Pub Date : 2013-09-12DOI: 10.1109/PacificVis.2013.6596149
Hans-Jörg Schulz, Z. Akbar, F. Maurer
In response to the large number of existing tree layouts, generic “meta-layouts” have recently been proposed. These generic approaches utilize layout design spaces to pinpoint a tree drawing with desired characteristics in the wealth of available drawing options and parameters. While design-space-based generic layouts work well for the confined set of implicit space-filling tree layouts, they have so far eluded their extension to explicit node-link diagrams. In order to produce both, implicit and explicit tree layouts, this paper parts with the descriptive nature of the design spaces and instead takes a generative approach based on operators. As these operators can be combined into operator sequences and be used at different stages of the layout process, a small operator set already suffices to yield a large number of different tree layouts. To this end, we present a generic tree layout pipeline and give examples of suitable layout operators to plug into the pipeline. A prototypical implementation of our pipeline and operators is presented, and it is illustrated with space-filling and node-link examples. Furthermore, the paper presents results from a user study evaluating our generative approach as it is realized by the prototype.
{"title":"A generative layout approach for rooted tree drawings","authors":"Hans-Jörg Schulz, Z. Akbar, F. Maurer","doi":"10.1109/PacificVis.2013.6596149","DOIUrl":"https://doi.org/10.1109/PacificVis.2013.6596149","url":null,"abstract":"In response to the large number of existing tree layouts, generic “meta-layouts” have recently been proposed. These generic approaches utilize layout design spaces to pinpoint a tree drawing with desired characteristics in the wealth of available drawing options and parameters. While design-space-based generic layouts work well for the confined set of implicit space-filling tree layouts, they have so far eluded their extension to explicit node-link diagrams. In order to produce both, implicit and explicit tree layouts, this paper parts with the descriptive nature of the design spaces and instead takes a generative approach based on operators. As these operators can be combined into operator sequences and be used at different stages of the layout process, a small operator set already suffices to yield a large number of different tree layouts. To this end, we present a generic tree layout pipeline and give examples of suitable layout operators to plug into the pipeline. A prototypical implementation of our pipeline and operators is presented, and it is illustrated with space-filling and node-link examples. Furthermore, the paper presents results from a user study evaluating our generative approach as it is realized by the prototype.","PeriodicalId":179865,"journal":{"name":"2013 IEEE Pacific Visualization Symposium (PacificVis)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134475979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-12DOI: 10.1109/PacificVis.2013.6596127
Ying Tu, Han-Wei Shen
Large scale semantic graphs such as social networks and knowledge graphs contain rich and useful information. However, due to combined challenges in scale, density, and heterogeneity, it is impractical for users to answer many interesting questions by visual inspection alone. This is because even a semantically simple question, such as which of my extended friends are also fans of my favorite band, can in fact require information from a non-trivial number of nodes to answer. In this paper, we propose a method that combines graph browsing with query to overcome the limitation of visual inspection. By using query as the main way for information discovery in graph exploration, our “query, expand, and query again” model enables users to probe beyond the visible part of the graph and only bring in the interesting nodes, leaving the view clutter-free. We have implemented a prototype called GraphCharter and demonstrated its effectiveness and usability in a case study and a user study on Freebase knowledge graph with millions of nodes and edges.
{"title":"GraphCharter: Combining browsing with query to explore large semantic graphs","authors":"Ying Tu, Han-Wei Shen","doi":"10.1109/PacificVis.2013.6596127","DOIUrl":"https://doi.org/10.1109/PacificVis.2013.6596127","url":null,"abstract":"Large scale semantic graphs such as social networks and knowledge graphs contain rich and useful information. However, due to combined challenges in scale, density, and heterogeneity, it is impractical for users to answer many interesting questions by visual inspection alone. This is because even a semantically simple question, such as which of my extended friends are also fans of my favorite band, can in fact require information from a non-trivial number of nodes to answer. In this paper, we propose a method that combines graph browsing with query to overcome the limitation of visual inspection. By using query as the main way for information discovery in graph exploration, our “query, expand, and query again” model enables users to probe beyond the visible part of the graph and only bring in the interesting nodes, leaving the view clutter-free. We have implemented a prototype called GraphCharter and demonstrated its effectiveness and usability in a case study and a user study on Freebase knowledge graph with millions of nodes and edges.","PeriodicalId":179865,"journal":{"name":"2013 IEEE Pacific Visualization Symposium (PacificVis)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133505278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-12DOI: 10.1109/PacificVis.2013.6596126
C. Hurter, O. Ersoy, A. Telea
Dynamic graphs are increasingly pervasive in modern information systems. However, understanding how a graph changes in time is difficult. We present here two techniques for simplified visualization of dynamic graphs using edge bundles. The first technique uses a recent image-based graph bundling method to create smoothly changing bundles from streaming graphs. The second technique incorporates additional edge-correspondence data and is thereby suited to visualize discrete graph sequences. We illustrate our methods with examples from real-world large dynamic graph datasets.
{"title":"Smooth bundling of large streaming and sequence graphs","authors":"C. Hurter, O. Ersoy, A. Telea","doi":"10.1109/PacificVis.2013.6596126","DOIUrl":"https://doi.org/10.1109/PacificVis.2013.6596126","url":null,"abstract":"Dynamic graphs are increasingly pervasive in modern information systems. However, understanding how a graph changes in time is difficult. We present here two techniques for simplified visualization of dynamic graphs using edge bundles. The first technique uses a recent image-based graph bundling method to create smoothly changing bundles from streaming graphs. The second technique incorporates additional edge-correspondence data and is thereby suited to visualize discrete graph sequences. We illustrate our methods with examples from real-world large dynamic graph datasets.","PeriodicalId":179865,"journal":{"name":"2013 IEEE Pacific Visualization Symposium (PacificVis)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123344578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-12DOI: 10.1109/PacificVis.2013.6596129
Hanqi Guo, Xiaoru Yuan
In this paper, we propose a novel volume visualization system enabling local transfer function specification through direct painting or sketching on the rendered image, in a WYSIWYG style. Localized transfer functions are defined on scalar topology regions specified by the user. Intelligent and fast feature inference algorithms have been developed to convert user's input to the region specification and to achieve desirable feature styles with the local transfer functions. In our system, users can not only manipulate the color appearance of the object volume, but also apply style transfer and generate various illustration styles with a unified input gesture. Without manual transfer function editing and without parameter specification, our system is capable of generating informative illustrations that intuitively highlight user specified local features.
{"title":"Local WYSIWYG volume visualization","authors":"Hanqi Guo, Xiaoru Yuan","doi":"10.1109/PacificVis.2013.6596129","DOIUrl":"https://doi.org/10.1109/PacificVis.2013.6596129","url":null,"abstract":"In this paper, we propose a novel volume visualization system enabling local transfer function specification through direct painting or sketching on the rendered image, in a WYSIWYG style. Localized transfer functions are defined on scalar topology regions specified by the user. Intelligent and fast feature inference algorithms have been developed to convert user's input to the region specification and to achieve desirable feature styles with the local transfer functions. In our system, users can not only manipulate the color appearance of the object volume, but also apply style transfer and generate various illustration styles with a unified input gesture. Without manual transfer function editing and without parameter specification, our system is capable of generating informative illustrations that intuitively highlight user specified local features.","PeriodicalId":179865,"journal":{"name":"2013 IEEE Pacific Visualization Symposium (PacificVis)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120813341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-12DOI: 10.1109/PacificVis.2013.6596123
Daichi Hirono, Hsiang-Yun Wu, M. Arikawa, Shigeo Takahashi
In composing hand-drawn 3D urban maps, the most common design problem is to avoid overlaps between geographic features such as roads and buildings by displacing them consistently over the map domain. Nonetheless, automating this map design process is still a challenging task because we have to maximally retain the 3D depth perception inherent in pairs of parallel lines embedded in the original layout of such geographic features. This paper presents a novel approach to disoccluding important geographic features when creating 3D urban maps for enhancing their visual readability. This is accomplished by formulating the design criteria as a constrained optimization problem based on the linear programming approach. Our mathematical formulation allows us to systematically eliminate occlusions of landmark roads and buildings, and further controls the degree of local 3D map deformation by devising an objective function to be minimized. Various design examples together with a user study are presented to demonstrate the robustness and feasibility of the proposed approach.
{"title":"Constrained optimization for disoccluding geographic landmarks in 3D urban maps","authors":"Daichi Hirono, Hsiang-Yun Wu, M. Arikawa, Shigeo Takahashi","doi":"10.1109/PacificVis.2013.6596123","DOIUrl":"https://doi.org/10.1109/PacificVis.2013.6596123","url":null,"abstract":"In composing hand-drawn 3D urban maps, the most common design problem is to avoid overlaps between geographic features such as roads and buildings by displacing them consistently over the map domain. Nonetheless, automating this map design process is still a challenging task because we have to maximally retain the 3D depth perception inherent in pairs of parallel lines embedded in the original layout of such geographic features. This paper presents a novel approach to disoccluding important geographic features when creating 3D urban maps for enhancing their visual readability. This is accomplished by formulating the design criteria as a constrained optimization problem based on the linear programming approach. Our mathematical formulation allows us to systematically eliminate occlusions of landmark roads and buildings, and further controls the degree of local 3D map deformation by devising an objective function to be minimized. Various design examples together with a user study are presented to demonstrate the robustness and feasibility of the proposed approach.","PeriodicalId":179865,"journal":{"name":"2013 IEEE Pacific Visualization Symposium (PacificVis)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116310762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-12DOI: 10.1109/PacificVis.2013.6596125
S. V. D. Elzen, Danny Holten, Jorik Blaas, J. V. Wijk
Networks are present in many fields such as finance, sociology, and transportation. Often these networks are dynamic: they have a structural as well as a temporal aspect. We present a technique that extends the Massive Sequence View (MSV) for the analysis of the temporal and structural aspects of dynamic networks. Using features in the data as well as in the visualization based on the Gestalt principles closure, proximity, and similarity, we developed node reordering strategies for the MSV to make these features stand out. This enables users to find temporal properties such as trends, counter trends, periodicity, temporal shifts, and anomalies in the network as well as structural properties such as communities and stars. We show the effectiveness of the reordering methods on both synthetic and real-world transaction data sets.
{"title":"Reordering Massive Sequence Views: Enabling temporal and structural analysis of dynamic networks","authors":"S. V. D. Elzen, Danny Holten, Jorik Blaas, J. V. Wijk","doi":"10.1109/PacificVis.2013.6596125","DOIUrl":"https://doi.org/10.1109/PacificVis.2013.6596125","url":null,"abstract":"Networks are present in many fields such as finance, sociology, and transportation. Often these networks are dynamic: they have a structural as well as a temporal aspect. We present a technique that extends the Massive Sequence View (MSV) for the analysis of the temporal and structural aspects of dynamic networks. Using features in the data as well as in the visualization based on the Gestalt principles closure, proximity, and similarity, we developed node reordering strategies for the MSV to make these features stand out. This enables users to find temporal properties such as trends, counter trends, periodicity, temporal shifts, and anomalies in the network as well as structural properties such as communities and stars. We show the effectiveness of the reordering methods on both synthetic and real-world transaction data sets.","PeriodicalId":179865,"journal":{"name":"2013 IEEE Pacific Visualization Symposium (PacificVis)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128955905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-12DOI: 10.1109/PACIFICVIS.2013.6596141
H. Carr, D. Duke
Contour trees and Reeb graphs are firmly embedded in scientific visualization for analysing univariate (scalar) fields. We generalize this analysis to multivariate fields with a data structure called the Joint Contour Net that quantizes the variation of multiple variables simultaneously. We report the first algorithm for constructing the Joint Contour Net and demonstrate that Contour Trees for individual variables can be extracted from the Joint Contour Net.
{"title":"Joint Contour Nets: Computation and properties","authors":"H. Carr, D. Duke","doi":"10.1109/PACIFICVIS.2013.6596141","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2013.6596141","url":null,"abstract":"Contour trees and Reeb graphs are firmly embedded in scientific visualization for analysing univariate (scalar) fields. We generalize this analysis to multivariate fields with a data structure called the Joint Contour Net that quantizes the variation of multiple variables simultaneously. We report the first algorithm for constructing the Joint Contour Net and demonstrate that Contour Trees for individual variables can be extracted from the Joint Contour Net.","PeriodicalId":179865,"journal":{"name":"2013 IEEE Pacific Visualization Symposium (PacificVis)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122707334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-12DOI: 10.1109/PacificVis.2013.6596145
S. Barlowe, Jing Yang, D. Jacobs, D. Livesay, J. Alsakran, Ye Zhao, Deeptak Verma, J. Mottonen
Understanding what causes proteins to change shape and how the resulting shape influences function will expedite the design of more narrowly focused drugs and therapies. Shape alterations are often the result of flexibility changes in a set of localized neighborhoods that may or may not act in concert. Computational models have been developed to predict flexibility changes under varying empirical parameters. In this paper, we tackle a significant challenge facing scientists when analyzing outputs of a computational model, namely how to identify, examine, compare, and group interesting neighborhoods of proteins under different parameter sets. This is a difficult task since comparisons over protein subunits that comprise diverse neighborhoods are often too complex to characterize with a simple metric and too numerous to analyze manually. Here, we present a series of novel visual analytics approaches toward addressing this task. User scenarios illustrate the utility of these approaches and feedback from domain experts confirms their effectiveness.
{"title":"A visual analytics approach to exploring protein flexibility subspaces","authors":"S. Barlowe, Jing Yang, D. Jacobs, D. Livesay, J. Alsakran, Ye Zhao, Deeptak Verma, J. Mottonen","doi":"10.1109/PacificVis.2013.6596145","DOIUrl":"https://doi.org/10.1109/PacificVis.2013.6596145","url":null,"abstract":"Understanding what causes proteins to change shape and how the resulting shape influences function will expedite the design of more narrowly focused drugs and therapies. Shape alterations are often the result of flexibility changes in a set of localized neighborhoods that may or may not act in concert. Computational models have been developed to predict flexibility changes under varying empirical parameters. In this paper, we tackle a significant challenge facing scientists when analyzing outputs of a computational model, namely how to identify, examine, compare, and group interesting neighborhoods of proteins under different parameter sets. This is a difficult task since comparisons over protein subunits that comprise diverse neighborhoods are often too complex to characterize with a simple metric and too numerous to analyze manually. Here, we present a series of novel visual analytics approaches toward addressing this task. User scenarios illustrate the utility of these approaches and feedback from domain experts confirms their effectiveness.","PeriodicalId":179865,"journal":{"name":"2013 IEEE Pacific Visualization Symposium (PacificVis)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130737083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-12DOI: 10.1109/PacificVis.2013.6596137
Silvia Born, M. Markl, M. Gutberlet, G. Scheuermann
In the last years, illustrative methods have found their way into flow visualization since they communicate difficult information in a comprehensible way. This is of great benefit especially in domains where the audience does not necessarily have flow expertise. One such domain is the medical field where the development of 4D MR imaging (for in-vivo 3D blood flow measurement) lead to an increased demand for easy flow analysis techniques. The goal and the challenge is to transfer the data into simple visualizations supporting the physician with flow interpretation and decision making. In this work, we take one step towards this goal. We present an approach for the illustrative visualization of steady flow features occurring in 4D MRI data of heart and aorta. Like shown in manually created illustrations, we restrict our visualization to the main data characteristics and do not depict every flow detail. The input for our method are flow features extracted from a dataset's complete set of streamlines with the help of line predicates. We create an abstract depiction of these line bundles by selecting a set of bundle representatives reflecting the most important flow aspects. These lines are rendered as three-dimensional arrows that are fused in areas where they represent the same flow. Since vortices are another important flow information for a physician, we identify these regions in the 4D MRI data and display them as unobtrusive, tube-like structures. A hatching texture provides for a visual effect of rotational blood flow. By applying our illustration technique to diverse flow structures of several 4D MRI datasets, we demonstrate that the abstract visualization is useful to gain an easier insight into the data. Feedback of medical experts confirmed the usefulness and revealed limitations of our work. The images are restricted to the essential flow features and, therefore, clearer and less cluttered. Our method has great potential and offers many possible applications, e.g., in comparative visualization and also beyond the medical domain.
{"title":"Illustrative visualization of cardiac and aortic blood flow from 4D MRI data","authors":"Silvia Born, M. Markl, M. Gutberlet, G. Scheuermann","doi":"10.1109/PacificVis.2013.6596137","DOIUrl":"https://doi.org/10.1109/PacificVis.2013.6596137","url":null,"abstract":"In the last years, illustrative methods have found their way into flow visualization since they communicate difficult information in a comprehensible way. This is of great benefit especially in domains where the audience does not necessarily have flow expertise. One such domain is the medical field where the development of 4D MR imaging (for in-vivo 3D blood flow measurement) lead to an increased demand for easy flow analysis techniques. The goal and the challenge is to transfer the data into simple visualizations supporting the physician with flow interpretation and decision making. In this work, we take one step towards this goal. We present an approach for the illustrative visualization of steady flow features occurring in 4D MRI data of heart and aorta. Like shown in manually created illustrations, we restrict our visualization to the main data characteristics and do not depict every flow detail. The input for our method are flow features extracted from a dataset's complete set of streamlines with the help of line predicates. We create an abstract depiction of these line bundles by selecting a set of bundle representatives reflecting the most important flow aspects. These lines are rendered as three-dimensional arrows that are fused in areas where they represent the same flow. Since vortices are another important flow information for a physician, we identify these regions in the 4D MRI data and display them as unobtrusive, tube-like structures. A hatching texture provides for a visual effect of rotational blood flow. By applying our illustration technique to diverse flow structures of several 4D MRI datasets, we demonstrate that the abstract visualization is useful to gain an easier insight into the data. Feedback of medical experts confirmed the usefulness and revealed limitations of our work. The images are restricted to the essential flow features and, therefore, clearer and less cluttered. Our method has great potential and offers many possible applications, e.g., in comparative visualization and also beyond the medical domain.","PeriodicalId":179865,"journal":{"name":"2013 IEEE Pacific Visualization Symposium (PacificVis)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132730583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-12DOI: 10.1109/PacificVis.2013.6596138
Yi Gu, Chaoli Wang
Significant advances have been made in time-varying data analysis and visualization, mainly in improving our ability to identify temporal trends and classify the underlying data. However, the ability to perform cost-effective data querying and indexing is often not incorporated, which posts a serious limitation as the size of time-varying data continue to grow. In this paper, we present a new approach that unifies data compacting, indexing and classification into a single framework. We achieve this by transforming the time-activity curve representation of a time-varying data set into a hierarchical symbolic representation. We further build an indexable version of the data hierarchy, from which we create the iTree for visual representation of the time-varying data. A hyperbolic layout algorithm is employed to draw the iTree with a large number of nodes and provide focus+context visualization for interaction. We achieve effective querying, searching and tracking of time-varying data sets by enabling multiple coordinated views consisting of the iTree, the symbolic view and the spatial view.
{"title":"iTree: Exploring time-varying data using indexable tree","authors":"Yi Gu, Chaoli Wang","doi":"10.1109/PacificVis.2013.6596138","DOIUrl":"https://doi.org/10.1109/PacificVis.2013.6596138","url":null,"abstract":"Significant advances have been made in time-varying data analysis and visualization, mainly in improving our ability to identify temporal trends and classify the underlying data. However, the ability to perform cost-effective data querying and indexing is often not incorporated, which posts a serious limitation as the size of time-varying data continue to grow. In this paper, we present a new approach that unifies data compacting, indexing and classification into a single framework. We achieve this by transforming the time-activity curve representation of a time-varying data set into a hierarchical symbolic representation. We further build an indexable version of the data hierarchy, from which we create the iTree for visual representation of the time-varying data. A hyperbolic layout algorithm is employed to draw the iTree with a large number of nodes and provide focus+context visualization for interaction. We achieve effective querying, searching and tracking of time-varying data sets by enabling multiple coordinated views consisting of the iTree, the symbolic view and the spatial view.","PeriodicalId":179865,"journal":{"name":"2013 IEEE Pacific Visualization Symposium (PacificVis)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116617882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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