DevLan/vispubs huggingface dataset:
Vega-Lite: A Grammar of Interactive Graphics
Authors: Arvind Satyanarayan, Dominik Moritz, Kanit Wongsuphasawat, Jeffrey Heer
Published at InfoVis, 2016

We present Vega-Lite, a high-level grammar that enables rapid specification of interactive data visualizations. Vega-Lite combines a traditional grammar of graphics, providing visual encoding rules and a composition algebra for layered and multi-view displays, with a novel grammar of interaction. Users specify interactive semantics by composing selections. In Vega-Lite, a selection is an abstraction that defines input event processing, points of interest, and a predicate function for inclusion testing. Selections parameterize visual encodings by serving as input data, defining scale extents, or by driving conditional logic. The Vega-Lite compiler automatically synthesizes requisite data flow and event handling logic, which users can override for further customization. In contrast to existing reactive specifications, Vega-Lite selections decompose an interaction design into concise, enumerable semantic units. We evaluate Vega-Lite through a range of examples, demonstrating succinct specification of both customized interaction methods and common techniques such as panning, zooming, and linked selection.
Visplause: Visual Data Quality Assessment of Many Time Series Using Plausibility Checks
Authors: Clemens Arbesser, Florian Spechtenhauser, Thomas Mühlbacher, Harald Piringer
Published at InfoVis, 2016

Trends like decentralized energy production lead to an exploding number of time series from sensors and other sources that need to be assessed regarding their data quality (DQ). While the identification of DQ problems for such routinely collected data is typically based on existing automated plausibility checks, an efficient inspection and validation of check results for hundreds or thousands of time series is challenging. The main contribution of this paper is the validated design of Visplause, a system to support an efficient inspection of DQ problems for many time series. The key idea of Visplause is to utilize meta-information concerning the semantics of both the time series and the plausibility checks for structuring and summarizing results of DQ checks in a flexible way. Linked views enable users to inspect anomalies in detail and to generate hypotheses about possible causes. The design of Visplause was guided by goals derived from a comprehensive task analysis with domain experts in the energy sector. We reflect on the design process by discussing design decisions at four stages and we identify lessons learned. We also report feedback from domain experts after using Visplause for a period of one month. This feedback suggests significant efficiency gains for DQ assessment, increased confidence in the DQ, and the applicability of Visplause to summarize indicators also outside the context of DQ.
Visualization by Demonstration: An Interaction Paradigm for Visual Data Exploration
Authors: Bahador Saket, Hannah Kim, Eli T. Brown, Alex Endert
Published at InfoVis, 2016

Although data visualization tools continue to improve, during the data exploration process many of them require users to manually specify visualization techniques, mappings, and parameters. In response, we present the Visualization by Demonstration paradigm, a novel interaction method for visual data exploration. A system which adopts this paradigm allows users to provide visual demonstrations of incremental changes to the visual representation. The system then recommends potential transformations (Visual Representation, Data Mapping, Axes, and View Specification transformations) from the given demonstrations. The user and the system continue to collaborate, incrementally producing more demonstrations and refining the transformations, until the most effective possible visualization is created. As a proof of concept, we present VisExemplar, a mixed-initiative prototype that allows users to explore their data by recommending appropriate transformations in response to the given demonstrations.
Visualizing Social Media Content with SentenTree
Authors: Mengdie Hu, Krist Wongsuphasawat, John T. Stasko
Published at InfoVis, 2016

We introduce SentenTree, a novel technique for visualizing the content of unstructured social media text. SentenTree displays frequent sentence patterns abstracted from a corpus of social media posts. The technique employs design ideas from word clouds and the Word Tree, but overcomes a number of limitations of both those visualizations. SentenTree displays a node-link diagram where nodes are words and links indicate word co-occurrence within the same sentence. The spatial arrangement of nodes gives cues to the syntactic ordering of words while the size of nodes gives cues to their frequency of occurrence. SentenTree can help people gain a rapid understanding of key concepts and opinions in a large social media text collection. It is implemented as a lightweight application that runs in the browser.
VizItCards: A Card-Based Toolkit for Infovis Design Education
Authors: Shiqing He, Eytan Adar
Published at InfoVis, 2016

Shifts in information visualization practice are forcing a reconsideration of how infovis is taught. Traditional curricula that focused on conveying research-derived knowledge are slowly integrating design thinking as a key learning objective. In part, this is motivated by the realization that infovis is a wicked design problem, requiring a different kind of design work. In this paper we describe, VizItCards, a card-driven workshop developed for our graduate infovis class. The workshop is intended to provide practice with good design techniques and to simultaneously reinforce key concepts. VizItCards relies on principles of collaborative-learning and research on parallel design to generate positive collaborations and high-quality designs. From our experience of simulating a realistic design scenario in a classroom setting, we find that our students were able to meet key learning objectives and their design performance improved during the class. We describe variants of the workshop, discussing which techniques we think match to which learning goals.
VLAT: Development of a Visualization Literacy Assessment Test
Authors: Sukwon Lee, Sung-Hee Kim, Bum Chul Kwon
Published at InfoVis, 2016

The Information Visualization community has begun to pay attention to visualization literacy; however, researchers still lack instruments for measuring the visualization literacy of users. In order to address this gap, we systematically developed a visualization literacy assessment test (VLAT), especially for non-expert users in data visualization, by following the established procedure of test development in Psychological and Educational Measurement: (1) Test Blueprint Construction, (2) Test Item Generation, (3) Content Validity Evaluation, (4) Test Tryout and Item Analysis, (5) Test Item Selection, and (6) Reliability Evaluation. The VLAT consists of 12 data visualizations and 53 multiple-choice test items that cover eight data visualization tasks. The test items in the VLAT were evaluated with respect to their essentialness by five domain experts in Information Visualization and Visual Analytics (average content validity ratio = 0.66). The VLAT was also tried out on a sample of 191 test takers and showed high reliability (reliability coefficient omega = 0.76). In addition, we demonstrated the relationship between users' visualization literacy and aptitude for learning an unfamiliar visualization and showed that they had a fairly high positive relationship (correlation coefficient = 0.64). Finally, we discuss evidence for the validity of the VLAT and potential research areas that are related to the instrument.
WeightLifter: Visual Weight Space Exploration for Multi-Criteria Decision Making
Authors: Stephan Pajer, Marc Streit, Thomas Torsney-Weir, Florian Spechtenhauser, Torsten Möller, Harald Piringer
Published at InfoVis, 2016

A common strategy in Multi-Criteria Decision Making (MCDM) is to rank alternative solutions by weighted summary scores. Weights, however, are often abstract to the decision maker and can only be set by vague intuition. While previous work supports a point-wise exploration of weight spaces, we argue that MCDM can benefit from a regional and global visual analysis of weight spaces. Our main contribution is WeightLifter, a novel interactive visualization technique for weight-based MCDM that facilitates the exploration of weight spaces with up to ten criteria. Our technique enables users to better understand the sensitivity of a decision to changes of weights, to efficiently localize weight regions where a given solution ranks high, and to filter out solutions which do not rank high enough for any plausible combination of weights. We provide a comprehensive requirement analysis for weight-based MCDM and describe an interactive workflow that meets these requirements. For evaluation, we describe a usage scenario of WeightLifter in automotive engineering and report qualitative feedback from users of a deployed version as well as preliminary feedback from decision makers in multiple domains. This feedback confirms that WeightLifter increases both the efficiency of weight-based MCDM and the awareness of uncertainty in the ultimate decisions.
A Survey of Perceptually Motivated 3D Visualization of Medical Image Data
Authors: Bernhard Preim, Alexandra Baer, Douglas W. Cunningham, Tobias Isenberg 0001, Timo Ropinski
Published at EuroVis, 2016

This survey provides an overview of perceptually motivated techniques for the visualization of medical image data, including physics‐based lighting techniques as well as illustrative rendering that incorporate spatial depth and shape cues. Additionally, we discuss evaluations that were conducted in order to study the perceptual effects of these visualization techniques as compared to conventional techniques. These evaluations assessed depth and shape perception with depth judgment, orientation matching, and related tasks. This overview of existing techniques and their evaluation serves as a basis for defining the evaluation process of medical visualizations and to discuss a research agenda.
A Survey of Topology-based Methods in Visualization
Authors: Christian Heine 0002, Heike Leitte, Mario Hlawitschka, Federico Iuricich, Leila De Floriani, Gerik Scheuermann, Hans Hagen, Christoph Garth
Published at EuroVis, 2016

This paper presents the state of the art in the area of topology‐based visualization. It describes the process and results of an extensive annotation for generating a definition and terminology for the field. The terminology enabled a typology for topological models which is used to organize research results and the state of the art. Our report discusses relations among topological models and for each model describes research results for the computation, simplification, visualization, and application. The paper identifies themes common to subfields, current frontiers, and unexplored territory in this research area.
A Survey on Visual Analysis Approaches for Financial Data
Authors: Sungahn Ko, Isaac Cho, Shehzad Afzal, Calvin Yau, Junghoon Chae, Abish Malik, Kaethe Beck, Yun Jang, William Ribarsky, David S. Ebert
Published at EuroVis, 2016

Market participants and businesses have made tremendous efforts to make the best decisions in a timely manner under varying economic and business circumstances. As such, decision‐making processes based on Financial data have been a popular topic in industries. However, analyzing Financial data is a non‐trivial task due to large volume, diversity and complexity, and this has led to rapid research and development of visualizations and visual analytics systems for Financial data exploration. Often, the development of such systems requires researchers to collaborate with Financial domain experts to better extract requirements and challenges in their tasks. Work to systematically study and gather the task requirements and to acquire an overview of existing visualizations and visual analytics systems that have been applied in Financial domains with respect to real‐world data sets has not been completed. To this end, we perform a comprehensive survey of visualizations and visual analytics. In this work, we categorize Financial systems in terms of data sources, applied automated techniques, visualization techniques, interaction, and evaluation methods. For the categorization and characterization, we utilize existing taxonomies of visualization and interaction. In addition, we present task requirements extracted from interviews with domain experts in order to help researchers design better systems with detailed goals.
A Visual Analytics Framework for Microblog Data Analysis at Multiple Scales of Aggregation
Authors: Jiawei Zhang 0003, Benjamin Ahlbrand, Abish Malik, Junghoon Chae, Zhiyu Min, Sungahn Ko, David S. Ebert
Published at EuroVis, 2016

Real‐time microblogs can be utilized to provide situational awareness during emergency and disaster events. However, the utilization of these datasets requires the decision makers to perform their exploration and analysis across a range of data scales from local to global, while maintaining a cohesive thematic context of the transition between the different granularity levels. The exploration of different information dimensions at the varied data and human scales remains to be a non‐trivial task. To this end, we present a visual analytics situational awareness environment that supports the real‐time exploration of microblog data across multiple scales of analysis. We classify microblogs based on a fine‐grained, crisis‐related categorization approach, and visualize the spatiotemporal evolution of multiple categories by coupling a spatial lens with a glyph‐based visual design. We propose a transparency‐based spatial context preserving technique that maintains a smooth transition between different spatial scales. To evaluate our system, we conduct user studies and provide domain expert feedback.
Arcs, Angles, or Areas: Individual Data Encodings in Pie and Donut Charts
Authors: Drew Skau, Robert Kosara
Published at EuroVis, 2016

Pie and donut charts have been a hotly debated topic in the visualization community for some time now. Even though pie charts have been around for over 200 years, our understanding of the perceptual factors used to read data in them is still limited. Data is encoded in pie and donut charts in three ways: arc length, center angle, and segment area. For our first study, we designed variations of pie charts to test the importance of individual encodings for reading accuracy. In our second study, we varied the inner radius of a donut chart from a filled pie to a thin outline to test the impact of removing the central angle. Both studies point to angle being the least important visual cue for both charts, and the donut chart being as accurate as the traditional pie chart.
AVOCADO: Visualization of Workflow-Derived Data Provenance for Reproducible Biomedical Research
Authors: Holger Stitz, S. Luger, Marc Streit, Nils Gehlenborg
Published at EuroVis, 2016

A major challenge in data‐driven biomedical research lies in the collection and representation of data provenance information to ensure that findings are reproducibile. In order to communicate and reproduce multi‐step analysis workflows executed on datasets that contain data for dozens or hundreds of samples, it is crucial to be able to visualize the provenance graph at different levels of aggregation. Most existing approaches are based on node‐link diagrams, which do not scale to the complexity of typical data provenance graphs. In our proposed approach, we reduce the complexity of the graph using hierarchical and motif‐based aggregation. Based on user action and graph attributes, a modular degree‐of‐interest (DoI) function is applied to expand parts of the graph that are relevant to the user. This interest‐driven adaptive approach to provenance visualization allows users to review and communicate complex multi‐step analyses, which can be based on hundreds of files that are processed by numerous workflows. We have integrated our approach into an analysis platform that captures extensive data provenance information, and demonstrate its effectiveness by means of a biomedical usage scenario.
BubbleNet: A Cyber Security Dashboard for Visualizing Patterns
Authors: Sean McKenna, Diane Staheli, Cody Fulcher, Miriah D. Meyer
Published at EuroVis, 2016

The field of cyber security is faced with ever‐expanding amounts of data and a constant barrage of cyber attacks. Within this space, we have designed BubbleNet as a cyber security dashboard to help network analysts identify and summarize patterns within the data. This design study faced a range of interesting constraints from limited time with various expert users and working with users beyond the network analyst, such as network managers. To overcome these constraints, the design study employed a user‐centered design process and a variety of methods to incorporate user feedback throughout the design of BubbleNet. This approach resulted in a successfully evaluated dashboard with users and further deployments of these ideas in both research and operational environments. By explaining these methods and the process, it can benefit future visualization designers to help overcome similar challenges in cyber security or alternative domains.
Comparing Bar Chart Authoring with Microsoft Excel and Tangible Tiles
Authors: Tiffany Wun, Jennifer Payne, Samuel Huron, Sheelagh Carpendale
Published at EuroVis, 2016

Providing tools that make visualization authoring accessible to visualization non‐experts is a major research challenge. Currently the most common approach to generating a visualization is to use software that quickly and automatically produces visualizations based on templates. However, it has recently been suggested that constructing a visualization with tangible tiles may be a more accessible method, especially for people without visualization expertise. There is still much to be learned about the differences between these two visualization authoring practices. To better understand how people author visualizations in these two conditions, we ran a qualitative study comparing the use of software to the use of tangible tiles, for the creation of bar charts. Close observation of authoring activities showed how each of the following varied according to the tool used: 1) sequences of action; 2) distribution of time spent on different aspects of the InfoVis pipeline; 3) pipeline task separation; and 4) freedom to manipulate visual variables. From these observations, we discuss the implications of the variations in activity sequences, noting tool design considerations and pointing to future research questions.
Comparing Node-Link and Node-Link-Group Visualizations From An Enjoyment Perspective
Authors: Bahador Saket, Carlos Scheidegger, Stephen G. Kobourov
Published at EuroVis, 2016

While evaluation studies in visualization often involve traditional performance measurements, there has been a concerted effort to move beyond time and accuracy. Of these alternative aspects, memorability and recall of visualizations have been recently considered, but other aspects such as enjoyment and engagement are not as well explored. We study the enjoyment of two different visualization methods through a user study. In particular, we describe the results of a three‐phase experiment comparing the enjoyment of two different visualizations of the same relational data: node‐link and node‐link‐group visualizations. The results indicate that the participants in this study found node‐link‐group visualizations more enjoyable than node‐link visualizations.
Composite Flow Maps
Authors: Daniel Cornel, Artem Konev, Bernhard Sadransky, Zsolt Horváth, Andrea Brambilla, Ivan Viola, Jürgen Waser
Published at EuroVis, 2016

Flow maps are widely used to provide an overview of geospatial transportation data. Existing solutions lack the support for the interactive exploration of multiple flow components at once. Flow components are given by different materials being transported, different flow directions, or by the need for comparing alternative scenarios. In this paper, we combine flows as individual ribbons in one composite flow map. The presented approach can handle an arbitrary number of sources and sinks. To avoid visual clutter, we simplify our flow maps based on a force‐driven algorithm, accounting for restrictions with respect to application semantics. The goal is to preserve important characteristics of the geospatial context. This feature also enables us to highlight relevant spatial information on top of the flow map such as traffic conditions or accessibility. The flow map is computed on the basis of flows between zones. We describe a method for auto‐deriving zones from geospatial data according to application requirements. We demonstrate the method in real‐world applications, including transportation logistics, evacuation procedures, and water simulation. Our results are evaluated with experts from corresponding fields.
ConToVi: Multi-Party Conversation Exploration using Topic-Space Views
Authors: Mennatallah El-Assady, Valentin Gold, Carmela Acevedo, Christopher Collins 0001, Daniel A. Keim
Published at EuroVis, 2016

We introduce a novel visual analytics approach to analyze speaker behavior patterns in multi‐party conversations. We propose Topic‐Space Views to track the movement of speakers across the thematic landscape of a conversation. Our tool is designed to assist political science scholars in exploring the dynamics of a conversation over time to generate and prove hypotheses about speaker interactions and behavior patterns. Moreover, we introduce a glyph‐based representation for each speaker turn based on linguistic and statistical cues to abstract relevant text features. We present animated views for exploring the general behavior and interactions of speakers over time and interactive steady visualizations for the detailed analysis of a selection of speakers. Using a visual sedimentation metaphor we enable the analysts to track subtle changes in the flow of a conversation over time while keeping an overview of all past speaker turns. We evaluate our approach on real‐world datasets and the results have been insightful to our domain experts.
Critical Points of Gaussian-Distributed Scalar Fields on Simplicial Grids
Authors: Tom Liebmann, Gerik Scheuermann
Published at EuroVis, 2016

Simulations and measurements often result in scalar fields with uncertainty due to errors or output sensitivity estimates. Methods for analyzing topological features of such fields usually are not capable of handling all aspects of the data. They either are not deterministic due to using Monte Carlo approaches, approximate the data with confidence intervals, or miss out on incorporating important properties, such as correlation. In this paper, we focus on the analysis of critical points of Gaussian‐distributed scalar fields. We introduce methods to deterministically extract critical points, approximate their probability with high precision, and even capture relations between them resulting in an abstract graph representation. Unlike many other methods, we incorporate all information contained in the data including global correlation. Our work therefore is a first step towards a reliable and complete description of topological features of Gaussian‐distributed scalar fields.