Detta examensarbete har syftat till att utforma ett informativt budskap om ITP 2 ålderspension. Målet har varit att lyfta fram specifik information om ITP 2 ålderspension för vår uppdragsgivares anställda. Budskapet har visualiserats genom en animerad informationsfilm och ska fungera som ett komplement till redan befintlig information. Baserat på tidigare forskning och resultat från intervjuer som vi genomfört har vi funnit riktlinjer som legat till grund för de designval och beslut vi tagit under processens gång. Resultatet blev en animerad informationsfilm med en avskalad och enkelt utformad design. / This project has aimed to design an informative message regarding ITP 2 retirement pension. The goal has been to highlight specific information regarding ITP 2 retirement pension for the employees of our client. The message has been visualized as an animated information video and will serve as a complement to existing information. Based on previous research and results from our conducted interviews, guidelines have been obtained which have formed the basis for the design choices and decisions we have taken during the process. The outcome of this project is an animated information video with a clean and simple design.

Aus der Einführung: "Die Verwendung von Prototypen besitzt eine zentrale Rolle bei der Produktentwicklung und im Designprozess (Camere et al. 2016). Wie Camere und Bordegoni feststellen hat sich der Fokus der Designdisziplin auf Funktionalität um die Aspekte der Usability und der User Experience erweitert. Damit einhergehend hat sich auch die Rolle der Prototypen von Funktionsmustern und Präsentationsobjekten um die Funktionen als Evaluierungs- und Versuchsobjekte ergänzt. Die Integration von Nutzern in den Designprozess ist dabei ein weiterer Punkt bei denen Prototypen ein wichtiges Werkzeug zur Kommunikation und kooperativen Arbeit liefert (Schneider 1996). Die Integration von Prototyping-Methoden in den unterschiedlichen Phasen des Designprozesses führt zu unterschiedlichen Anforderungen hinsichtlich der Form und Aufgabe der Prototypen. Entsprechend vielfältig sind die heute verwendeten Arten von Prototyping. ..."

Orientador: Celmar Guimarães da Silva / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Tecnologia / Made available in DSpace on 2018-08-27T09:05:54Z (GMT). No. of bitstreams: 1 Medina_BrunoFigueiredo_M.pdf: 3649814 bytes, checksum: ab007f9e22f1dab1394a99e9b4d80b4f (MD5) Previous issue date: 2015 / Resumo: Matrizes são estruturas subjacentes a diferentes tipos de visualização de dados, como por exemplo, heatmaps. Diferentes algoritmos possibilitam uma permutação automática de suas linhas e colunas para prover um melhor entendimento visual, procurando agrupar linhas e colunas similares e evidenciar padrões. Trabalhos anteriores testaram e compararam alguns desses algoritmos em matrizes de dados binários, obtendo bons resultados o algoritmo PQR-Sort with Sorted Restrictions, em termos de tempo de execução e qualidade da reordenação em alguns tipos de matrizes. Contudo, este algoritmo não foi estendido para trabalhar com matrizes de dados quantitativos. Dessa forma, como continuidade desses trabalhos, este projeto testa a hipótese de que é possível elaborar variações do algoritmo PQR-Sort with Sorted Restrictions capazes de reordenar matrizes de dados quantitativos, e cuja eficiência de tempo e de qualidade da reordenação supere algoritmos de mesmo propósito. Neste projeto, foram elaborados os algoritmos Smoothed Multiple Binarization (SMB) e Multiple Binarization (MB). Ambos utilizam criação de vetores característicos (para descoberta de padrões canônicos de dados), árvores PQR e binarização de matrizes para sua reordenação. O SMB possui um potencial para prover boas reordernações de matrizes que contenham ruídos, pois faz o tratamento destes ruídos no conjunto de dados. Esses algoritmos foram testados e comparados com o Multidimensional Scaling (MDS) e algoritmo de Sugiyama adaptado (heurística baricêntrica), em termos de qualidade de reordenação e tempo de execução sobre matrizes sintéticas com os padrões canônicos Simplex, Band, Circumplex e Equi. Os resultados obtidos indicaram que os algoritmos SMB e MB destacaram-se dentre os demais pela capacidade de evidenciação do padrão Circumplex, e trouxeram resultados similares aos dos algoritmos testados para os padrões Equi e Band. Os resultados também indicam que SMB e MB são, em média, 3 e 6 vezes mais rápidos que o MDS, respectivamente. Deste modo, o uso de SMB e MB torna-se atrativo para a reordenação de matrizes que evidenciem padrões Circumplex, Equi e Band / Abstract: Matrices are structures underlying different types of data visualization, as heatmap. Different algorithms enable automatic permutation of their rows and columns to provide a better visual understanding, aiming to group similar rows and columns and show patterns. Earlier work tested and compared some of these algorithms on binary data matrices, and revealed that PQR-Sort with Sorted Restrictions algorithm returned good results in terms of runtime and quality of reordered matrix. However, this algorithm was not extended for quantitative data matrices. Thus, as a continuation of these studies, this project aims to test the hypothesis that it is possible to develop variations of the PQR-Sort with Sorted Restrictions algorithm able to reorder quantitative data matrices, and whose quality of results and time efficiency surpasses algorithms that have the same purpose. In this work, it was elaborated the Smoothed Multiple Binarization (SMB) and Multiple Binarization (MB). Both use feature selection (to discovering canonical pattern of data), PQR Tree and binary matrices for their reordering. SMB algorithm has a potential to provide good matrices reordering with noise, because it does the noise treatment in data sets. These algorithms were tested and compared with Multidimensional Scaling (MDS) and Adapted Sugiyama (or Barycentric Heuristic) algorithms, in terms of quality of reordering and runtime on synthetics matrices with the canonical patterns Simplex, Band, Circumplex and Equi. The results indicated that SMB and MB algorithms stood out from the others by capacity of highlight Circumplex pattern, besides showing that may to obtain similar results to MDS and Adapted Sugiyama for Equi and Band patterns. Furthermore, SMB and MB were, on average, 3 and 6 times faster than MDS, respectively. Thus, the use of the SMB and MB algorithms can be attractive for matrices reordering that evidence Circumplex, Equi and Band patterns / Mestrado / Tecnologia e Inovação / Mestre em Tecnologia

As técnicas de projeção ou posicionamento de pontos no plano, que servem para mapear dados multi-dimensionais em espaços visuais, sempre despertaram grande interesse da comunidade de visualização e análise de dados por representarem uma forma útil de exploração baseada em relações de similaridade e correlação. Apesar disso, muitos problemas ainda são encontrados em tais técnicas, limitando suas aplicações. Em especial, as técnicas de projeção multi-dimensional de maior qualidade têm custo computacional proibitivo para grandes conjuntos de dados. Adicionalmente, problemas referentes à escalabilidade visual, isto é, à capacidade da metáfora visual empregada de representar dados de forma compacta e amigável, são recorrentes. Esta tese trata o problema da projeção multi-dimensional de vários pontos de vista, propondo técnicas que resolvem, até certo ponto, cada um dos problemas verificados. Também é fato que a complexidade e o tamanho dos conjuntos de dados indicam que a visualização deve trabalhar em conjunto com técnicas de mineração, tanto embutidas no processo de mapeamento, como por meio de ferramentas auxiliares de interpretação. Nesta tese incorporamos alguns aspectos de mineração integrados ao processo de visualização multi-dimensional, principalmente na aplicação de projeções para visualização de coleções de documentos, propondo uma estratégia de extração de tópicos. Como suporte ao desenvolvimento e teste dessas técnicas, foram criados diferentes sistemas de software. O principal inclui as técnicas desenvolvidas e muitas das técnicas clássicas de projeção, podendo ser usado para exploração de conjuntos de dados multi-dimensionais em geral, com funcionalidade adicional para mapeamento de coleções de documentos. Como principal contribuição desta tese propomos um entendimento mais profundo dos problemas encontrados nas técnicas de projeção vigentes e o desenvolvimento de técnicas de projeção (ou mapeamento) que são rápidas, tratam adequadamente a formação visual de grupos de dados altamente similares, separam satisfatoriamente esses grupos no layout, e permitem a exploração dos dados em vários níveis de detalhe / Projection or point placement techniques, useful for mapping multidimensional data into visual spaces, have always risen interest in the visualization and data analysis communities because they can support data exploration based on similarity or correlation relations. Regardless of that interest, various problems arise when dealing with such techniques, impairing their widespread application. In particularly the projections that yield highest quality layouts have prohibitive computational cost for large data sets. Additionally, there are issues regarding visual scalability, i.e., the capability of visually fit the individual points in the exploration space as the data set grows large. This thesis treats the problems of projections from various perspectives, presenting novel techniques that solve, to certain extent, several of the verified problems. It is also a fact that size and complexity of data sets suggest the integration of data mining capabilities into the visualization pipeline, both during the mapping process and as a tools to extract additional information after the data have been layed out. This thesis also add some aspects of mining to the multidimensional visualization process, mainly for the particular application of analysis of document collections, proposing and implementing an approach for topic extraction. As supporting tools for testing these techniques and comparing them to existing ones different software systems were written. The main one includes the techniques developed here as well as several of the classical projection and dimensional reduction techniques, and can be used for exploring various kinds of data sets, with addition functionality to support the mapping of document collections. This thesis contributes to the understanding of the projection or mapping problem and develops new techniques that are fast, treat adequately the visual formation of groups of highly related data items, separate those groups properly and allow exploration of data in various levels of detail

Usuários da Internet estão muito familiarizados que resultados de uma consulta sejam exibidos como uma lista ordenada de snippets. Cada snippet possui conteúdo textual que mostra um resumo do documento referido (ou página web) e um link para o mesmo. Esta representação tem muitas vantagens como, por exemplo, proporcionar uma navegação fácil e simples de interpretar. No entanto, qualquer usuário que usa motores de busca poderia reportar possivelmente alguma experiência de decepção com este modelo. Todavia, ela tem limitações em situações particulares, como o não fornecimento de uma visão geral da coleção de documentos recuperados. Além disso, dependendo da natureza da consulta - por exemplo, pode ser muito geral, ou ambígua, ou mal expressa - a informação desejada pode ser mal classificada, ou os resultados podem contemplar temas variados. Várias tarefas de busca seriam mais fáceis se fosse devolvida aos usuários uma visão geral dos documentos organizados de modo a refletir a forma como são relacionados, em relação ao conteúdo. Propomos uma técnica de visualização para exibir os resultados de consultas web que visa superar tais limitações. Ela combina a capacidade de preservação de vizinhança das projeções multidimensionais com a conhecida representação baseada em snippets. Essa visualização emprega uma projeção multidimensional para derivar layouts bidimensionais dos resultados da pesquisa, que preservam as relações de similaridade de texto, ou vizinhança. A similaridade é calculada mediante a aplicação da similaridade do cosseno sobre uma representação bag-of-words vetorial de coleções construídas a partir dos snippets. Se os snippets são exibidos diretamente de acordo com o layout derivado, eles se sobrepõem consideravelmente, produzindo uma visualização pobre. Nós superamos esse problema definindo uma energia funcional que considera tanto a sobreposição entre os snippets e a preservação da estrutura de vizinhanças como foi dada no layout da projeção. Minimizando esta energia funcional é fornecida uma representação bidimensional com preservação das vizinhanças dos snippets textuais com sobreposição mínima. A visualização transmite tanto uma visão global dos resultados da consulta como os agrupamentos visuais que refletem documentos relacionados, como é ilustrado em vários dos exemplos apresentados / Internet users are very familiar with the results of a search query displayed as a ranked list of snippets. Each textual snippet shows a content summary of the referred document (or web page) and a link to it. This display has many advantages, e.g., it affords easy navigation and is straightforward to interpret. Nonetheless, any user of search engines could possibly report some experience of disappointment with this metaphor. Indeed, it has limitations in particular situations, as it fails to provide an overview of the document collection retrieved. Moreover, depending on the nature of the query - e.g., it may be too general, or ambiguous, or ill expressed - the desired information may be poorly ranked, or results may contemplate varied topics. Several search tasks would be easier if users were shown an overview of the returned documents, organized so as to reflect how related they are, content-wise. We propose a visualization technique to display the results of web queries aimed at overcoming such limitations. It combines the neighborhood preservation capability of multidimensional projections with the familiar snippet-based representation by employing a multidimensional projection to derive two-dimensional layouts of the query search results that preserve text similarity relations, or neighborhoods. Similarity is computed by applying the cosine similarity over a bag-of-words vector representation of collection built from the snippets. If the snippets are displayed directly according to the derived layout they will overlap considerably, producing a poor visualization. We overcome this problem by defining an energy functional that considers both the overlapping amongst snippets and the preservation of the neighborhood structure as given in vii the projected layout. Minimizing this energy functional provides a neighborhood preserving two-dimensional arrangement of the textual snippets with minimum overlap. The resulting visualization conveys both a global view of the query results and visual groupings that reflect related results, as illustrated in several examples shown

As técnicas de projeção multidimensional tornaram-se uma ferramenta de análise importante. Elas buscam mapear dados de um espaço multidimensional para um espaço visual, de menor dimensão, preservando as estruturas de distância ou de vizinhança no mapa visual produzido. Apesar dos recentes avanços, as técnicas existentes ainda apresentam deficiências que prejudicam a sua utilização como ferramentas exploratórias em certos domínios. Um exemplo está nos cenários streaming, nos quais os dados são produzidos e/ou coletados de forma contínua. Como a maioria das técnicas de projeção necessitam percorrer os dados mais de uma vez para produzir um layout final, e fluxos normalmente não podem ser carregados por completo em memória principal, a aplicação direta ou mesmo a adaptação das técnicas existentes em tais cenários é inviável. Nessa tese de doutorado é apresentado um novo modelo de projeção, chamado de Xtreaming, no qual as instâncias de dados são visitadas apenas uma vez durante o processo de projeção. Esse modelo é capaz de se adaptar a mudanças nos dados conforme eles são recebidos, atualizando o mapa visual para refletir as novas estruturas que surgem ao longo do tempo. Os resultados dos testes mostram que o Xtreaming é muito competitivo em termos de preservação de distâncias e tempo de execução se comparado com técnicas do estado-da-arte. Também é apresentada uma nova técnica de projeção multidimensional, chamada de User-assisted Projection Technique for Distance Information (UPDis), que foi projetada para permitir a intervenção do usuário exigindo apenas informações de distância entre as instâncias, e que é utilizada como parte do Xtreaming. Os resultados também mostram que a UPDis é tão rápida, precisa e flexível quanto as técnicas do estado-da-arte. / Multidimensional Projection techniques have become an important analytics tool. They map data from a multidimensional space into a visual space preserving the distance or neighborhood structures on the produced layout. Despite the recent advances, existing techniques still present drawbacks that impair their use as exploratory tools on certain domains. An example is the streaming scenario, in which data are captured or produced continuously. Since most projection techniques need to traverse the data more than once to produce a final layout, and streaming data typically cannot be completely loaded into the main memory, the direct use or even adaptation of the existing techniques in such scenarios is infeasible. In this dissertation, we present a novel projection model, called Xtreaming, wherein the data instances are visited only once during the projection process. This model is able to adapt itself to the changes in data as data is received, updating the visual layout to reflect the new structures that emerge over time. The tests show that Xtreaming is very competitive regarding distance preservation and running time when compared with state-of-the-art projection techniques. We also present a new multidimensional projection technique, called User-assisted Projection Technique for Distance Information (UPDis), that was designed to allow user intervention requiring only distance information between data instances. UPDis is used as part of the Xtreaming model. The results show that UPDis is as fast, accurate and flexible as state-of-the-art techniques.

Simulações por computador permitem reduzir custo e, muitas vezes, realizar experimentos que na vida real seriam impraticáveis, ou por questões ambientais (explosões nucleares), ou por fatores que estão fora do controle do ser humano (colisões entre estrelas). Entretanto, e muito difícil manipular e analisar as centenas de gigabytes, ou mesmo terabytes, que tais simulações produzem como resultado. Os trabalhos que lidam com tais conjuntos de dados, tipicamente, empregam tanto técnicas de visualização científica como técnicas de visualização da informação, em geral refletindo o comportamento dos dados em um único instante de tempo. Entretanto, a análise da evolução temporal e a disponibilização de representações visuais integradas ainda é um grande desafio. Esse trabalho introduz diversas estratégias buscando tratar estes problemas, as quais tem em comum a utilização de projeções multidimensionais para apoiar a análise exploratória dos de dados, tanto em um instante de tempo específico, como ao longo da evolução temporal. O objetivo é favorecer a localização de grupos de elementos com comportamento similar e acompanhar sua evolução ao longo da simulação. Uma das estratégias introduzidas resume o comportamento temporal dos dados multidimensionais em uma única visualização, o que permite rastrear as entidades com comportamento similar e analisá-las ao longo da simulação / Computer simulations of physical phenomena allow reducing costs and studying behavior that would be unfeasible to observe in real life situations, either due to environmental limitations, e.g., a nuclear explosion, or due to factors that are beyond human control (e.g., collisions between stars). Millions of primitives (voxels, vertices or particle) may be required to accurately capture system behavior, thus generating very large data sets that are typically time-varying and multidimensional, as multiple simulation variables describe each primitive. Therefore, analyzing the hundreds of gigabytes or even terabytes resulting from these simulations remains a challenge. Current solutions that handle this type of data usually rely on Scientific or Information Visualization techniques, but typically revealing data behavior at a particular time instant. It remains a major challenge to provide visualizations capable of assisting analysts trying to inspect and understand behavior along the temporal domain. This work is an attempt in this direction, introducing several strategies to handle these problems. They have in common the use of multidimensional projection techniques to support exploratory analysis of simulation data, both at specic time instants and along the simulation as a whole. The goal is to favor the perception of groups of elements showing similar behavior and track their temporal evolution. One of the strategies introduced summarizes, in a single visual representation, the temporal behavior of the multidimensional data space, thus allowing analysts to identify and analyze the entities with similar behavior along the simulation

Access to and understanding data plays an essential role in the increasingly digital world. Representation and analysis of relations between various data entities, i.e., graph and network structures in the data, is an important problem for various industries. In contrast to simple graphs that focus on edges with two endpoints only, a hypergraph provides a natural method to represent multi-way interactions with an arbitrary number of endpoints for each edge, and it can be a better alternative than a bipartite graph for comparable applications. However, traditional approaches for visually representing hypergraphs are purely static diagrams without support for interaction, which can be difficult to perceive and do not scale well with regard to the number of nodes and edges. They are not adequate for the representation and interactive exploration of large or dense hypergraph data sets found in real-world applications. The ISOVIS (Information and Software Visualisation) research group at Linnaeus University has previously introduced a novel radial visualization approach for undirected hypergraphs called Onion. The Onion tool focuses on solving the issues of edge clutter, overlaps, and edge crossings. However, certain open challenges and suggestions for improvements were identified for the respective implementation, and there is an opportunity to fill a gap in the hypergraph visualization research by building upon the original Onion approach study. In this thesis project, we implement the new version of the Onion approach based on the principles and challenges established previously. The contributions of this work include evidence regarding the effectiveness and efficiency of a hypergraph comparison technique, the usability of edge bundling in the context of hypergraph exploration tasks, and the scalability of the interactive visualization through an entirely new web-based version of the Onion approach. To obtain the respective results, the new implementation is applied for two case studies involving real-world data sets, and further validated through a user study with several participants. The results of this work can be helpful for researchers of network visualization and practitioners in need of approaches for representing and exploring data that can be modeled as hypergraphs.

The performance of hard disks has become increasingly important as the volume of data storage increases. At the bottom level of large-scale storage networks is the hard disk. Despite the importance of hard drives in a storage network, it is often difficult to analyze the performance of hard disks due to the sheer size of the datasets seen by hard disks. Additionally, hard drive workloads can have several multi-dimensional characteristics, such as access time, queue depth and block-address space. The result is that hard drive workloads are extremely diverse and large, making extracting meaningful information from hard drive workloads very difficult. This is one reason why there are several inefficiencies in storage networks. In this paper, we develop a tool that assists in communicating valuable insights into these datasets, resulting in an approach that utilizes parallel coordinates to model data storage workloads captured with bus analyzers. Users are presented with an effective visualization of workload captures with this implementation, along with methods to interact with and manipulate the model in order to more clearly analyze the lowest level of their storage systems. Design decisions regarding the feature set of this tool are based on the analysis needs of domain experts and feedback from a conducted user study. Results from our user study evaluations demonstrate the efficacy of our tool to observe valuable insights, which can potentially assist in future storage system design and deployment decisions. Using this tool, domain experts were able to model storage system datasets with various features to manipulate the visualization to make observations and discoveries, such as detecting logical block address banding and observe various dataset trends which were not readily noticeable using conventional analysis methods.

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 Bibliography