DevLan/vispubs huggingface dataset:
Visual opinion analysis of customer feedback data
Authors: Daniela Oelke, Ming C. Hao, Christian Rohrdantz, Daniel A. Keim, Umeshwar Dayal, Lars-Erik Haug, Halldór Janetzko
Published at VAST, 2009

Today, online stores collect a lot of customer feedback in the form of surveys, reviews, and comments. This feedback is categorized and in some cases responded to, but in general it is underutilized - even though customer satisfaction is essential to the success of their business. In this paper, we introduce several new techniques to interactively analyze customer comments and ratings to determine the positive and negative opinions expressed by the customers. First, we introduce a new discrimination-based technique to automatically extract the terms that are the subject of the positive or negative opinion (such as price or customer service) and that are frequently commented on. Second, we derive a Reverse-Distance-Weighting method to map the attributes to the related positive and negative opinions in the text. Third, the resulting high-dimensional feature vectors are visualized in a new summary representation that provides a quick overview. We also cluster the reviews according to the similarity of the comments. Special thumbnails are used to provide insight into the composition of the clusters and their relationship. In addition, an interactive circular correlation map is provided to allow analysts to detect the relationships of the comments to other important attributes and the scores. We have applied these techniques to customer comments from real-world online stores and product reviews from web sites to identify the strength and problems of different products and services, and show the potential of our technique.
Visualization of uncertainty and analysis of geographical data
Authors: Jo Wood, Aidan Slingsby, Naz Khalili-Shavarini, Jason Dykes, David M. Mountain
Published at VAST, 2009

A team of five worked on this challenge to identify a possible criminal structure within the Flitter social network. Initially we worked on the problem individually, deliberately not sharing any data, results or conclusions. This maximised the chances of spotting any blunders, unjustified assumptions or inferences and allowed us to triangulate any common conclusions. After an agreed period we shared our results demonstrating the visualization applications we had built and the reasoning behind our conclusions. This sharing of assumptions encouraged us to incorporate uncertainty in our visualization approaches as it became clear that there was a number of possible interpretations of the rules and assumptions governing the challenge. This summary of the work emphasises one of those applications detailing the geographic analysis and uncertainty handling of the network data.
Visualized subgraph search
Authors: Dóra Erdös, Zsolt Fekete, András Lukács
Published at VAST, 2009

We present a visually supported search and browsing system for network-type data, especially a novel module for subgraph search with a GUI to define subgraphs for queries. We describe how this prototype was applied for the Vast Challenge 2009, Flitter Mini Challenge.
What's being said near "Martha"? Exploring name entities in literary text collections
Authors: Romain Vuillemot, Tanya E. Clement, Catherine Plaisant, Amit Kumar
Published at VAST, 2009

A common task in literary analysis is to study characters in a novel or collection. Automatic entity extraction, text analysis and effective user interfaces facilitate character analysis. Using our interface, called POSvis, the scholar uses word clouds and self-organizing graphs to review vocabulary, to filter by part of speech, and to explore the network of characters located near characters under review. Further, visualizations show word usages within an analysis window (i.e. a book chapter), which can be compared with a reference window (i.e. the whole book). We describe the interface and report on an early case study with a humanities scholar.
Working memory load as a novel tool for evaluating visual analytics
Authors: Courtney C. Dornburg, Laura E. Matzen, Travis L. Bauer, Laura A. McNamara
Published at VAST, 2009

The current visual analytics literature highlights design and evaluation processes that are highly variable and situation dependent, which raises at least two broad challenges. First, lack of a standardized evaluation criterion leads to costly re-designs for each task and specific user community. Second, this inadequacy in criterion validation raises significant uncertainty regarding visualization outputs and their related decisions, which may be especially troubling in high consequence environments like those of the intelligence community. As an attempt to standardize the ldquoapples and orangesrdquo of the extant situation, we propose the creation of standardized evaluation tools using general principles of human cognition. Theoretically, visual analytics enables the user to see information in a way that should attenuate the user's memory load and increase the user's task-available cognitive resources. By using general cognitive abilities like available working memory resources as our dependent measures, we propose to develop standardized evaluative capabilities that can be generalized across contexts, tasks, and user communities.
"Search, Show Context, Expand on Demand": Supporting Large Graph Exploration with Degree-of-Interest
Authors: Frank van Ham, Adam Perer
Published at InfoVis, 2009

A common goal in graph visualization research is the design of novel techniques for displaying an overview of an entire graph. However, there are many situations where such an overview is not relevant or practical for users, as analyzing the global structure may not be related to the main task of the users that have semi-specific information needs. Furthermore, users accessing large graph databases through an online connection or users running on less powerful (mobile) hardware simply do not have the resources needed to compute these overviews. In this paper, we advocate an interaction model that allows users to remotely browse the immediate context graph around a specific node of interest. We show how Furnas' original degree of interest function can be adapted from trees to graphs and how we can use this metric to extract useful contextual subgraphs, control the complexity of the generated visualization and direct users to interesting datapoints in the context. We demonstrate the effectiveness of our approach with an exploration of a dense online database containing over 3 million legal citations.
A Comparison of User-Generated and Automatic Graph Layouts
Authors: Tim Dwyer, Bongshin Lee, Danyel Fisher, Kori Inkpen Quinn, Petra Isenberg, George G. Robertson, Chris North 0001
Published at InfoVis, 2009

The research presented in this paper compares user-generated and automatic graph layouts. Following the methods suggested by van Ham et al. (2008), a group of users generated graph layouts using both multi-touch interaction on a tabletop display and mouse interaction on a desktop computer. Users were asked to optimize their layout for aesthetics and analytical tasks with a social network. We discuss characteristics of the user-generated layouts and interaction methods employed by users in this process. We then report on a web-based study to compare these layouts with the output of popular automatic layout algorithms. Our results demonstrate that the best of the user-generated layouts performed as well as or better than the physics-based layout. Orthogonal and circular automatic layouts were found to be considerably less effective than either the physics-based layout or the best of the user-generated layouts. We highlight several attributes of the various layouts that led to high accuracy and improved task completion time, as well as aspects in which traditional automatic layout methods were unsuccessful for our tasks.
A Multi-Threading Architecture to Support Interactive Visual Exploration
Authors: Harald Piringer, Christian Tominski, Philipp Muigg, Wolfgang Berger
Published at InfoVis, 2009

During continuous user interaction, it is hard to provide rich visual feedback at interactive rates for datasets containing millions of entries. The contribution of this paper is a generic architecture that ensures responsiveness of the application even when dealing with large data and that is applicable to most types of information visualizations. Our architecture builds on the separation of the main application thread and the visualization thread, which can be cancelled early due to user interaction. In combination with a layer mechanism, our architecture facilitates generating previews incrementally to provide rich visual feedback quickly. To help avoiding common pitfalls of multi-threading, we discuss synchronization and communication in detail. We explicitly denote design choices to control trade-offs. A quantitative evaluation based on the system VI S P L ORE shows fast visual feedback during continuous interaction even for millions of entries. We describe instantiations of our architecture in additional tools.
A Nested Model for Visualization Design and Validation
Authors: Tamara Munzner
Published at InfoVis, 2009

We present a nested model for the visualization design and validation with four layers: characterize the task and data in the vocabulary of the problem domain, abstract into operations and data types, design visual encoding and interaction techniques, and create algorithms to execute techniques efficiently. The output from a level above is input to the level below, bringing attention to the design challenge that an upstream error inevitably cascades to all downstream levels. This model provides prescriptive guidance for determining appropriate evaluation approaches by identifying threats to validity unique to each level. We also provide three recommendations motivated by this model: authors should distinguish between these levels when claiming contributions at more than one of them, authors should explicitly state upstream assumptions at levels above the focus of a paper, and visualization venues should accept more papers on domain characterization.
ABySS-Explorer: Visualizing Genome Sequence Assemblies
Authors: Cydney B. Nielsen, Shaun D. Jackman, Inanç Birol, Steven J. M. Jones
Published at InfoVis, 2009

One bottleneck in large-scale genome sequencing projects is reconstructing the full genome sequence from the short subsequences produced by current technologies. The final stages of the genome assembly process inevitably require manual inspection of data inconsistencies and could be greatly aided by visualization. This paper presents our design decisions in translating key data features identified through discussions with analysts into a concise visual encoding. Current visualization tools in this domain focus on local sequence errors making high-level inspection of the assembly difficult if not impossible. We present a novel interactive graph display, ABySS-Explorer, that emphasizes the global assembly structure while also integrating salient data features such as sequence length. Our tool replaces manual and in some cases pen-and-paper based analysis tasks, and we discuss how user feedback was incorporated into iterative design refinements. Finally, we touch on applications of this representation not initially considered in our design phase, suggesting the generality of this encoding for DNA sequence data.
ActiviTree: Interactive Visual Exploration of Sequences in Event-Based Data Using Graph Similarity
Authors: Katerina Vrotsou, Jimmy Johansson 0001, Matthew Cooper 0001
Published at InfoVis, 2009

The identification of significant sequences in large and complex event-based temporal data is a challenging problem with applications in many areas of today's information intensive society. Pure visual representations can be used for the analysis, but are constrained to small data sets. Algorithmic search mechanisms used for larger data sets become expensive as the data size increases and typically focus on frequency of occurrence to reduce the computational complexity, often overlooking important infrequent sequences and outliers. In this paper we introduce an interactive visual data mining approach based on an adaptation of techniques developed for Web searching, combined with an intuitive visual interface, to facilitate user-centred exploration of the data and identification of sequences significant to that user. The search algorithm used in the exploration executes in negligible time, even for large data, and so no pre-processing of the selected data is required, making this a completely interactive experience for the user. Our particular application area is social science diary data but the technique is applicable across many other disciplines.
Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations
Authors: Christopher Collins 0001, Gerald Penn, Sheelagh Carpendale
Published at InfoVis, 2009

While many data sets contain multiple relationships, depicting more than one data relationship within a single visualization is challenging. We introduce Bubble Sets as a visualization technique for data that has both a primary data relation with a semantically significant spatial organization and a significant set membership relation in which members of the same set are not necessarily adjacent in the primary layout. In order to maintain the spatial rights of the primary data relation, we avoid layout adjustment techniques that improve set cluster continuity and density. Instead, we use a continuous, possibly concave, isocontour to delineate set membership, without disrupting the primary layout. Optimizations minimize cluster overlap and provide for calculation of the isocontours at interactive speeds. Case studies show how this technique can be used to indicate multiple sets on a variety of common visualizations.
code_swarm: A Design Study in Organic Software Visualization
Authors: Michael Ogawa, Kwan-Liu Ma
Published at InfoVis, 2009

In May of 2008, we published online a series of software visualization videos using a method called code_swarm. Shortly thereafter, we made the code open source and its popularity took off. This paper is a study of our code swarm application, comprising its design, results and public response. We share our design methodology, including why we chose the organic information visualization technique, how we designed for both developers and a casual audience, and what lessons we learned from our experiment. We validate the results produced by code_swarm through a qualitative analysis and by gathering online user comments. Furthermore, we successfully released the code as open source, and the software community used it to visualize their own projects and shared their results as well. In the end, we believe code_swarm has positive implications for the future of organic information design and open source information visualization practice.
Comparing Dot and Landscape Spatializations for Visual Memory Differences
Authors: Melanie Tory, Colin Swindells, Rebecca Dreezer
Published at InfoVis, 2009

Spatialization displays use a geographic metaphor to arrange non-spatial data. For example, spatializations are commonly applied to document collections so that document themes appear as geographic features such as hills. Many common spatialization interfaces use a 3-D landscape metaphor to present data. However, it is not clear whether 3-D spatializations afford improved speed and accuracy for user tasks compared to similar 2-D spatializations. We describe a user study comparing users' ability to remember dot displays, 2-D landscapes, and 3-D landscapes for two different data densities (500 vs. 1000 points). Participants' visual memory was statistically more accurate when viewing dot displays and 3-D landscapes compared to 2-D landscapes. Furthermore, accuracy remembering a spatialization was significantly better overall for denser spatializations. Theseresults are of benefit to visualization designers who are contemplating the best ways to present data using spatialization techniques.
Configuring Hierarchical Layouts to Address Research Questions
Authors: Aidan Slingsby, Jason Dykes, Jo Wood
Published at InfoVis, 2009

We explore the effects of selecting alternative layouts in hierarchical displays that show multiple aspects of large multivariate datasets, including spatial and temporal characteristics. Hierarchical displays of this type condition a dataset by multiple discrete variable values, creating nested graphical summaries of the resulting subsets in which size, shape and colour can be used to show subset properties. These 'small multiples' are ordered by the conditioning variable values and are laid out hierarchically using dimensional stacking. Crucially, we consider the use of different layouts at different hierarchical levels, so that the coordinates of the plane can be used more effectively to draw attention to trends and anomalies in the data. We argue that these layouts should be informed by the type of conditioning variable and by the research question being explored. We focus on space-filling rectangular layouts that provide data-dense and rich overviews of data to address research questions posed in our exploratory analysis of spatial and temporal aspects of property sales in London. We develop a notation ('HiVE') that describes visualisation and layout states and provides reconfiguration operators, demonstrate its use for reconfiguring layouts to pursue research questions and provide guidelines for this process. We demonstrate how layouts can be related through animated transitions to reduce the cognitive load associated with their reconfiguration whilst supporting the exploratory process.
Conjunctive Visual Forms
Authors: Chris E. Weaver
Published at InfoVis, 2009

Visual exploration of multidimensional data is a process of isolating and extracting relationships within and between dimensions. Coordinated multiple view approaches are particularly effective for visual exploration because they support precise expression of heterogeneous multidimensional queries using simple interactions. Recent visual analytics research has made significant progress in identifying and understanding patterns of composed views and coordinations that support fast, flexible, and open-ended data exploration. What is missing is formalization of the space of expressible queries in terms of visual representation and interaction. This paper introduces the conjunctive visual form model in which visual exploration consists of interactively-driven sequences of transitions between visual states that correspond to conjunctive normal forms in boolean logic. The model predicts several new and useful ways to extend the space of rapidly expressible queries through addition of simple interactive capabilities to existing compositional patterns. Two recent related visual tools offer a subset of these capabilities, providing a basis for conjecturing about such extensions.
Constructing Overview + Detail Dendrogram-Matrix Views
Authors: Jin Chen, Alan M. MacEachren, Donna Peuquet
Published at InfoVis, 2009

A dendrogram that visualizes a clustering hierarchy is often integrated with a re-orderable matrix for pattern identification. The method is widely used in many research fields including biology, geography, statistics, and data mining. However, most dendrograms do not scale up well, particularly with respect to problems of graphical and cognitive information overload. This research proposes a strategy that links an overview dendrogram and a detail-view dendrogram, each integrated with a re-orderable matrix. The overview displays only a user-controlled, limited number of nodes that represent the ldquoskeletonrdquo of a hierarchy. The detail view displays the sub-tree represented by a selected meta-node in the overview. The research presented here focuses on constructing a concise overview dendrogram and its coordination with a detail view. The proposed method has the following benefits: dramatic alleviation of information overload, enhanced scalability and data abstraction quality on the dendrogram, and the support of data exploration at arbitrary levels of detail. The contribution of the paper includes a new metric to measure the ldquoimportancerdquo of nodes in a dendrogram; the method to construct the concise overview dendrogram from the dynamically-identified, important nodes; and measure for evaluating the data abstraction quality for dendrograms. We evaluate and compare the proposed method to some related existing methods, and demonstrating how the proposed method can help users find interesting patterns through a case study on county-level U.S. cervical cancer mortality and demographic data.
Document Cards: A Top Trumps Visualization for Documents
Authors: Hendrik Strobelt, Daniela Oelke, Christian Rohrdantz, Andreas Stoffel, Daniel A. Keim, Oliver Deussen
Published at InfoVis, 2009

Finding suitable, less space consuming views for a document's main content is crucial to provide convenient access to large document collections on display devices of different size. We present a novel compact visualization which represents the document's key semantic as a mixture of images and important key terms, similar to cards in a top trumps game. The key terms are extracted using an advanced text mining approach based on a fully automatic document structure extraction. The images and their captions are extracted using a graphical heuristic and the captions are used for a semi-semantic image weighting. Furthermore, we use the image color histogram for classification and show at least one representative from each non-empty image class. The approach is demonstrated for the IEEE InfoVis publications of a complete year. The method can easily be applied to other publication collections and sets of documents which contain images.
Exemplar-based Visualization of Large Document Corpus
Authors: Yanhua Chen, Lijun Wang, Ming Dong 0001, Jing Hua 0001
Published at InfoVis, 2009

With the rapid growth of the World Wide Web and electronic information services, text corpus is becoming available online at an incredible rate. By displaying text data in a logical layout (e.g., color graphs), text visualization presents a direct way to observe the documents as well as understand the relationship between them. In this paper, we propose a novel technique, Exemplar-based visualization (EV), to visualize an extremely large text corpus. Capitalizing on recent advances in matrix approximation and decomposition, EV presents a probabilistic multidimensional projection model in the low-rank text subspace with a sound objective function. The probability of each document proportion to the topics is obtained through iterative optimization and embedded to a low dimensional space using parameter embedding. By selecting the representative exemplars, we obtain a compact approximation of the data. This makes the visualization highly efficient and flexible. In addition, the selected exemplars neatly summarize the entire data set and greatly reduce the cognitive overload in the visualization, leading to an easier interpretation of large text corpus. Empirically, we demonstrate the superior performance of EV through extensive experiments performed on the publicly available text data sets.