualisation led to an increase in accuracy and a decrease in completion time when participants performed counting tasks. However, in locating tasks, the presence of the visualisation led to a decrease in participants’ performance

Scoped: Evaluating A Composite Visualisation Of The Scope Chain Hierarchy Within Source Code

This paper presents two studies that evaluate the effectiveness of a software visualisation tool which uses a com- posite visualisation to encode the scope chain and information related to the scope chain within source code. The first study evaluates the effectiveness of adding the composite visualisation to a source code editor to help programmers understand scope relationships within source code. The second study evaluates the effectiveness of each individual component within the composite visualisation. The composite visualisation is composed of a packed circle tree diagram (overview component) and a list view (detail view component). The packed circle tree functions as an abstract mini-map to provide viewers with a high-level overview of the scope chain hierarchy within a source code document. The list view provides additional information about identifiers (variables, functions, and parameters) that are accessible from the scope within which the cursor is located, in the source code document. Both studies utilise a between-subject design, in which groups of participants were presented with source code fragments and asked to answer a series of code understanding questions. The results of the studies indicate that adding a composite visualisation to a source code editor can have a positive effect on code understanding, especially when the textual representation of the code no longer corresponds to the actual behaviour of the code (as is the case, for example, in languages such as JavaScript that implement variable hoisting)