Design studies are an increasingly popular form of problem-driven visualization research, yet there is little guidance available about how to do them effectively. In this paper we reflect on our combined experience conducting twenty-one design studies, as well reading and reviewing many more, extensive literature review other field work methods methodologies. Based foundation provide definitions, propose a methodological framework, practical for studies. We define study project in which...

Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data. For DR techniques to be useful exploratory data analysis, they need adapted human needs and domain-specific problems, ideally, interactively, on-the-fly. Many visual analytics systems have already demonstrated the benefits of tightly integrating with interactive visualizations. Nevertheless, general, structured understanding this integration missing. To address this, we systematically studied...

Various case studies in different application domains have shown the great potential of visual parameter space analysis to support validating and using simulation models. In order guide systematize research endeavors this area, we provide a conceptual framework for problems. The is based on our own experience structured visualization literature. It contains three major components: (1) data flow model that helps abstractly describe problems independent their domain; (2) set four navigation...

Moving beyond the dominant bag-of-words approach to sentiment analysis we introduce an alternative procedure based on distributed word embeddings. The strength of embeddings is ability capture similarities in meaning. We use as part a supervised machine learning which estimates levels negativity parliamentary speeches. procedure's accuracy evaluated with crowdcoded training sentences; its external validity through study patterns Austrian results show potential for social sciences.

To verify cluster separation in high-dimensional data, analysts often reduce the data with a dimension reduction (DR) technique, and then visualize it 2D Scatterplots, interactive 3D or Scatterplot Matrices (SPLOMs). With goal of providing guidance between these visual encoding choices, we conducted an empirical study which two human coders manually inspected broad set 816 scatterplots derived from 75 datasets, 4 DR techniques, 3 previously mentioned scatterplot techniques. Each coder scored...

Abstract We provide two contributions, a taxonomy of visual cluster separation factors in scatterplots, and an in‐depth qualitative evaluation recently proposed validated measures. initially intended to use these measures guidance for the dimension reduction (DR) techniques encoding (VE) choices, but found that they failed produce reliable results. To understand why, we conducted systematic data study covering broad collection 75 real synthetic high‐dimensional datasets, four DR techniques,...

We have created and made available to all a dataset with information about every paper that has appeared at the IEEE Visualization (VIS) set of conferences: InfoVis, SciVis, VAST, Vis. The each includes its title, abstract, authors, citations other papers in conference series, among many attributes. This article describes motivation for creating dataset, as well our process coalescing cleaning data, three visualizations we facilitate exploration data. data is meant be useful broad...

Labeling data instances is an important task in machine learning and visual analytics. Both fields provide a broad set of labeling strategies, whereby (and particular active learning) follows rather model-centered approach analytics employs user-centered approaches (visual-interactive labeling). have individual strengths weaknesses. In this work, we conduct experiment with three parts to assess compare the performance these different strategies. our study, (1) identify strategies for...

An increasing number of interactive visualization tools stress the integration with computational software like MATLAB and R to access a variety proven algorithms. In many cases, however, algorithms are used as black boxes that run completion in isolation which contradicts needs data exploration. This paper structures, formalizes, discusses possibilities enable user involvement ongoing computations. Based on structured characterization regarding intermediate feedback control, main...

We present a systematic review of 45S papers that report on evaluations in mixed and augmented reality (MR/AR) published ISMAR, CHI, IEEE VR, UIST over span 11 years (2009-2019). Our goal is to provide guidance for future MR/AR approaches. To this end, we characterize publications by paper type (e.g., technique, design study), research topic tracking, rendering), evaluation scenario algorithm performance, user performance), cognitive aspects perception, emotion), the context which were...

Situated visualization has become an increasingly popular research area in the community, fueled by advancements augmented reality (AR) technology and immersive analytics. Visualizing data spatial proximity to their physical referents affords new design opportunities considerations not present traditional visualization, which researchers are now beginning explore. However, AR community extensive history of designing graphics that displayed highly contexts. In this work, we leverage richness...

Recent advancements in robotics and human–machine interfaces enable new collaborative procedures that combine the strengths of machines humans. Compared to existing automation technologies timber prefabrication industry, human–robot collaboration (HRC) offers possibilities for increased flexibility productivity. This paper aims map out challenges opportunities HRC within context by constructing a conceptual framework. The framework is based on three pillars: (1) theories frameworks, (2)...

We propose the nested blocks and guidelines model for design validation of visualization systems. The extends previously proposed four-level by adding finer grained structure within each level, providing explicit mechanisms to capture discuss decision rationale. Blocks are outcomes process at a specific relationships between these blocks. algorithm technique levels describe choices, as do data abstraction whereas task domain situation identified outcome designer’s understanding requirements....

Abstract Visual quality measures seek to algorithmically imitate human judgments of patterns such as class separability, correlation, or outliers. In this paper, we propose a novel data‐driven framework for evaluating measures. The basic idea is take large set visually encoded data, scatterplots, with reliable “ground truth” judgements, and use human‐labeled data learn how well measure would predict judgements on previously unseen data. Measures can then be evaluated based predictive...

We present the results of a comprehensive analysis visualization paper keywords supplied for 4366 papers submitted to five main conferences. describe keywords, topic areas, and 10-year historic trends from two datasets: (1) standardized PCS taxonomy in use submissions IEEE InfoVis, Vis-SciVis, VAST, EuroVis, PacificVis since 2009 (2) author-chosen published Visualization conference series (now called VIS) 2004. Our research topics can serve as starting point (a) help create common vocabulary...

We investigate priming and anchoring effects on perceptual tasks in visualization. Priming or depict the phenomena that a stimulus might influence subsequent human judgments level, cognitive level by providing frame of reference. Using visual class separability scatterplots as an example task, we performed set five studies to potential existence effects. Our findings show - under certain circumstances such indeed exist. In other words, humans judge same scatterplot differently depending...

We characterize five task sequences related to visualizing dimensionally-reduced data, drawing from data collected interviews with ten analysts spanning six application domains, and our understanding of the technique literature. Our characterization visualization for fills a gap created by abundance proposed techniques tools that combine high-dimensional analysis, dimensionality reduction, visualization, is intended be used in design evaluation future tools. discuss implications existing...

Dimensionality reduction (DR) is a common strategy for visual analysis of labeled high-dimensional data. Low-dimensional representations the data help, instance, to explore class separability and spatial distribution Widely-used unsupervised DR methods like PCA do not aim maximize separation, while supervised LDA often assume certain distributions take perceptual capabilities humans into account. These issues make them ineffective complicated structures. Towards filling this gap, we present...

Appropriate choice of colors significantly aids viewers in understanding the structures multiclass scatterplots and becomes more important with a growing number data points groups. An appropriate color mapping is also an parameter for creation aesthetically pleasing scatterplot. Currently, users visualization software routinely rely on mappings that have been pre-defined by software. A default mapping, however, cannot ensure optimal perceptual separability between groups, sometimes may even...

We present RagRug, an open-source toolkit for situated analytics. The abilities of RagRug go beyond previous immersive analytics toolkits by focusing on specific requirements emerging when using augmented reality (AR) rather than virtual reality. combines state the art visual encoding capabilities with a comprehensive physical-virtual model, which lets application developers systematically describe physical objects in real world and their role AR. connect AR visualizations data streams from...