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DimStiller: Workflows for dimensional analysis and reduction
"... DimStiller is a system for dimensionality reduction and analysis. It frames the task of understanding and transforming input dimensions as a series of analysis steps where users transform data tables by chaining together different techniques, called operators, into pipelines of expressions. The indi ..."
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Cited by 19 (5 self)
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DimStiller is a system for dimensionality reduction and analysis. It frames the task of understanding and transforming input dimensions as a series of analysis steps where users transform data tables by chaining together different techniques, called operators, into pipelines of expressions. The individual operators have controls and views that are linked together based on the structure of the expression. Users interact with the operator controls to tune parameter choices, with immediate visual feedback guiding the exploration of local neighborhoods of the space of possible data tables. DimStiller also provides global guidance for navigating data-table space through expression templates called workflows, which permit re-use of common patterns of analysis. 1
Steerable, Progressive Multidimensional Scaling
"... Current implementations of Multidimensional Scaling (MDS), an approach that attempts to best represent data point similarity in a low-dimensional representation, are not suited for many of today’s large-scale datasets. We propose an extension to the spring model approach that allows the user to int ..."
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Cited by 16 (1 self)
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Current implementations of Multidimensional Scaling (MDS), an approach that attempts to best represent data point similarity in a low-dimensional representation, are not suited for many of today’s large-scale datasets. We propose an extension to the spring model approach that allows the user to interactively explore datasets that are far beyond the scale of previous implementations of MDS. We present MDSteer, a steerable MDS computation engine and visualization tool that progressively computes an MDS layout and handles datasets of over one million points. Our technique employs hierarchical data structures and progressive layouts to allow the user to steer the computation of the algorithm to the interesting areas of the dataset. The algorithm iteratively alternates between a layout stage in which a sub-selection of points are added to the set of active points affected by the MDS iteration, and a binning stage which increases the depth of the bin hierarchy and organizes the currently unplaced points into separate spatial regions. This binning strategy allows the user to select onscreen regions of the layout to focus the MDS computation into the areas of the dataset that are assigned to the selected bins. We show both real and common synthetic benchmark datasets with dimensionalities ranging from 3 to 300 and cardinalities of over one million points.
A visual workspace for constructing hybrid multidimensional scaling algorithms and coordinating multiple views
- Information Visualization
, 2003
"... Data can be distinguished according to volume, variable types and distribution, and each of these characteristics imposes constraints upon the choice of applicable algorithms for their visualisation. This has led to an abundance of often disparate algorithmic techniques. Previous work has shown that ..."
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Cited by 10 (4 self)
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Data can be distinguished according to volume, variable types and distribution, and each of these characteristics imposes constraints upon the choice of applicable algorithms for their visualisation. This has led to an abundance of often disparate algorithmic techniques. Previous work has shown that a hybrid algorithmic approach can be successful in addressing the impact of data volume on the feasibility of multidimensional scaling (MDS). This paper presents a system and framework in which a user can easily explore algorithms as well as their hybrid conjunctions and the data flowing through them. Visual programming and a novel algorithmic architecture let the user semi–automatically define data flows and the co-ordination of multiple views of algorithmic and visualisation components. We propose that our approach has two main benefits: significant improvements in run times of MDS algorithms can be achieved, and intermediate views of the data and the visualisation program structure can provide greater insight and control over the visualisation process.
A Pivot-Based Routine for Improved Parent-Finding in Hybrid MDS
, 2004
"... The problem of exploring or visualising data of high dimensionality is central to many tools for information visualisation. Through representing a data set in terms of inter-object proximities, multidimensional scaling may be employed to generate a configuration of objects in low-dimensional space i ..."
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Cited by 10 (0 self)
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The problem of exploring or visualising data of high dimensionality is central to many tools for information visualisation. Through representing a data set in terms of inter-object proximities, multidimensional scaling may be employed to generate a configuration of objects in low-dimensional space in such a way as to preserve high-dimensional relationships. An algorithm is presented here for a heuristic hybrid model for the generation of such configurations. Building on a model introduced in 2002, the algorithm functions by means of sampling, spring model and interpolation phases. The most
Reflections on QuestVis: A Visualization System for an Environmental Sustainability Model. UBC Computer Science
"... We present lessons learned from the iterative design of QuestVis, a visualization interface for the QUEST environmental sustainability model. The QUEST model predicts the effects of policy choices in the present using scenarios of future outcomes that consist of several hundred indicators. QuestVis ..."
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Cited by 9 (5 self)
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We present lessons learned from the iterative design of QuestVis, a visualization interface for the QUEST environmental sustainability model. The QUEST model predicts the effects of policy choices in the present using scenarios of future outcomes that consist of several hundred indicators. QuestVis treats this information as a high-dimensional dataset, and shows the relationship between input choices and output indicators using linked views and a compact multilevel browser for indicator values. A first prototype also featured an overview of the space of all possible scenarios based on dimensionality reduction, but this representation was deemed to be be inappropriate for a target audience of people unfamiliar with data analysis. A second prototype with a considerably simplified and streamlined interface was created that supported comparison between multiple scenarios using a flexible approach to aggregation. However, QuestVis was not deployed because of a mismatch between the design goals of the project and the true needs of the target user community, who did not need to carry out detailed analysis of the high-dimensional dataset. We discuss this breakdown in the context of a nested model for visualization design and evaluation.
A survey of visualization construction user interfaces
- In EuroVis-Short Papers
"... We have systematically surveyed the publications on visualization construction user interfaces that have been published in 12 major Visualization and HCI venues. We found six different visualization construction approaches (visual builder, visualization spreadsheet, textual programming, visual dataf ..."
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Cited by 9 (0 self)
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We have systematically surveyed the publications on visualization construction user interfaces that have been published in 12 major Visualization and HCI venues. We found six different visualization construction approaches (visual builder, visualization spreadsheet, textual programming, visual dataflow programming, template editor, and shelf configuration). The approaches differ in their flexibility, whether they support presentation or exploration tasks, and the spatial, temporal, and conceptual distance between the user interface (UI) and the visualization. Our results provide guidance to designers of visualization construction UIs.
Aid Co-ordination
- Public Administration and Development
, 1990
"... A visual workspace for constructing hybrid ..."
QuestVis and MDSteer: The visualization of high-dimensional environmental sustainability data
, 2004
"... The visualization of large high-dimensional datasets is an active topic within the research area of information visualization (infovis), a research area that studies the visual representations of complex abstract datasets. My thesis presents two infovis systems that were motivated by the desire to e ..."
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The visualization of large high-dimensional datasets is an active topic within the research area of information visualization (infovis), a research area that studies the visual representations of complex abstract datasets. My thesis presents two infovis systems that were motivated by the desire to explore a 294-dimensional environmental sustainability dataset. Our collaborators developed the environmental dataset from expert knowledge on ecological, economical, and social systems which were used to model future scenarios consisting of 294 measures of environmental sustainability such as urban population, water supply levels, or tonnes of waste. Since these complex systems and large datasets are difficult for a non-expert user to comprehend, we developed QuestVis, a tool that applies infovis theories and techniques to improve the comprehensibility during exploration of the environmental dataset. The tool consists of three components: the input panel, the Multiscale Dimension Visualizer (MDV), and the Scenario Space Explorer (SSE). The MDV presents up to ten 294-dimensional future scenarios simultaneously on the screen to enable users
User Interfaces Supporting Information Visualization Novices in Visualization Construction
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STUDIES
, 2013
"... c ○ Stephen Ingram, 2013ing. To address the case of costly distances, we develop an algorithm framework, Glint, which efficiently manages the number of distance function calculations for the Multidimensional Scaling class of DR algorithms. We then show that Glint implementations of Multidimensional ..."
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c ○ Stephen Ingram, 2013ing. To address the case of costly distances, we develop an algorithm framework, Glint, which efficiently manages the number of distance function calculations for the Multidimensional Scaling class of DR algorithms. We then show that Glint implementations of Multidimensional Scaling algorithms achieve substantial speed improvements or remove the need for human monitoring. iii Preface Parts of this thesis have appeared in publications and journal submissions. Most of Chapter 3 is based on the following published conference paper:
