Exploring the integration of data mining and data visualization

Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being generated everyday in various applications. The integration of data mining and data visualization has been widely used to analyze these massive and complex data sets to discover hidden patterns. For both data mining and visualization to be effective, it is important to include the visualization techniques in the mining process and to generate the discovered patterns for a more comprehensive visual view. In this dissertation, four related problems: dimensionality reduction for visualizing high dimensional datasets, visualization-based clustering evaluation, interactive document mining, and multiple clusterings exploration are studied to explore the integration of data mining and data visualization. In particular, we 1) propose an efficient feature selection method (reliefF + mRMR) for preprocessing high dimensional datasets; 2) present DClusterE to integrate cluster validation with user interaction and provide rich visualization tools for users to examine document clustering results from multiple perspectives; 3) design two interactive document summarization systems to involve users efforts and generate customized summaries from 2D sentence layouts; and 4) propose a new framework which organizes the different input clusterings into a hierarchical tree structure and allows for interactive exploration of multiple clustering solutions.

A large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling

With the exponential increasing demands and uses of GIS data visualization system, such as urban planning, environment and climate change monitoring, weather simulation, hydrographic gauge and so forth, the geospatial vector and raster data visualization research, application and technology has become prevalent. However, we observe that current web GIS techniques are merely suitable for static vector and raster data where no dynamic overlaying layers. While it is desirable to enable visual explorations of large-scale dynamic vector and raster geospatial data in a web environment, improving the performance between backend datasets and the vector and raster applications remains a challenging technical issue. This dissertation is to implement these challenging and unimplemented areas: how to provide a large-scale dynamic vector and raster data visualization service with dynamic overlaying layers accessible from various client devices through a standard web browser, and how to make the large-scale dynamic vector and raster data visualization service as rapid as the static one. To accomplish these, a large-scale dynamic vector and raster data visualization geographic information system based on parallel map tiling and a comprehensive performance improvement solution are proposed, designed and implemented. They include: the quadtree-based indexing and parallel map tiling, the Legend String, the vector data visualization with dynamic layers overlaying, the vector data time series visualization, the algorithm of vector data rendering, the algorithm of raster data re-projection, the algorithm for elimination of superfluous level of detail, the algorithm for vector data gridding and re-grouping and the cluster servers side vector and raster data caching.

Untangle sustainable development goal 8 through data visualization and HCI methods

Following the approval of the 2030 Agenda for Sustainable Development in 2015, sustainability became a hotly debated topic. In order to build a better and more sustainable future by 2030, this agenda addressed several global issues, including inequality, climate change, peace, and justice, in the form of 17 Sustainable Development Goals (SDGs), that should be understood and pursued by nations, corporations, institutions, and individuals. In this thesis, we researched how to exploit and integrate Human-Computer Interaction (HCI) and Data Visualization to promote knowledge and awareness about SDG 8, which wants to encourage lasting, inclusive, and sustainable economic growth, full and productive employment, and decent work for all. In particular, we focused on three targets: green economy, sustainable tourism, employment, decent work for all, and social protection. The primary goal of this research is to determine whether HCI approaches may be used to create and validate interactive data visualization that can serve as helpful decision-making aids for specific groups and raise their knowledge of public-interest issues. To accomplish this goal, we analyzed four case studies. In the first two, we wanted to promote knowledge and awareness about green economy issues: we investigated the Human-Building Interaction inside a Smart Campus and the dematerialization process inside a University. In the third, we focused on smart tourism, investigating the relationship between locals and tourists to create meaningful connections and promote more sustainable tourism. In the fourth, we explored the industry context to highlight sustainability policies inside well-known companies. This research focuses on the hypothesis that interactive data visualization tools can make communities aware of sustainability aspects related to SDG8 and its targets. The research questions addressed are two: "how to promote awareness about SDG8 and its targets through interactive data visualizations?" and "to what extent are these interactive data visualizations effective?".

PIATTAFORMA DI DATA VISUALIZATION GUIDATA DALLA MODELLAZIONE STATISTICA DEI DATI Applicazione a dati sanitari di pazienti oncologici della regione Emila-Romagna

Una gestione, un’analisi e un’interpretazione efficienti dei big data possono cambiare il modello lavorativo, modificare i risultati, aumentare le produzioni, e possono aprire nuove strade per l’assistenza sanitaria moderna. L'obiettivo di questo studio è incentrato sulla costruzione di una dashboard interattiva di un nuovo modello e nuove prestazioni nell’ambito della Sanità territoriale. Lo scopo è quello di fornire al cliente una piattaforma di Data Visualization che mostra risultati utili relativi ai dati sanitari in modo da fornire agli utilizzatori sia informazioni descrittive che statistiche sulla attuale gestione delle cure e delle terapie somministrate. Si propone uno strumento che consente la navigazione dei dati analizzando l’andamento di un set di indicatori di fine vita calcolati a partire da pazienti oncologici della Regione Emilia Romagna in un arco temporale che va dal 2010 ad oggi.

Data Visualization e Sonification per aumentare la consapevolezza sull'inquinamento attraverso un'applicazione web interattiva

Nonostante la consapevolezza sulle condizioni non ottimali della qualità dell'aria sia sempre più diffusa, a molte persone risulta ancora insidioso comprendere il significato dei dati sull'argomento tramite la sola rappresentazione grafica. L'obbiettivo di questo progetto è quello di presentare, tramite un'applicazione web interattiva, le informazioni sull'inquinamento atmosferico in maniera più semplice e coinvolgente. La strategia scelta è la Sonificazione: un processo che trasforma un dato di qualsiasi natura in un suono che ne rispecchia le caratteristiche. Su questa base, vengono approfondite le problematiche dell'inquinamento, le metodologie di rappresentazione e le debolezze di queste ultime. Dopo essere entrato in dettaglio sul funzionamento della Sonificazione e sulle sue applicazioni, il volume segue lo sviluppo del sistema in tutte le sue fasi: l'analisi dei requisiti, la scelta delle tecnologie, l'implementazione e i test. L'elaborato presta particolare attenzione a spiegare in dettaglio la realizzazione della traccia audio di Sonificazione, l'elemento più importante di tutto l'applicativo.

Aumentare la consapevolezza sul benessere digitale: Data Visualization e Sonification in un’applicazione mobile

La tecnologia gioca un ruolo importante nella vita della maggior parte delle persone, ma come possiamo assicurarci che migliori effettivamente la vita piuttosto che distrarci da essa? Con gli smartphone di oggi, i social media e i flussi infiniti di contenuti, molte persone sono pronte a condannare la tecnologia sulla base della loro convinzione che questi prodotti siano dannosi per la salute mentale e il benessere. Ma concentrarsi solo su questi effetti potenzialmente dannosi non ci aiuta a raccogliere tutti i vantaggi che questi strumenti hanno da offrire, gestendo anche i loro rischi. Da qui nasce il digital wellbeing: un termine utilizzato per descrivere l’impatto delle tecnologie e dei servizi digitali sulla salute mentale, fisica, sociale ed emotiva delle persone. Lo scopo di questa tesi è quello di aumentare la consapevolezza sul reale utilizzo dei dispositivi e sulle proprie abitudini salutari attraverso la sonificazione, un processo di traduzione dei dati in suono, a volte in un contesto musicale utilizzato come metodo per superare le barriere della comunicazione scientifica. Questo metodo è particolarmente vantaggioso per la sua capacità di rappresentare i dati scientifici per le persone con disabilità visive, che spesso non sono in grado di interagire con le tradizionali visualizzazioni dei dati. Per raggiungere l'obiettivo della tesi viene preso in esame una solo tipologia di dispositivi, gli iPhone, per la quale verrà creata un'applicazione che riesca ad ottenere i dati sulla salute, sulla forma fisica e di utilizzo dello smartphone.

Integration and visualization of systems biology data in context of the genome

Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.

Distributed Visualization Systems in Remote Sensing Data Processing Grid

Implementation of GEOSS/GMES initiative requires creation and integration of service providers, most of which provide geospatial data output from Grid system to interactive user. In this paper approaches of DOS- centers (service providers) integration used in Ukrainian segment of GEOSS/GMES will be considered and template solutions for geospatial data visualization subsystems will be suggested. Developed patterns are implemented in DOS center of Space Research Institute of National Academy of Science of Ukraine and National Space Agency of Ukraine (NASU-NSAU).

Scalable Visualization of Galaxies, Oceans, and Brains

One of the challenges in scientific visualization is to generate software libraries suitable for the large-scale data emerging from tera-scale simulations and instruments. We describe the efforts currently under way at SDSC and NPACI to address these challenges. The scope of the SDSC project spans data handling, graphics, visualization, and scientific application domains. Components of the research focus on the following areas: intelligent data storage, layout and handling, using an associated “Floor-Plan” (meta data); performance optimization on parallel architectures; extension of SDSC’s scalable, parallel, direct volume renderer to allow perspective viewing; and interactive rendering of fractional images (“imagelets”), which facilitates the examination of large datasets. These concepts are coordinated within a data-visualization pipeline, which operates on component data blocks sized to fit within the available computing resources. A key feature of the scheme is that the meta data, which tag the data blocks, can be propagated and applied consistently. This is possible at the disk level, in distributing the computations across parallel processors; in “imagelet” composition; and in feature tagging. The work reflects the emerging challenges and opportunities presented by the ongoing progress in high-performance computing (HPC) and the deployment of the data, computational, and visualization Grids.

Exploratory geospatial data analysis using self-organizing maps

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

Integer and Fractional Order Entropy Analysis of Earthquake Data-series

This paper studies the statistical distributions of worldwide earthquakes from year 1963 up to year 2012. A Cartesian grid, dividing Earth into geographic regions, is considered. Entropy and the Jensen–Shannon divergence are used to analyze and compare real-world data. Hierarchical clustering and multi-dimensional scaling techniques are adopted for data visualization. Entropy-based indices have the advantage of leading to a single parameter expressing the relationships between the seismic data. Classical and generalized (fractional) entropy and Jensen–Shannon divergence are tested. The generalized measures lead to a clear identification of patterns embedded in the data and contribute to better understand earthquake distributions.

Data fusion with computational intelligence techniques: a case study of fuzzy inference for terrain assessment

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Gene expression databases and data mining.

The DNA microarray technology has arguably caught the attention of the worldwide life science community and is now systematically supporting major discoveries in many fields of study. The majority of the initial technical challenges of conducting experiments are being resolved, only to be replaced with new informatics hurdles, including statistical analysis, data visualization, interpretation, and storage. Two systems of databases, one containing expression data and one containing annotation data are quickly becoming essential knowledge repositories of the research community. This present paper surveys several databases, which are considered "pillars" of research and important nodes in the network. This paper focuses on a generalized workflow scheme typical for microarray experiments using two examples related to cancer research. The workflow is used to reference appropriate databases and tools for each step in the process of array experimentation. Additionally, benefits and drawbacks of current array databases are addressed, and suggestions are made for their improvement.

Manual de uso del software Ocean Data View (ODV)

El presente manual de uso del software de visualización de datos “Ocean Data View” (ODV) describe la exploración, análisis y visualización de datos oceanográficos según el formato de la colección mundial de base de datos del océano “World Ocean Database” (WOD). El manual comprende 6 ejercicios prácticos donde se describe paso a paso la creación de las metavariables, la importación de los datos y su visualización mediante mapas de latitud, longitud y gráficos de dispersión, secciones verticales y series de tiempo. Se sugiere el uso extensivo del ODV para la visualización de datos oceanográficos por el personal científico del IMARPE.

A sample visualization of contributions to http://eprints.soton.ac.uk

This is a sample visualization of contributions to eprints.soton.ac.uk. The visualization was created from data from the OAI endpoint using gource. The data is divided by dc:subject classification. The idea was taken from Martin Hawksey's blog post http://mashe.hawksey.info/2011/12/google-refining-jorum-ukoer/