Visualizing multi-level structures in data
department or school: Science, Faculty of
department or school: Computer Science, Department of
data provider: DSpace
degree campus: UBCV
creator: Liu, Zipeng
issued: 2021-08-27T07:00:00Z
issued: 2021
related degree: Doctor of Philosophy - PhD
degree grantor: University of British Columbia
description: Visualization is an important tool to analyze data, but there emerge various challenges from complex analytical data and tasks. In this dissertation, I present four projects that were motivated by these challenges, situated in the nested model proposed by Munzner, which consists of four layers to describe the components in visualization: domain, data and task, encoding design, and algorithm. In ADVIEW, to address the challenges of comparing many phylogenetic trees in the domain of biology, I propose a visual encoding to compress a tree representation, design and implement a multi-view interactive tool to handle the multiple levels of detail in a tree collection dataset, ranging from the whole collection, through subsets of trees, individual trees, subtrees, to leaf nodes. In SPRAWLTER, to address the existing visual encoding problems of readability metrics for node-link graphs, I propose two novel metrics to measure a finer-grained clutter and to balance the geometric sparseness and clutter. These metrics recognize different levels of visual saliency such as metanodes and leaf nodes in multi-level graphs. In LOGSEG, to fulfill user demands for chunking actions in the domain of image editing software, I propose a segmentation model for the action logs to serve the demands that require different chunking granularities. For example, smart undo for going back to a previous user task needs a low-level chunking, while managing an overview of milestones needs a high-level one. In CORGIE, to fill the gap in visual qualitative evaluation of graph neural networks (GNNs) in the domain of machine learning, I propose an approach and design a tool to explore correspondences between a graph and its embedding to check how different levels of structures are preserved from the input graph to the output embedding. I also design a new graph layout to reveal how a GNN leverages node neighbors and computes an embedding. I identify a common theme among these projects: multi-level structur…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/79497
note: Visualizing Multi-level Structures in DatabyZipeng LiuBachelor of Science, Peking University, 2015A THESIS SUBMITTED IN PARTIAL FULFILLMENTOF THE REQUIREMENTS FOR THE DEGREE OFDoctor of PhilosophyinTHE FACULTY OF GRADUATE AND POSTDOCTORALSTUDIES(Computer Science)The University of British Columbia(Vancouver)August 2021© Zipeng Liu, 2021The following individuals certify that they have read, and recommend to the Fac-ulty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled:Visualizing Multi-level Structures in Datasubmitted by Zipeng Liu in partial fulfillment of the requirements for the degreeof Doctor of Philosophy in Computer Science.Supervisory Committee:Tamara Munzner, Computer ScienceSupervisorGiuseppe Carenini, Computer ScienceSupervisory Committee MemberMichiel van de Panne, Computer ScienceSupervisory Committee MemberExamining Committee Members:William Evans, Computer ScienceUniversity ExaminerSathish Gopalakrishnan, Electrical and Computer EngineeringUniversity ExaminerEnrico Bertini, Computer Science and Engineering, New York University TandonSchool of EngineeringExternal ExamineriiAbstractVisualization is an important tool to analyze data, but there emerge various chal-lenges from complex analytical data and tasks. In this dissertation, I present fourprojects that were motivated by these challenges, situated in the nested model pro-posed by Munzner, which consists of four layers to describe the components invisualization: domain, data and task, encoding design, and algorithm.In ADVIEW, to address the challenges of comparing many phylogenetic trees in thedomain of biology, I propose a visual encoding to compress a tree representation,design and implement a multi-view interactive tool to handle the multiple levelsof detail in a tree collection dataset, ranging from the whole collection, throughsubsets of trees, individual trees, subtrees, to leaf nodes. In SPRAWLTER, to addressthe existing visual encoding problems of readability metrics fo…
has type: Thesis/Dissertation
date issued: 2021-11
is shown at: 10.14288/1.0401773
language: eng
degree discipline: Computer Science
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Munzner, Tamara
type: Text
identifier URI: http://hdl.handle.net/2429/79497