Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets

Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis

A global transformation is being fueled by unprecedented growth in the quality, quantity, and number of different parameters in environmental data through the convergence of several technological advances in data collection and modeling. Although these data hold great potential for helping us understand many complex and, in some cases, life-threatening environmental processes, our ability to generate such data is far outpacing our ability to analyze it. In particular, conventional environmental data analysis tools are inadequate for coping with the size and complexity of these data. As a result, users are forced to reduce the problem in order to adapt to the capabilities of the tools. To overcome these limitations, we must complement the power of computational methods with human knowledge, flexible thinking, imagination, and our capacity for insight by developing visual analysis tools that distill information into the actionable criteria needed for enhanced decision support. In light of said challenges, we have integrated automated statistical analysis capabilities with a highly interactive, multivariate visualization interface to produce a promising approach for visual environmental data analysis. By combining advanced interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading, we provide an enhanced variant of the classical parallel coordinates plot. Furthermore, the system facilitates statistical processes such as stepwise linear regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. These capabilities are combined into a unique geovisual analytics system that is demonstrated via a pedagogical case study and three North Atlantic tropical cyclone climate studies using a systematic workflow. In addition to revealing several significant associations between environmental observations and tropical cyclone activity, this research corroborates the notion that enhanced parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, real-world data sets

Chatbot-Based Natural Language Interfaces for Data Visualisation: A Scoping Review

Rapid growth in the generation of data from various sources has made data visualisation a valuable tool for analysing data. However, visual analysis can be a challenging task, not only due to intricate dashboards but also when dealing with complex and multidimensional data. In this context, advances in Natural Language Processing technologies have led to the development of Visualisation-oriented Natural Language Interfaces (V-NLIs). In this paper, we carry out a scoping review that analyses synergies between the fields of Data Visualisation and Natural Language Interaction. Specifically, we focus on chatbot-based V-NLI approaches and explore and discuss three research questions. The first two research questions focus on studying how chatbot-based V-NLIs contribute to interactions with the Data and Visual Spaces of the visualisation pipeline, while the third seeks to know how chatbot-based V-NLIs enhance users' interaction with visualisations. Our findings show that the works in the literature put a strong focus on exploring tabular data with basic visualisations, with visual mapping primarily reliant on fixed layouts. Moreover, V-NLIs provide users with restricted guidance strategies, and few of them support high-level and follow-up queries. We identify challenges and possible research opportunities for the V-NLI community such as supporting high-level queries with complex data, integrating V-NLIs with more advanced systems such as Augmented Reality (AR) or Virtual Reality (VR), particularly for advanced visualisations, expanding guidance strategies beyond current limitations, adopting intelligent visual mapping techniques, and incorporating more sophisticated interaction methods

New data analytics and visualization methods in personal data mining, cancer data analysis and sports data visualization

In this dissertation, we discuss a reading profiling system, a biological data visualization system and a sports visualization system. Self-tracking is getting increasingly popular in the field of personal informatics. Reading profiling can be used as a personal data collection method. We present UUAT, an unintrusive user attention tracking system. In UUAT, we used user interaction data to develop technologies that help to pinpoint a users reading region (RR). Based on computed RR and user interaction data, UUAT can identify a readers reading struggle or interest. A biomarker is a measurable substance that may be used as an indicator of a particular disease. We developed CancerVis for visual and interactive analysis of cancer data and demonstrate how to apply this platform in cancer biomarker research. CancerVis provides interactive multiple views from different perspectives of a dataset. The views are synchronized so that users can easily link them to a same data entry. Furthermore, CancerVis supports data mining practice in cancer biomarker, such as visualization of optimal cutpoints and cutthrough exploration. Tennis match summarization helps after-live sports consumers assimilate an interested match. We developed TennisVis, a comprehensive match summarization and visualization platform. TennisVis offers chart- graph for a client to quickly get match facts. Meanwhile, TennisVis offers various queries of tennis points to satisfy diversified client preferences (such as volley shot, many-shot rally) of tennis fans. Furthermore, TennisVis offers video clips for every single tennis point and a recommendation rating is computed for each tennis play. A case study shows that TennisVis identifies more than 75% tennis points in full time match

Model-Driven Development of Aspect-Oriented Software Architectures

The work presented in this thesis of master is an approach that takes advantage of the Model-Driven Development approach for developing aspect-oriented software architectures. A complete MDD support for the PRISMA approach is defined by providing code generation, verification and reusability properties.Pérez Benedí, J. (2007). Model-Driven Development of Aspect-Oriented Software Architectures. http://hdl.handle.net/10251/12451Archivo delegad

Interactive multiview information visualization in tablet-sized touch devices for scientific data

In this thesis we describe an exploratory visualization system for scientific data using multiple views in tablet-sized touch devices. The increasing ubiquity of mobile devices and vast amount of data generation create a need for such exploration environment. We make the data analysis available anywhere at anytime with our approach. This thesis includes an interaction framework for scientific data and a spatial selection technique based on transfer functions. We then combine the interaction and selection with multiple information visualization views to make the data exploration possible. The proposed approach is one of the first multiview exploratory visualizations in tablet devices

A View on Research Panorama of Spiritual Tourism: A Bibliometric Analysis

Spiritual tourism infuses mindfulness and spirituality into the fabric of travel. The main objective of this research is to pinpoint the status quo on the research panorama of spiritual tourism. Furthermore, this study assesses how far spirituality-based research has progressed in tourism. This study employs a bibliometric approach to analyze 174 research papers extracted from the Scopus database from the year 2005 to 2022. The research molded the obtained informational structure in the form of publication years, publication sources, prolific authors and their locations, the main keywords, and most cited research papers. Additionally, co-authorship, inter-country co-authorship, and keywords co-occurrences network maps in the field of research on spiritual tourism were created with the aid of VOSviewer software. It has been found that spiritual tourism is an attracting and growing topic for researchers working in the tourism sector. The most cited paper is “Spiritual journey to Hajj: Australian and Pakistani experience and expectations” (Haq & Jackson, 2009) with 66 citations. The most productive author is Farooq Haq from Canadian University Dubai. Canadian University, Dubai, and Central Queensland University, Australia, generated the most papers. The “International Journal of Religious Tourism and Pilgrimage” (n=20) published the most spiritual tourism-themed research papers

MODEL DRIVEN SOFTWARE PRODUCT LINE ENGINEERING: SYSTEM VARIABILITY VIEW AND PROCESS IMPLICATIONS

La Ingeniería de Líneas de Productos Software -Software Product Line Engineerings (SPLEs) en inglés- es una técnica de desarrollo de software que busca aplicar los principios de la fabricación industrial para la obtención de aplicaciones informáticas: esto es, una Línea de productos Software -Software Product Line (SPL)- se emplea para producir una familia de productos con características comunes, cuyos miembros, sin embargo, pueden tener características diferenciales. Identificar a priori estas características comunes y diferenciales permite maximizar la reutilización, reduciendo el tiempo y el coste del desarrollo. Describir estas relaciones con la suficiente expresividad se vuelve un aspecto fundamental para conseguir el éxito. La Ingeniería Dirigida por Modelos -Model Driven Engineering (MDE) en inglés- se ha revelado en los últimos años como un paradigma que permite tratar con artefactos software con un alto nivel de abstracción de forma efectiva. Gracias a ello, las SPLs puede aprovecharse en granmedida de los estándares y herramientas que han surgido dentro de la comunidad de MDE. No obstante, aún no se ha conseguido una buena integración entre SPLE y MDE, y como consecuencia, los mecanismos para la gestión de la variabilidad no son suficientemente expresivos. De esta manera, no es posible integrar la variabilidad de forma eficiente en procesos complejos de desarrollo de software donde las diferentes vistas de un sistema, las transformaciones de modelos y la generación de código juegan un papel fundamental. Esta tesis presenta MULTIPLE, un marco de trabajo y una herramienta que persiguen integrar de forma precisa y eficiente los mecanismos de gestión de variabilidad propios de las SPLs dentro de los procesos de MDE. MULTIPLE proporciona lenguajes específicos de dominio para especificar diferentes vistas de los sistemas software. Entre ellas se hace especial hincapié en la vista de variabilidad ya que es determinante para la especificación de SPLs.Gómez Llana, A. (2012). MODEL DRIVEN SOFTWARE PRODUCT LINE ENGINEERING: SYSTEM VARIABILITY VIEW AND PROCESS IMPLICATIONS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/15075Palanci

eHealth in Chronic Diseases

This book provides a review of the management of chronic diseases (evaluation and treatment) through eHealth. Studies that examine how eHealth can help to prevent, evaluate, or treat chronic diseases and their outcomes are included