773 research outputs found

    IS-EUD 2017 6th international symposium on end-user development:extended abstracts

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    From Molecules to the Masses : Visual Exploration, Analysis, and Communication of Human Physiology

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    Det overordnede målet med denne avhandlingen er tverrfaglig anvendelse av medisinske illustrasjons- og visualiseringsteknikker for å utforske, analysere og formidle aspekter ved fysiologi til publikum med ulik faglig nivå og bakgrunn. Fysiologi beskriver de biologiske prosessene som skjer i levende vesener over tid. Vitenskapen om fysiologi er kompleks, men samtidig kritisk for vår forståelse av hvordan levende organismer fungerer. Fysiologi dekker en stor bredde romlig-temporale skalaer og fordrer behovet for å kombinere og bygge bro mellom basalfagene (biologi, fysikk og kjemi) og medisin. De senere årene har det vært en eksplosjon av nye, avanserte eksperimentelle metoder for å detektere og karakterisere fysiologiske data. Volumet og kompleksiteten til fysiologiske data krever effektive strategier for visualisering for å komplementere dagens standard analyser. Hvilke tilnærminger som benyttes i visualiseringen må nøye balanseres og tilpasses formålet med bruken av dataene, enten dette er for å utforske dataene, analysere disse eller kommunisere og presentere dem. Arbeidet i denne avhandlingen bidrar med ny kunnskap innen teori, empiri, anvendelse og reproduserbarhet av visualiseringsmetoder innen fysiologi. Først i avhandlingen er en rapport som oppsummerer og utforsker dagens kunnskap om muligheter og utfordringer for visualisering innen fysiologi. Motivasjonen for arbeidet er behovet forskere innen visualiseringsfeltet, og forskere i ulike anvendelsesområder, har for en sammensatt oversikt over flerskala visualiseringsoppgaver og teknikker. Ved å bruke søk over et stort spekter av metodiske tilnærminger, er dette den første rapporten i sitt slag som kartlegger visualiseringsmulighetene innen fysiologi. I rapporten er faglitteraturen oppsummert slik at det skal være enkelt å gjøre oppslag innen ulike tema i rom-og-tid-skalaen, samtidig som litteraturen er delt inn i de tre høynivå visualiseringsoppgavene data utforsking, analyse og kommunikasjon. Dette danner et enkelt grunnlag for å navigere i litteraturen i feltet og slik danner rapporten et godt grunnlag for diskusjon og forskningsmuligheter innen feltet visualisering og fysiologi. Basert på arbeidet med rapporten var det særlig to områder som det er ønskelig for oss å fortsette å utforske: (1) utforskende analyse av mangefasetterte fysiologidata for ekspertbrukere, og (2) kommunikasjon av data til både eksperter og ikke-eksperter. Arbeidet vårt av mangefasetterte fysiologidata er oppsummert i to studier i avhandlingen. Hver studie omhandler prosesser som foregår på forskjellige romlig-temporale skalaer og inneholder konkrete eksempler på anvendelse av metodene vurdert av eksperter i feltet. I den første av de to studiene undersøkes konsentrasjonen av molekylære substanser (metabolitter) ut fra data innsamlet med magnetisk resonansspektroskopi (MRS), en avansert biokjemisk teknikk som brukes til å identifisere metabolske forbindelser i levende vev. Selv om MRS kan ha svært høy sensitivitet og spesifisitet i medisinske anvendelser, er analyseresultatene fra denne modaliteten abstrakte og vanskelige å forstå også for medisinskfaglige eksperter i feltet. Vår designstudie som undersøkte oppgavene og kravene til ekspertutforskende analyse av disse dataene førte til utviklingen av SpectraMosaic. Dette er en ny applikasjon som gjør det mulig for domeneeksperter å analysere konsentrasjonen av metabolitter normalisert for en hel kohort, eller etter prøveregion, individ, opptaksdato, eller status på hjernens aktivitetsnivå ved undersøkelsestidspunktet. I den andre studien foreslås en metode for å utføre utforskende analyser av flerdimensjonale fysiologiske data i motsatt ende av den romlig-temporale skalaen, nemlig på populasjonsnivå. En effektiv arbeidsflyt for utforskende dataanalyse må kritisk identifisere interessante mønstre og relasjoner, noe som blir stadig vanskeligere når dimensjonaliteten til dataene øker. Selv om dette delvis kan løses med eksisterende reduksjonsteknikker er det alltid en fare for at subtile mønstre kan gå tapt i reduksjonsprosessen. Isteden presenterer vi i studien DimLift, en iterativ dimensjonsreduksjonsteknikk som muliggjør brukeridentifikasjon av interessante mønstre og relasjoner som kan ligge subtilt i et datasett gjennom dimensjonale bunter. Nøkkelen til denne metoden er brukerens evne til å styre dimensjonalitetsreduksjonen slik at den følger brukerens egne undersøkelseslinjer. For videre å undersøke kommunikasjon til eksperter og ikke-eksperter, studeres i neste arbeid utformingen av visualiseringer for kommunikasjon til publikum med ulike nivåer av ekspertnivå. Det er naturlig å forvente at eksperter innen et emne kan ha ulike preferanser og kriterier for å vurdere en visuell kommunikasjon i forhold til et ikke-ekspertpublikum. Dette påvirker hvor effektivt et bilde kan benyttes til å formidle en gitt scenario. Med utgangspunkt i ulike teknikker innen biomedisinsk illustrasjon og visualisering, gjennomførte vi derfor en utforskende studie av kriteriene som publikum bruker når de evaluerer en biomedisinsk prosessvisualisering målrettet for kommunikasjon. Fra denne studien identifiserte vi muligheter for ytterligere konvergens av biomedisinsk illustrasjon og visualiseringsteknikker for mer målrettet visuell kommunikasjonsdesign. Særlig beskrives i større dybde utviklingen av semantisk konsistente retningslinjer for farging av molekylære scener. Hensikten med slike retningslinjer er å heve den vitenskapelige kompetansen til ikke-ekspertpublikum innen molekyler visualisering, som vil være spesielt relevant for kommunikasjon til befolkningen i forbindelse med folkehelseopplysning. All kode og empiriske funn utviklet i arbeidet med denne avhandlingen er åpen kildekode og tilgjengelig for gjenbruk av det vitenskapelige miljøet og offentligheten. Metodene og funnene presentert i denne avhandlingen danner et grunnlag for tverrfaglig biomedisinsk illustrasjon og visualiseringsforskning, og åpner flere muligheter for fortsatt arbeid med visualisering av fysiologiske prosesser.The overarching theme of this thesis is the cross-disciplinary application of medical illustration and visualization techniques to address challenges in exploring, analyzing, and communicating aspects of physiology to audiences with differing expertise. Describing the myriad biological processes occurring in living beings over time, the science of physiology is complex and critical to our understanding of how life works. It spans many spatio-temporal scales to combine and bridge the basic sciences (biology, physics, and chemistry) to medicine. Recent years have seen an explosion of new and finer-grained experimental and acquisition methods to characterize these data. The volume and complexity of these data necessitate effective visualizations to complement standard analysis practice. Visualization approaches must carefully consider and be adaptable to the user's main task, be it exploratory, analytical, or communication-oriented. This thesis contributes to the areas of theory, empirical findings, methods, applications, and research replicability in visualizing physiology. Our contributions open with a state-of-the-art report exploring the challenges and opportunities in visualization for physiology. This report is motivated by the need for visualization researchers, as well as researchers in various application domains, to have a centralized, multiscale overview of visualization tasks and techniques. Using a mixed-methods search approach, this is the first report of its kind to broadly survey the space of visualization for physiology. Our approach to organizing the literature in this report enables the lookup of topics of interest according to spatio-temporal scale. It further subdivides works according to any combination of three high-level visualization tasks: exploration, analysis, and communication. This provides an easily-navigable foundation for discussion and future research opportunities for audience- and task-appropriate visualization for physiology. From this report, we identify two key areas for continued research that begin narrowly and subsequently broaden in scope: (1) exploratory analysis of multifaceted physiology data for expert users, and (2) communication for experts and non-experts alike. Our investigation of multifaceted physiology data takes place over two studies. Each targets processes occurring at different spatio-temporal scales and includes a case study with experts to assess the applicability of our proposed method. At the molecular scale, we examine data from magnetic resonance spectroscopy (MRS), an advanced biochemical technique used to identify small molecules (metabolites) in living tissue that are indicative of metabolic pathway activity. Although highly sensitive and specific, the output of this modality is abstract and difficult to interpret. Our design study investigating the tasks and requirements for expert exploratory analysis of these data led to SpectraMosaic, a novel application enabling domain researchers to analyze any permutation of metabolites in ratio form for an entire cohort, or by sample region, individual, acquisition date, or brain activity status at the time of acquisition. A second approach considers the exploratory analysis of multidimensional physiological data at the opposite end of the spatio-temporal scale: population. An effective exploratory data analysis workflow critically must identify interesting patterns and relationships, which becomes increasingly difficult as data dimensionality increases. Although this can be partially addressed with existing dimensionality reduction techniques, the nature of these techniques means that subtle patterns may be lost in the process. In this approach, we describe DimLift, an iterative dimensionality reduction technique enabling user identification of interesting patterns and relationships that may lie subtly within a dataset through dimensional bundles. Key to this method is the user's ability to steer the dimensionality reduction technique to follow their own lines of inquiry. Our third question considers the crafting of visualizations for communication to audiences with different levels of expertise. It is natural to expect that experts in a topic may have different preferences and criteria to evaluate a visual communication relative to a non-expert audience. This impacts the success of an image in communicating a given scenario. Drawing from diverse techniques in biomedical illustration and visualization, we conducted an exploratory study of the criteria that audiences use when evaluating a biomedical process visualization targeted for communication. From this study, we identify opportunities for further convergence of biomedical illustration and visualization techniques for more targeted visual communication design. One opportunity that we discuss in greater depth is the development of semantically-consistent guidelines for the coloring of molecular scenes. The intent of such guidelines is to elevate the scientific literacy of non-expert audiences in the context of molecular visualization, which is particularly relevant to public health communication. All application code and empirical findings are open-sourced and available for reuse by the scientific community and public. The methods and findings presented in this thesis contribute to a foundation of cross-disciplinary biomedical illustration and visualization research, opening several opportunities for continued work in visualization for physiology.Doktorgradsavhandlin

    IS-EUD 2017 6th international symposium on end-user development:extended abstracts

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    VisuaLeague II - Animated maps for performance analysis in games

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    Tese de mestrado, Informática, Universidade de Lisboa, Faculdade de Ciências, 2018O fenómeno de eSports tem vindo a aumentar ao longo dos anos e, com este, também o interesse por videosjogos online, tanto por parte dos jogadores como treinadores e analistas. Um dos mais populares géneros destes jogos é o Multiplayer Online Battle Arena (MOBA) e durante uma partida existem vários tipos de eventos. Estes eventos, ou ações, podem variar desde a posição de um jogador num determinado instante de tempo ou o caminho que este percorreu de um ponto a outro, a eventos mais específicos do jogo, tais como a posição onde o jogador morreu ou o número de balas disparadas numa determinada área. Analisar este tipo de dados por jogadores, treinadores e analistas pode gerar o reconhecimento de padrões permitindo definir novas estratégias que ajudem os jogadores a melhorar o seu desempenho. Com a evolução da tecnologia, tem-se tornado cada vez mais fácil utilizar técnicas de telemetria para registar eventos em jogos online o que, por sua vez, leva a um elevado volume de dados que pode ser recolhido ao longo do tempo. Para que se possa extrair informação relevante desses conjuntos de dados, por vezes volumosos, é fundamental explorar quais as técnicas de visualização mais adequadas. O objetivo deste trabalho consiste em utilizar o conjunto de dados telemétricos recolhidos pela Riot Games, provenientes de partidas de League of Legends (LoL), para redesenhar um protótipo onde se explora a técnica de visualização mapas animados, melhorando o desempenho computacional deste, resolvendo problemas como a sobreposição de eventos e a limitação de só suportar a análise até dois jogadores em simultâneo. Foram aplicadas técnicas de visualização complementares para a mitigação dos problemas acima mencionados, assim como técnicas com o intuito de apresentar dados estáticos e estatísticos, complementando a análise do desempenho de jogadores feita com a principal técnica de visualização utilizada. Por fim, foi feita uma avaliação do sistema de forma a perceber se as técnicas de visualização em uso são adequadas a este tipo de análise, e de que forma a ferramenta desenvolvida compete com outras existentes no mercado, com o objetivo de fazer análises do desempenho de jogadores. Este relatório apresenta o trabalho relacionado sobre dados espácio-temporais, assim como técnicas de visualização aplicadas aos mesmos e técnicas de visualização usadas em videojogos. É discutida a relevância dos eSports e a sua possível aplicação em áreas científicas, como visualização de estruturas moleculares, pelas técnicas de visualização utilizadas. São apresentados diferentes géneros de videojogos, como First-Person Shooter (FPS), Real-Time Strategy (RTS) e MOBA, explorando o tipo de análise que pode ser feita entre os géneros. É feita uma breve introdução à visualização, onde se enumeram seis passos que se devem ter em conta no processo de desenho de uma visualização correta. Existindo diferentes tipos de visualização, sendo a explorada neste relatório a visualização de informação, é nesta onde recaem os tipos de dados que são analisados utilizando o protótipo desenvolvido. Para a visualização de dados espácio-temporais, são introduzidos várias técnicas, dando foco a dois métodos utilizados em projetos anteriores: o Cubo Espaço-Tempo e os Mapas Animados. Uma vez que se está a explorar técnicas de visualização adequadas para analisar jogos, são também introduzidas diferentes técnicas de visualização existentes, aplicadas diretamente dentro do jogo, como mini mapa, barras de vida e heatmaps, ou usadas por aplicações de terceiros para análise, como gráficos de barras e linhas. Ligando o trabalho já desenvolvido com o atual, são revistos dois protótipos anteriores onde já foram aplicadas as técnicas de Cubo Espaço-Tempo e Mapas Animados, referindo as vantagens e desvantagens de cada uma para a análise de desempenho de jogadores. Por fim, ainda dentro do trabalho relacionado, é efetuada uma apresentação ao jogo LoL, explicando a mecânica do jogo, cujos dados telemétricos foram utilizados para a análise e aplicação desenvolvida, explicitando que tipo de dados espácio-temporais oferece. De seguida, é apresentado o protótipo desenvolvido juntamente com as vantagens de se construir uma aplicação web. A informação sobre a arquitetura desenvolvida é descrita em detalhe, assim como as tecnologias usadas, estando estas listadas tanto as do lado do cliente, como as do lado do servidor. Também é descrito como é que o processamento de dados foi realizado, mostrando excertos de pseudocódigo para melhor compreensão. Neste processamento de dados, é explicado como foi implementado o sistema de trajetos usado pela aplicação, assim como o tratamento efetuado sobre os dados, filtragem e reordenação, para o fácil uso e análise feita pelos utilizadores. Exibindo as funcionalidades da aplicação, é feita uma ponte entre os dados que foram processados, como estes são mostrados, e a sua possível interação com o utilizador, esclarecendo como foi realizada a sua implementação e o seu propósito. Algumas destas funcionalidades são fruto das soluções encontradas para os problemas do protótipo anterior. Outras fazem parte das técnicas de visualização utilizadas para complementar a técnica principal de visualização em uso. Para testar a aplicação desenvolvida foram realizados dois tipos de avaliação: a primeira correspondendo a entrevistas informais e a segunda uma comparação entre a aplicação desenvolvida com outras duas existentes no mercado, o OP.GG e o Replay do LoL. Estas ferramentas são apresentadas brevemente e utilizadas na avaliação da aplicação desenvolvida, tendo sido efetuada uma comparação direta entre elas, tanto ao nível dos dados apresentados, como ao nível das funcionalidades e técnicas de visualização que usam para apresentar estes dados. Para a segunda avaliação é explicada a metodologia e aparelhos usados na sua concretização, o tipo de participantes (jogadores casuais e profissionais da área) e as tarefas definidas que foram executadas nas três diferentes ferramentas de análise. Os resultados são apresentados, onde é discutida a precisão do sistema de trajetórias desenvolvido para a aplicação, assim como a análise feita pelos participantes para as diferentes tarefas, comparando-a entre as diferentes ferramentas utilizadas. Foi feito um levantamento das respostas finais dos participantes, onde foi perguntado o quão útil e fácil de usar é VisuaLeague II em relação às outras duas ferramentas, juntamente com a capacidade de se efetuar uma análise mais rápida. Também foi pedido aos participantes que declarassem as vantagens e desvantagens de usar VisuaLeague II em relação ao OP.GG e ao Replay do LoL. O estudo realizado pelos participantes sugere que os utilizadores preferem visualizar dados espácio-temporais dinamicamente, ou seja, visualizando mudanças ao longo do tempo, usando mapas animados. Além disso, a visualização de dados estáticos e estatísticos, juntamente com a visualização de dados espácio-temporais, melhora a análise do desempenho do jogador. Com a análise feita pelos participantes no estudo, é possível dividir a análise em dois tipos: as análises feitas por jogadores casuais e análises feitas por profissionais (tanto jogadores como treinadores/analistas). Os jogadores casuais simplesmente descrevem o que está a acontecer na visualização. No entanto, os profissionais elaboram teorias sobre o desempenho de um jogador, dando sugestões sobre como o jogador devia ter jogado em certas ocasiões. No geral, os participantes demonstraram uma atitude mais positiva em relação ao uso do VisuaLeague II e do Replay do LoL do que o OP.GG como uma ferramenta de análise, simplesmente porque melhores técnicas de visualização estão a ser utilizadas para visualizar dados espácio-temporais. Trabalho futuro também é mencionado onde se explicita vários pontos em que Visua- League II pode ser melhorado. Uma ideia é formulada com o propósito de ser possível a análise do desempenho do jogador não apenas em um jogo, mas ser possível expandir o protótipo de forma a analisar o desempenho do jogador ao longo de vários jogos.The phenomenon of eSports has been increasing over the years as well as the interest in online video games by players, coaches and analysts. One of the most popular genres of these games is the Multiplayer Online Battle Arena (MOBA) and during a match there are several types of events. These events, or actions, can range from the path a player traveled from one point to another, to more specific events in the match, such as the position where the player died. Analyzing this type of data by these stakeholders can generate pattern recognition allowing them to define new strategies that help players improve their performance. With the evolution of technology, it has become easier to use telemetry techniques to record events in online games, which leads to a high volume of data that can be collected over time. The objective of this work is to use the telemetric data provided by Riot Games, from League of Legends (LoL) matches, to redesign a prototype that explores the animated maps visualization technique, improving its computational performance, solving problems such as overlapping events and analysis only up to two players. Additional visualization techniques were applied to mitigate the above-mentioned problems, as well as the addition of other techniques to present static and statistical data. Finally, a comparison between the developed tool (VisuaLeague II) and other existing ones in the market (OP.GG and LoL’s Replay) was performed to understand if the visualization techniques implemented are adequate for analyzing player’s performance. The study carried out suggests that participants demonstrated a more positive attitude towards using VisuaLeague II and LoL’s Replay rather than OP.GG as an analysis tool, simply because better visualization techniques are being used to visualize spatio-temporal data. In addition, viewing static and statistical data, along with displaying spatio-temporal data, improves the player’s performance analysis

    The structural response and progressive failure of batten to rafter connections under wind loads

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    Batten to rafter connections in light framed timber housing are vulnerable to wind loading and failures of these connections are one of the more common failure modes seen in post windstorm damage surveys. Such failures often occur in a progressive or cascading manner resulting in the loss of a large section of the building envelope. These progressive failures of batten to rafter connections are a complex process influenced by the pressure fluctuations on the roof surface, the response of individual connections and the behaviour of the structural system as a whole. This study presents a method of examining load redistribution and progressive failure behaviour of batten to rafter connections in light framed structures. Nonlinear time history analysis was performed using a finite element model using fluctuating pressures determined from a wind tunnel study and connection properties determined from laboratory testing of connections under dynamic loads. Flow separation and building-induced turbulence cause intermittent 'peak-events' where negative pressures on the roof surface are especially high. These 'peak-events' can move across the roof causing high loads occurring at different connections with slight lead or lag times. Damage to connections occur during the 'peak events' as nails are incrementally withdrawn. Loads are redistributed and load paths change during nail slips, causing damage to spread from an initial location. Load redistribution continues until a few connections fail completely, upon which a cascading failure occurs where almost all connections on the roof fail in rapid succession. As an application of this research, the analyses performed were used to assess the fragility of batten-rafter failures, and the most vulnerable parts of the roof identified. Cost effective retrofitting measures can be justified and designed with this information

    ICSEA 2022: the seventeenth international conference on software engineering advances

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    The Seventeenth International Conference on Software Engineering Advances (ICSEA 2022), held between October 16th and October 20th, 2022, continued a series of events covering a broad spectrum of software-related topics. The conference covered fundamentals on designing, implementing, testing, validating and maintaining various kinds of software. Several tracks were proposed to treat the topics from theory to practice, in terms of methodologies, design, implementation, testing, use cases, tools, and lessons learned. The conference topics covered classical and advanced methodologies, open source, agile software, as well as software deployment and software economics and education. Other advanced aspects are related to on-time practical aspects, such as run-time vulnerability checking, rejuvenation process, updates partial or temporary feature deprecation, software deployment and configuration, and on-line software updates. These aspects trigger implications related to patenting, licensing, engineering education, new ways for software adoption and improvement, and ultimately, to software knowledge management. There are many advanced applications requiring robust, safe, and secure software: disaster recovery applications, vehicular systems, biomedical-related software, biometrics related software, mission critical software, E-health related software, crisis-situation software. These applications require appropriate software engineering techniques, metrics and formalisms, such as, software reuse, appropriate software quality metrics, composition and integration, consistency checking, model checking, provers and reasoning. The nature of research in software varies slightly with the specific discipline researchers work in, yet there is much common ground and room for a sharing of best practice, frameworks, tools, languages and methodologies. Despite the number of experts we have available, little work is done at the meta level, that is examining how we go about our research, and how this process can be improved. There are questions related to the choice of programming language, IDEs and documentation styles and standard. Reuse can be of great benefit to research projects yet reuse of prior research projects introduces special problems that need to be mitigated. The research environment is a mix of creativity and systematic approach which leads to a creative tension that needs to be managed or at least monitored. Much of the coding in any university is undertaken by research students or young researchers. Issues of skills training, development and quality control can have significant effects on an entire department. In an industrial research setting, the environment is not quite that of industry as a whole, nor does it follow the pattern set by the university. The unique approaches and issues of industrial research may hold lessons for researchers in other domains. We take here the opportunity to warmly thank all the members of the ICSEA 2022 technical program committee, as well as all the reviewers. The creation of such a high-quality conference program would not have been possible without their involvement. We also kindly thank all the authors who dedicated much of their time and effort to contribute to ICSEA 2022. We truly believe that, thanks to all these efforts, the final conference program consisted of top-quality contributions. We also thank the members of the ICSEA 2022 organizing committee for their help in handling the logistics of this event. We hope that ICSEA 2022 was a successful international forum for the exchange of ideas and results between academia and industry and for the promotion of progress in software engineering advances

    Distributed D3: A web-based distributed data visualisation framework for Big Data

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    The influx of Big Data has created an ever-growing need for analytic tools targeting towards the acquisition of insights and knowledge from large datasets. Visual perception as a fundamental tool used by humans to retrieve information from the outside world around us has its unique ability to distinguish patterns pre-attentively. Visual analytics via data visualisations is therefore a very powerful tool and has become ever more important in this era. Data-Driven Documents (D3.js) is a versatile and popular web-based data visualisation library that has tended to be the standard toolkit for visualising data in recent years. However, the library is technically inherent and limited in capability by the single thread model of a single browser window in a single machine, and therefore not able to deal with large datasets. The main objective of this thesis is to overcome this limitation and address possible challenges by developing the Distributed D3 framework that employs distributed mechanism to enable the possibility of delivering web-based visualisations for large-scale data, which also allows to effectively utilise the graphical computational resources of the modern visualisation environments. As a result, the first contribution is that the integrated version of Distributed D3 framework has been developed for the Data Observatory. The work proves the concept of Distributed D3 is feasible in reality and also enables developers to collaborate on large-scale data visualisations by using it on the Data Observatory. The second contribution is that the Distributed D3 has been optimised by investigating the potential bottlenecks for large-scale data visualisation applications. The work finds the key performance bottlenecks of the framework and shows an improvement of the overall performance by 35.7% after optimisations, which improves the scalability and usability of Distributed D3 for large-scale data visualisation applications. The third contribution is that the generic version of Distributed D3 framework has been developed for the customised environments. The work improves the usability and flexibility of the framework and makes it ready to be published in the open-source community for further improvements and usages.Open Acces

    Parallel Hierarchies: Interactive Visualization of Multidimensional Hierarchical Aggregates

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    Exploring multi-dimensional hierarchical data is a long-standing problem present in a wide range of fields such as bioinformatics, software systems, social sciences and business intelligence. While each hierarchical dimension within these data structures can be explored in isolation, critical information lies in the relationships between dimensions. Existing approaches can either simultaneously visualize multiple non-hierarchical dimensions, or only one or two hierarchical dimensions. Yet, the challenge of visualizing multi-dimensional hierarchical data remains open. To address this problem, we developed a novel data visualization approach -- Parallel Hierarchies -- that we demonstrate on a real-life SAP SE product called SAP Product Lifecycle Costing. The starting point of the research is a thorough customer-driven requirement engineering phase including an iterative design process. To avoid restricting ourselves to a domain-specific solution, we abstract the data and tasks gathered from users, and demonstrate the approach generality by applying Parallel Hierarchies to datasets from bioinformatics and social sciences. Moreover, we report on a qualitative user study conducted in an industrial scenario with 15 experts from 9 different companies. As a result of this co-innovation experience, several SAP customers requested a product feature out of our solution. Moreover, Parallel Hierarchies integration as a standard diagram type into SAP Analytics Cloud platform is in progress. This thesis further introduces different uncertainty representation methods applicable to Parallel Hierarchies and in general to flow diagrams. We also present a visual comparison taxonomy for time-series of hierarchically structured data with one or multiple dimensions. Moreover, we propose several visual solutions for comparing hierarchies employing flow diagrams. Finally, after presenting two application examples of Parallel Hierarchies on industrial datasets, we detail two validation methods to examine the effectiveness of the visualization solution. Particularly, we introduce a novel design validation table to assess the perceptual aspects of eight different visualization solutions including Parallel Hierarchies.:1 Introduction 1.1 Motivation and Problem Statement 1.2 Research Goals 1.3 Outline and Contributions 2 Foundations of Visualization 2.1 Information Visualization 2.1.1 Terms and Definition 2.1.2 What: Data Structures 2.1.3 Why: Visualization Tasks 2.1.4 How: Visualization Techniques 2.1.5 How: Interaction Techniques 2.2 Visual Perception 2.2.1 Visual Variables 2.2.2 Attributes of Preattentive and Attentive Processing 2.2.3 Gestalt Principles 2.3 Flow Diagrams 2.3.1 Classifications of Flow Diagrams 2.3.2 Main Visual Features 2.4 Summary 3 Related Work 3.1 Cross-tabulating Hierarchical Categories 3.1.1 Visualizing Categorical Aggregates of Item Sets 3.1.2 Hierarchical Visualization of Categorical Aggregates 3.1.3 Visualizing Item Sets and Their Hierarchical Properties 3.1.4 Hierarchical Visualization of Categorical Set Aggregates 3.2 Uncertainty Visualization 3.2.1 Uncertainty Taxonomies 3.2.2 Uncertainty in Flow Diagrams 3.3 Time-Series Data Visualization 3.3.1 Time & Data 3.3.2 User Tasks 3.3.3 Visual Representation 3.4 Summary ii Contents 4 Requirement Engineering Phase 4.1 Introduction 4.2 Environment 4.2.1 The Product 4.2.2 The Customers and Development Methodology 4.2.3 Lessons Learned 4.3 Visualization Requirements for Product Costing 4.3.1 Current Visualization Practice 4.3.2 Visualization Tasks 4.3.3 Data Structure and Size 4.3.4 Early Visualization Prototypes 4.3.5 Challenges and Lessons Learned 4.4 Data and Task Abstraction 4.4.1 Data Abstraction 4.4.2 Task Abstraction 4.5 Summary and Outlook 5 Parallel Hierarchies 5.1 Introduction 5.2 The Parallel Hierarchies Technique 5.2.1 The Individual Axis: Showing Hierarchical Categories 5.2.2 Two Interlinked Axes: Showing Pairwise Frequencies 5.2.3 Multiple Linked Axes: Propagating Frequencies 5.2.4 Fine-tuning Parallel Hierarchies through Reordering 5.3 Design Choices 5.4 Applying Parallel Hierarchies 5.4.1 US Census Data 5.4.2 Yeast Gene Ontology Annotations 5.5 Evaluation 5.5.1 Setup of the Evaluation 5.5.2 Procedure of the Evaluation 5.5.3 Results from the Evaluation 5.5.4 Validity of the Evaluation 5.6 Summary and Outlook 6 Visualizing Uncertainty in Flow Diagrams 6.1 Introduction 6.2 Uncertainty in Product Costing 6.2.1 Background 6.2.2 Main Causes of Bad Quality in Costing Data 6.3 Visualization Concepts 6.4 Uncertainty Visualization using Ribbons 6.4.1 Selected Visualization Techniques 6.4.2 Study Design and Procedure 6.4.3 Results 6.4.4 Discussion 6.5 Revised Visualization Approach using Ribbons 6.5.1 Application to Sankey Diagram 6.5.2 Application to Parallel Sets 6.5.3 Application to Parallel Hierarchies 6.6 Uncertainty Visualization using Nodes 6.6.1 Visual Design of Nodes 6.6.2 Expert Evaluation 6.7 Summary and Outlook 7 Visual Comparison Task 7.1 Introduction 7.2 Comparing Two One-dimensional Time Steps 7.2.1 Problem Statement 7.2.2 Visualization Design 7.3 Comparing Two N-dimensional Time Steps 7.4 Comparing Several One-dimensional Time Steps 7.5 Summary and Outlook 8 Parallel Hierarchies in Practice 8.1 Application to Plausibility Check Task 8.1.1 Plausibility Check Process 8.1.2 Visual Exploration of Machine Learning Results 8.2 Integration into SAP Analytics Cloud 8.2.1 SAP Analytics Cloud 8.2.2 Ocean to Table Project 8.3 Summary and Outlook 9 Validation 9.1 Introduction 9.2 Nested Model Validation Approach 9.3 Perceptual Validation of Visualization Techniques 9.3.1 Design Validation Table 9.3.2 Discussion 9.4 Summary and Outlook 10 Conclusion and Outlook 10.1 Summary of Findings 10.2 Discussion 10.3 Outlook A Questionnaires of the Evaluation B Survey of the Quality of Product Costing Data C Questionnaire of Current Practice Bibliograph

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