Dashboard for collecting and depicting the marine megafauna presence

While more and more technologies and software are being created and applied for the ocean setting, most of them still remain at high cost, and hinder the data to wider public. Understanding the marine biodiversity can be achieved through numerous ways, however, there is a lack of consensus and operability when depicting the marine megafauna population. Moreover, Deep Learning (DL) techniques are becoming accessible to wider population, and there is a potential of exposing them to the marine biologists, involving them to participate in public web-based dashboards, depicting those data. This dissertation addresses such issues, by providing an interactive dashboard, capable of fa cilitating the classification, prediction and deeper analysis of marine species. Using the State of Art (SoA) Machine Learning (ML) techniques for image vision, and providing the interactive vi sualizations, this thesis seeks to provide a less cumbersome apparatus for marine biologists, who can participate further in data gathering, labelling, depicting, ecological modelling, and potential calls for action. In further, this dissertation document provides the aquatic dashboard functionality using Human-Computer Interaction (HCI) techniques and interactive means to ease the upload, clas sification, and visualization of collected marine taxa, with a case study on marine megafauna imagery (e.g. whales, dolphins, sea birds, seals and turtles). As it will be hereinafter described, marine biologists, as end users, will evaluate of the proposed dashboard.Todos os dias surgem novas tecnologias e softwares que podem ser aplicados no ecossistema marinho, sendo que a maioria destas permanecem com um custo elevado, dificultando assim o acesso ao público em geral. O conhecimento deste sistema e de toda a biodiversidade nele existente, pode ser alcançado de diversas formas, no entanto, existe uma falta de consenso e operacionalidade ao descrever a população de megafauna. Além disto, técnicas de aprendizagem automática como o deep learning, permanecem acessíveis a uma população mais ampla, e existe o potential do envolvimento de profissionais da área, mais conhecidos como biólogos marinhos, para participar na criação e usabilidade de plataformas conhecidas como dashboards. Esta tese tem como função debater estas questões, fornecendo um dashboard interativo, capaz de facilitar a classificação, previsão e análise mais profunda das espécies marinhas. Usando técnicas de aprendizagem automática de última geração, para informação visual em imagens, e fornecer interfaces visuais muito interativas, esta tese procura fornecer uma ferramenta simples para os biólogos marinhos, podendo assim participar na recolha de dados, rotulagem, modelação ecológica e possíveis pedidos de alerta. A dissertação produzirá um dashboard funcional, utilizando técnicas de Interação Humano Computador (HCI) e meios interativos para facilitar o carregamento de dados, a classificação e visualização da fauna marinha coletada (p.ex. baleia, golfinho, ave marinha, foca e tartaruga). Como será descrito durante este manuscrito, biólogos marinhos, como utilizadores finais, irão participar na avaliação deste proposto dashboard

트리 구조를 이용한 3차원 공간 내 데이터 시각화 연구

학위논문 (박사)-- 서울대학교 대학원 : 미술대학 디자인학부 디자인전공, 2019. 2. 김수정.Speculative visualization combines both data visualization methods and aesthetics to draw attention to specific social, political and environmental issues. The speculative data visualization project proposed in this work explores electronic waste trade and the environmental performance of various nations. Illegal trading of electronic waste without proper disposal and recycling measures has a severe impact on both human health and the environment. This trade can be represented as a network data structure. The overall environmental health and ecosystem vitality of those trading countries, represented by their Environmental Performance Index (EPI), can also give greater insight into this issue. This EPI data has a hierarchical structure. This work explores methods to visualize these two data sets simultaneously in a manner that allows for analytical exploration of the data while communicating its underlying meaning. This project-based design research specifically focuses on visualizing hierarchical datasets with a node-link type tree structure and suggests a novel data visualization method, called the data garden, to visualize these hierarchical datasets within a spatial network. This draws inspiration from networks found between trees in nature. This is applied to the illegal e-waste trade and environmental datasets to provoke discussion, provide a holistic understanding and improve the peoples awareness on these issues. This uses both analytical data visualization techniques, along with a more aesthetic approach. The data garden approach is used to create a 3D interactive data visualization that users can use to navigate and explore the data in a meaningful way while also providing an emotional connection to the subject. This is due to the ability of the data garden approach to accurately show the underlying data while also closely mimicking natural structures. The visualization project intends to encourage creative professionals to create both visually appealing and thought-provoking data visualizations on significant issues that can reach a mass audience and improve awareness of citizens. Additionally, this design research intends to cause further discussion on the role of aesthetics and creative practices in data visualizations.사변적 시각화(speculative visualization)는 데이터 시각화 방법과 미학을 결합하여 특정한 사회, 정치 및 환경 문제에 관심을 유도하는 것입니다. 제안한 사변적 데이터 시각화 프로젝트를 통해 다양한 국가의 전자 폐기물 거래와 환경 성과를 살펴봅니다. 적절한 처리와 재활용 조치가 이뤄지지 않은 전자폐기물의 불법 거래는 환경과 인간에 심각한 영향을 미칩니다. 이 거래는 네트워크 데이터 구조로 표현할 수 있습니다. 환경성과지수(EPI)를 통해 이 거래에 참여하는 국가들의 전반적인 환경 보건과 생태계 활력을 살펴보는 것은 이 문제에 더 깊은 통찰력을 제공할 수 있습니다. 이 환경성과지수는 계층 구조로 되어 있습니다. 이 연구는 데이터를 분석적으로 탐구할 수 있도록 하는 방법을 통해 두 가지 데이터를 동시에 시각화하고, 이를 통해 표면에 드러나지 않는 데이터의 의미를 전달하는 방법을 탐구합니다. 본 연구는 프로젝트를 기반으로 하는 디자인 연구로, 노드 링크 유형 트리 구조를 통해 계층적 데이터를 시각화하는 것에 중점을 두고 있습니다. 자연에서 발견할 수 있는 나무 간 네트워크에서 영감을 얻어 공간 네트워크에서 계층적 데이터 세트를 시각화합니다. 데이터 정원이라고 하는 이 새로운 데이터 시각화 방법을 불법 전자 폐기물 거래와 환경 데이터에 적용하여 토론을 유발하고 전체적인 이해를 제공하며 이러한 문제에 대한 사람들의 인식을 개선하고자 합니다. 이는 보다 미적인 접근과 분석적 데이터 시각화 기술을 모두 사용합니다. 데이터 정원을 통한 접근으로 삼차원 대화형 데이터 시각화를 만들 수 있습니다. 이 시각화를 통해 사용자는 데이터를 의미 있는 방식으로 살펴보는 동시에 주제와 감성적인 연결을 받을 수 있습니다. 이는 데이터 정원 방법이 데이터를 정확하게 보여주는 동시에 자연 구조를 면밀하게 모방하기 때문입니다. 본 시각화 프로젝트는 창의적인 전문가들이 중요한 문제에 대해 시각적으로 매력적이고 생각을 자극하는 데이터 시각화를 만들어 대중에게 도달하고 시민들의 인식을 향상할 수 있도록 권장합니다. 또한, 본 디자인 연구는 데이터 시각화에서 미학과 창조적인 실천의 역할에 대한 더 많은 논의를 유도하고자 합니다.Abstract I Table of Contents III List of Figures VI 1. Introduction 1 1.1 Research Background 2 1.2 Research Goal and Method 6 1.3 Terminology 9 2. Hierarchical Relationships: Trees 14 2.1 The History of Tree Diagrams 16 2.1.1 Significance of Trees 16 2.1.2 Aristotles Hierarchical Order of Life 19 2.1.3 Early Religious Depictions of Hierarchical Structures 22 2.1.4 Depicting Evolution 26 2.2 Tree Structures 29 2.3 Tree Layouts 31 3. Complex Relationships: Networks 34 3.1 Attributes of Networks 36 3.1.1 Interdependence and Interconnectedness 38 3.1.2 Decentralization 42 3.1.3 Nonlinearity 45 3.1.4 Multiplicity 46 3.2 Spatial Networks 46 3.3 Combining Tree Structures and Networks 48 4. Design Study Goals and Criteria 51 4.1 Objectives of the Design Study 71 4.2 Data Visualization Approaches 54 4.3 Criteria of Data Visualization 57 4.3.1 Aesthetics 58 4.3.2 Information Visualization Principles 62 4.3.2.1 Visual Cues in Data Visualization 62 4.3.2.2 Gestalt Principles 65 4.3.2.3 Increasing Efficiency of Network Visualizations 67 4.4 Case Study 70 5. Design Study: Data Garden Method 78 5.1 Concept of the Data Garden Structure 79 5.2 Data Garden Tree Structure 84 5.2.1 360°Vertical Branches 85 5.2.2 Break Point of the Branches 87 5.2.3 Aligning Hierarchy Levels 89 5.2.3.1 Design 01 – Extend Method 90 5.2.3.2 Design 02 – Collapse Method 91 5.2.4 Node Placement Technique 92 5.3 Conveying 3D Information 95 6. Design Study: Visualization Project 98 6.1 Theme 99 6.1.1 E-waste Trade 100 6.1.2 Environmental Performance Index 102 6.2 Visual Design Concept 104 6.3 Assigning Attributes 105 6.4 Visual Design Process 107 6.4.1 Leaf (Node) Design Process 107 6.4.1.1 Leaf Inspiration 107 6.4.1.2 Leaf Design 108 6.4.1.3 Leaf Area Calculation and Alignment 113 6.4.2 Stem (Branch) Design Process 116 6.4.3 Root (Link) Design Process 117 6.5 Interaction Design 118 6.5.1 Navigation 118 6.5.2 User Interface 119 6.5.3 Free and Detail Modes 120 6.5.4 Data Details 121 6.6 Visualization Renders 122 6.7 Exhibition 129 7. Conclusion 131 7.1 Conclusion 132 7.2 Limitations and Further Research 133 Bibliography 135 국문초록 (Abstract in Korean) 144Docto

Visualização de padrões temporais cíclicos em estudos de fenologia

Orientadores: Ricardo da Silva Torres, Leonor Patrícia Cerdeira MorellatoTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Em diversas aplicações, grandes volumes de dados multidimensionais têm sido gerados continuamente ao longo do tempo. Uma abordagem adequada para lidar com estas coleções consiste no uso de métodos de visualização de informação, a partir dos quais padrões de interesse podem ser identificados, possibilitando o entendimento de fenômenos temporais complexos. De fato, em diversos domínios, o desenvolvimento de ferramentas adequadas para apoiar análises complexas, por exemplo, aquelas baseadas na identificação de padrões de mudanças ou correlações existentes entre múltiplas variáveis ao longo do tempo é de suma importância. Em estudos de fenologia, por exemplo, especialistas observam as mudanças que ocorrem ao longo da vida de plantas e animais e investigam qual é a relação entre essas mudanças com variáveis ambientais. Neste cenário, especialistas em fenologia cada vez mais precisam de ferramentas para, adequadamente, visualizar séries temporais longas, com muitas variáveis e de diferentes tipos (por exemplo, texto e imagem), assim como identificar padrões temporais cíclicos. Embora diversas abordagens tenham sido propostas para visualizar dados que variam ao longo do tempo, muitas não são apropriadas ou aplicáveis para dados de fenologia, porque não são capazes de: (i) lidar com séries temporais longas, com muitas variáveis de diferentes tipos de dados e de uma ou mais dimensões; e (ii) permitir a identificação de padrões temporais cíclicos e drivers ambientais associados. Este trabalho aborda essas questões a partir da proposta de duas novas abordagens para apoiar a análise e visualização de dados temporais multidimensionais. Nossa primeira proposta combina estruturas visuais radiais com ritmos visuais. As estruturas radiais são usadas para fornecer informação contextual sobre fenômenos cíclicos, enquanto que o ritmo visual é usado para sumarizar séries temporais longas em representações compactas. Nós desenvolvemos, avaliamos e validamos nossa proposta com especialistas em fenologia em tarefas relacionadas à visualização de dados de observação direta da fenologia de plantas em nível tanto de indivíduos quanto de espécies. Nós também validamos a proposta usando dados temporais relacionados a imagens obtidas de sistemas de monitoramento de vegetação próxima à superfície. Nossa segunda abordagem é uma nova representação baseada em imagem, chamada Change Frequency Heatmap (CFH), usada para codificar mudanças temporais de dados numéricos multivariados. O método calcula histogramas de padrões de mudanças observados em sucessivos instantes de tempo. Nós validamos o uso do CFH a partir da criação de uma ferramenta de caracterização de mudanças no ciclo de vida de plantas de múltiplos indivíduos e espécies ao longo do tempo. Nós demonstramos o potencial do CFH para ajudar na identificação visual de padrões de mudanças temporais complexas, especialmente na identificação de variações entre indivíduos em estudos relacionados à fenologia de plantasAbstract: In several applications, large volumes of multidimensional data have been generated continuously over time. One suitable approach for handling those collections in a meaningful way consists in the use of information visualization methods, based on which patterns of interest can be identified, triggering the understanding of complex temporal phenomena. In fact, in several domains, the development of appropriate tools for supporting complex analysis based, for example, on the identification of change patterns in temporal data or existing correlations, over time, among multiple variables, is of paramount importance. In phenology studies, for instance, phenologists observe changes in the development of plants and animals throughout their lives and investigate what is the relationship between these changes with environmental changes. Therefore, phenologists increasingly need tools for visualizing appropriately long-term series with many variables of different data types, as well as for identifying cyclical temporal patterns. Although several approaches have been proposed to visualize data varying over time, most of them are not appropriate or applicable to phenology data, because they are not able: (i) to handle long-term series with many variables of different data types and one or more dimensions and (ii) to support the identification of cyclical temporal patterns and associated environmental drivers. This work addresses these shortcomings by presenting two new approaches to support the analysis and visualization of multidimensional temporal data. Our first proposal to visualize phenological data combines radial visual structures along with visual rhythms. Radial visual structures are used to provide contextual insights regarding cyclical phenomena, while the visual rhythm encoding is used to summarize long-term time series into compact representations. We developed, evaluated, and validated our proposal with phenology experts using plant phenology direct observational data both at individuals and species levels. Also we validated the proposal using image-related temporal data obtained from near-surface vegetation monitoring systems. Our second approach is a novel image-based representation, named Change Frequency Heatmap (CFH), used to encode temporal changes of multivariate numerical data. The method computes histograms of change patterns observed at successive timestamps. We validated the use of CFHs through the creation of a temporal change characterization tool to support complex plant phenology analysis, concerning the characterization of plant life cycle changes of multiple individuals and species over time. We demonstrated the potential of CFH to support visual identification of complex temporal change patterns, especially to decipher interindividual variations in plant phenologyDoutoradoCiência da ComputaçãoDoutora em Ciência da Computação162312/2015-62013/501550-0CNPQCAPESFAPES

Visualizing Set Relations and Cardinalities Using Venn and Euler Diagrams

In medicine, genetics, criminology and various other areas, Venn and Euler diagrams are used to visualize data set relations and their cardinalities. The data sets are represented by closed curves and the data set relationships are depicted by the overlaps between these curves. Both the sets and their intersections are easily visible as the closed curves are preattentively processed and form common regions that have a strong perceptual grouping effect. Besides set relations such as intersection, containment and disjointness, the cardinality of the sets and their intersections can also be depicted in the same diagram (referred to as area-proportional) through the size of the curves and their overlaps. Size is a preattentive feature and so similarities, differences and trends are easily identified. Thus, such diagrams facilitate data analysis and reasoning about the sets. However, drawing these diagrams manually is difficult, often impossible, and current automatic drawing methods do not always produce appropriate diagrams. This dissertation presents novel automatic drawing methods for different types of Euler diagrams and a user study of how such diagrams can help probabilistic judgement. The main drawing algorithms are: eulerForce, which uses a force-directed approach to lay out Euler diagrams; eulerAPE, which draws area-proportional Venn diagrams with ellipses. The user study evaluated the effectiveness of area- proportional Euler diagrams, glyph representations, Euler diagrams with glyphs and text+visualization formats for Bayesian reasoning, and a method eulerGlyphs was devised to automatically and accurately draw the assessed visualizations for any Bayesian problem. Additionally, analytic algorithms that instantaneously compute the overlapping areas of three general intersecting ellipses are provided, together with an evaluation of the effectiveness of ellipses in drawing accurate area-proportional Venn diagrams for 3-set data and the characteristics of the data that can be depicted accurately with ellipses

Multi-Modal Interfaces for Sensemaking of Graph-Connected Datasets

The visualization of hypothesized evolutionary processes is often shown through phylogenetic trees. Given evolutionary data presented in one of several widely accepted formats, software exists to render these data into a tree diagram. However, software packages commonly in use by biologists today often do not provide means to dynamically adjust and customize these diagrams for studying new hypothetical relationships, and for illustration and publication purposes. Even where these options are available, there can be a lack of intuitiveness and ease-of-use. The goal of our research is, thus, to investigate more natural and effective means of sensemaking of the data with different user input modalities. To this end, we experimented with different input modalities, designing and running a series of prototype studies, ultimately focusing our attention on pen-and-touch. Through several iterations of feedback and revision provided with the help of biology experts and students, we developed a pen-and-touch phylogenetic tree browsing and editing application called PhyloPen. This application expands on the capabilities of existing software with visualization techniques such as overview+detail, linked data views, and new interaction and manipulation techniques using pen-and-touch. To determine its impact on phylogenetic tree sensemaking, we conducted a within-subject comparative summative study against the most comparable and commonly used state-of-the-art mouse-based software system, Mesquite. Conducted with biology majors at the University of Central Florida, each used both software systems on a set number of exercise tasks of the same type. Determining effectiveness by several dependent measures, the results show PhyloPen was significantly better in terms of usefulness, satisfaction, ease-of-learning, ease-of-use, and cognitive load and relatively the same in variation of completion time. These results support an interaction paradigm that is superior to classic mouse-based interaction, which could have the potential to be applied to other communities that employ graph-based representations of their problem domains

LIPIcs, Volume 277, GIScience 2023, Complete Volume

LIPIcs, Volume 277, GIScience 2023, Complete Volum

Close and Distant Reading Visualizations for the Comparative Analysis of Digital Humanities Data

Traditionally, humanities scholars carrying out research on a specific or on multiple literary work(s) are interested in the analysis of related texts or text passages. But the digital age has opened possibilities for scholars to enhance their traditional workflows. Enabled by digitization projects, humanities scholars can nowadays reach a large number of digitized texts through web portals such as Google Books or Internet Archive. Digital editions exist also for ancient texts; notable examples are PHI Latin Texts and the Perseus Digital Library. This shift from reading a single book “on paper” to the possibility of browsing many digital texts is one of the origins and principal pillars of the digital humanities domain, which helps developing solutions to handle vast amounts of cultural heritage data – text being the main data type. In contrast to the traditional methods, the digital humanities allow to pose new research questions on cultural heritage datasets. Some of these questions can be answered with existent algorithms and tools provided by the computer science domain, but for other humanities questions scholars need to formulate new methods in collaboration with computer scientists. Developed in the late 1980s, the digital humanities primarily focused on designing standards to represent cultural heritage data such as the Text Encoding Initiative (TEI) for texts, and to aggregate, digitize and deliver data. In the last years, visualization techniques have gained more and more importance when it comes to analyzing data. For example, Saito introduced her 2010 digital humanities conference paper with: “In recent years, people have tended to be overwhelmed by a vast amount of information in various contexts. Therefore, arguments about ’Information Visualization’ as a method to make information easy to comprehend are more than understandable.” A major impulse for this trend was given by Franco Moretti. In 2005, he published the book “Graphs, Maps, Trees”, in which he proposes so-called distant reading approaches for textual data that steer the traditional way of approaching literature towards a completely new direction. Instead of reading texts in the traditional way – so-called close reading –, he invites to count, to graph and to map them. In other words, to visualize them. This dissertation presents novel close and distant reading visualization techniques for hitherto unsolved problems. Appropriate visualization techniques have been applied to support basic tasks, e.g., visualizing geospatial metadata to analyze the geographical distribution of cultural heritage data items or using tag clouds to illustrate textual statistics of a historical corpus. In contrast, this dissertation focuses on developing information visualization and visual analytics methods that support investigating research questions that require the comparative analysis of various digital humanities datasets. We first take a look at the state-of-the-art of existing close and distant reading visualizations that have been developed to support humanities scholars working with literary texts. We thereby provide a taxonomy of visualization methods applied to show various aspects of the underlying digital humanities data. We point out open challenges and we present our visualizations designed to support humanities scholars in comparatively analyzing historical datasets. In short, we present (1) GeoTemCo for the comparative visualization of geospatial-temporal data, (2) the two tag cloud designs TagPies and TagSpheres that comparatively visualize faceted textual summaries, (3) TextReuseGrid and TextReuseBrowser to explore re-used text passages among the texts of a corpus, (4) TRAViz for the visualization of textual variation between multiple text editions, and (5) the visual analytics system MusikerProfiling to detect similar musicians to a given musician of interest. Finally, we summarize our and the collaboration experiences of other visualization researchers to emphasize the ingredients required for a successful project in the digital humanities, and we take a look at future challenges in that research field

12th International Conference on Geographic Information Science: GIScience 2023, September 12–15, 2023, Leeds, UK

No abstract available

Proceedings of the 18th International Conference on Engineering Design (ICED11):Book of Abstracts

The ICED series of conferences is the Design Society's "flagship" event. ICED11 took place on August 15-18, 2011, at the campus of the Danish Technical University in Lyngby/Copenhagen, Denmark. The Proceedings of the conference are published in 10 individual volumes, arranged according to topics. All volumes of the Proceedings may be purchased individually through Amazon and other on-line booksellers. For members of the Design Society, all papers are available on this website. The Programme and Abstract Book is publically available for download