Self-Organized Sociopolitical Interactions as the Best Way to Achieve Organized Patterns in Human Social Systems: Going Beyond the Top-Down Control of Classical Political Regimes

The dissertation extrapolates the theory of self-organization in biological organisms to sociopolitical self-organization, in human social systems. It is stated that the latter is the best way to organize human social systems, given their complex nature and the impossibility of the computational dynamics that classical political regimes must perform in order to, unsuccesfully, try to organize human social systems by means of top-down control. Sociopolitical self-organization is presented as the optimal producer of order in human social systems, and it is claimed that anarchic complex networks are the resulting structures.Comment: Originally published in: Repository, Universidad del Rosario Link: http://repository.urosario.edu.co/handle/10336/4387 (2013

iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu

Refinamiento de los algoritmos de dimensionado y posicionamiento de nodos en árboles de conos

En el presente artículo se estudiaron con detalle los algoritmos de posicionamiento, dimensionado y rotación dinámica de conos actualmente conocidos en árboles de conos. Se realiza un análisis orientado a refinar los algoritmos, entender su entorno y mejorar su eficiencia desde el punto de vista de tiempo de ejecución así como la necesidad y posibilidad de que se presenten choques entre los subárboles. Se ofrece también una mejora al algoritmo base para disminuir los casos en que se presentan estos choques

Explorative Graph Visualization

Netzwerkstrukturen (Graphen) sind heutzutage weit verbreitet. Ihre Untersuchung dient dazu, ein besseres Verständnis ihrer Struktur und der durch sie modellierten realen Aspekte zu gewinnen. Die Exploration solcher Netzwerke wird zumeist mit Visualisierungstechniken unterstützt. Ziel dieser Arbeit ist es, einen Überblick über die Probleme dieser Visualisierungen zu geben und konkrete Lösungsansätze aufzuzeigen. Dabei werden neue Visualisierungstechniken eingeführt, um den Nutzen der geführten Diskussion für die explorative Graphvisualisierung am konkreten Beispiel zu belegen.Network structures (graphs) have become a natural part of everyday life and their analysis helps to gain an understanding of their inherent structure and the real-world aspects thereby expressed. The exploration of graphs is largely supported and driven by visual means. The aim of this thesis is to give a comprehensive view on the problems associated with these visual means and to detail concrete solution approaches for them. Concrete visualization techniques are introduced to underline the value of this comprehensive discussion for supporting explorative graph visualization

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

ScaleTrotter: Illustrative Visual Travels Across Negative Scales

We present ScaleTrotter, a conceptual framework for an interactive, multi-scale visualization of biological mesoscale data and, specifically, genome data. ScaleTrotter allows viewers to smoothly transition from the nucleus of a cell to the atomistic composition of the DNA, while bridging several orders of magnitude in scale. The challenges in creating an interactive visualization of genome data are fundamentally different in several ways from those in other domains like astronomy that require a multi-scale representation as well. First, genome data has intertwined scale levels---the DNA is an extremely long, connected molecule that manifests itself at all scale levels. Second, elements of the DNA do not disappear as one zooms out---instead the scale levels at which they are observed group these elements differently. Third, we have detailed information and thus geometry for the entire dataset and for all scale levels, posing a challenge for interactive visual exploration. Finally, the conceptual scale levels for genome data are close in scale space, requiring us to find ways to visually embed a smaller scale into a coarser one. We address these challenges by creating a new multi-scale visualization concept. We use a scale-dependent camera model that controls the visual embedding of the scales into their respective parents, the rendering of a subset of the scale hierarchy, and the location, size, and scope of the view. In traversing the scales, ScaleTrotter is roaming between 2D and 3D visual representations that are depicted in integrated visuals. We discuss, specifically, how this form of multi-scale visualization follows from the specific characteristics of the genome data and describe its implementation. Finally, we discuss the implications of our work to the general illustrative depiction of multi-scale data